Medicine, Faculty of
Medicine, Department of
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UBCV
Schoenthal, Tison David
Master of Science - MSc
University of British Columbia
Hypoxic ischemic brain injury (HIBI) is the resultant cerebral injury acquired after cardiac arrest stemming from cerebral ischemia during circulatory arrest and reperfusion following return of spontaneous circulation. Regrettably, HIBI outcomes remain poor, with survivors commonly experiencing neurological disabilities and neuropsychiatric sequelae. A cornerstone of HIBI management focusses on optimizing cerebral oxygen delivery and utilization. Central to this objective, the manipulation of arterial blood gases has come under scrutiny as a potential therapeutic approach, specifically the implementation of normobaric hyperoxia and mild hypercapnia. In study 1, normobaric hyperoxia was administered in post-cardiac arrest HIBI patients for 6 hours, targeting an arterial oxygen tension (PaO₂) of 200–300mmHg. Patients were monitored with jugular venous bulb oximetry, near infrared spectrometry and hemodynamic bedside monitoring in the ICU, with arterial and jugular venous blub blood samples taken at baseline, 2-, 4-, and the 6- hour mark, and following the resumption of normoxemia (PaO₂ 80–120mmHg) with additional blood samples taken at the 12- and 24-hour marks. The jugular venous oxygen saturation and regional saturation of oxygen did not increase during exposure to normobaric hyperoxia. Neurofilament light, a blood-based biomarker reflecting axonal injury, was significantly elevated at the 6-hour mark. In study 2, mild hypercapnia was administered for 2 hours in post-cardiac arrest HIBI patients who were monitored with transcranial Doppler ultrasound (TCD), jugular venous bulb oximetry and hemodynamic bedside monitoring. Baseline serum and plasma samples were taken from the in situ arterial and jugular venous bulb catheters, and then repeated at the 1- and 2- hour marks. TCD was also conducted in 15 healthy humans who were exposed to mild hypercapnia for control comparisons. Arterial CO₂ levels significantly increased during the study; however, no differences were seen in the jugular venous bulb oxygen saturation or cerebral oxygen extraction fraction. The cerebral arterio-venous difference of ubiquitin carboxyl hydrolase L1, a biomarker of neuron cell body injury, decreased at the 1-hour mark. HIBI patients also demonstrated decreased cerebrovascular reactivity and conductance compared to healthy humans when exposed to mild hypercapnia.
THE EFFECTS OF ARTERIAL OXYGEN AND CARBON DIOXIDE TENSION ON CEREBRAL VASCULAR PHYSIOLOGY IN HYPOXIC ISCHEMIC BRAIN INJURY AFTER CARDIAC ARREST by Tison David Schoenthal B.Sc., The University of British Columbia, 2016 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) December 2023 © Tison David Schoenthal, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: The Effects of Arterial Oxygen and Carbon Dioxide Tension on Cerebral Vascular Physiology in Hypoxic Ischemic Brain Injury After Cardiac Arrest submitted by Tison David Schoenthal in partial fulfilment of the requirements for the degree of Master of Science in Experimental Medicine Examining Committee: Dr. Mypinder Sekhon, Clinical Associate Professor, Department of Medicine, UBC Supervisor Dr. Donald Griesdale, Assistant Professor, Department of Medicine, UBC Supervisory Committee Member Dr. Shananjit Thiara, Clinical Assistant Professor, Department of Medicine, UBC Additional Examiner Dr. Kurt Smith, Associate Professor, School of Exercise Science, Physical & Health Education, University of Victoria Additional Examiner iii Abstract Hypoxic ischemic brain injury (HIBI) is the resultant cerebral injury acquired after cardiac arrest stemming from cerebral ischemia during circulatory arrest and reperfusion following return of spontaneous circulation. Regrettably, HIBI outcomes remain poor, with survivors commonly experiencing neurological disabilities and neuropsychiatric sequelae. A cornerstone of HIBI management focusses on optimizing cerebral oxygen delivery and utilization. Central to this objective, the manipulation of arterial blood gases has come under scrutiny as a potential therapeutic approach, specifically the implementation of normobaric hyperoxia and mild hypercapnia. In study 1, normobaric hyperoxia was administered in post-cardiac arrest HIBI patients for 6 hours, targeting an arterial oxygen tension (PaO2) of 200–300mmHg. Patients were monitored with jugular venous bulb oximetry, near infrared spectrometry and hemodynamic bedside monitoring in the ICU, with arterial and jugular venous blub blood samples taken at baseline, 2-, 4-, and the 6- hour mark, and following the resumption of normoxemia (PaO2 80–120mmHg) with additional blood samples taken at the 12- and 24-hour marks. The jugular venous oxygen saturation and regional saturation of oxygen did not increase during exposure to normobaric hyperoxia. Neurofilament light, a blood-based biomarker reflecting axonal injury, was significantly elevated at the 6-hour mark. In study 2, mild hypercapnia was administered for 2 hours in post-cardiac arrest HIBI patients who were monitored with transcranial Doppler ultrasound (TCD), jugular venous bulb oximetry and hemodynamic bedside monitoring. Baseline serum and plasma samples were taken from the in situ arterial and jugular venous bulb catheters, and then repeated at the 1- and 2- hour marks. TCD was also conducted in 15 healthy humans who were exposed to mild hypercapnia for control comparisons. Arterial CO2 levels significantly iv increased during the study; however, no differences were seen in the jugular venous bulb oxygen saturation or cerebral oxygen extraction fraction. The cerebral arterio-venous difference of ubiquitin carboxyl hydrolase L1, a biomarker of neuron cell body injury, decreased at the 1-hour mark. HIBI patients also demonstrated decreased cerebrovascular reactivity and conductance compared to healthy humans when exposed to mild hypercapnia. v Lay Summary Cardiac arrest occurs when the heart stops beating and fails to deliver blood and oxygen to the body and brain. The outcomes for cardiac arrest patients are poor, indicating the need to identify effective therapies. A central aim of post-cardiac arrest care is to optimize oxygen delivery to the injured brain. This can ostensibly be achieved by increasing the amount of oxygen administered to a patient or augmenting the flow of blood to the brain. In two separate studies, we aimed to assess the use of elevated levels of oxygen and carbon dioxide in the blood and monitored physiologic parameters. In both studies, we were able to successfully increase the amount of oxygen and carbon dioxide in the blood. However, the indices of cerebral oxygenation and brain injury did not improve indicating that additional mechanisms of brain injury are at play which prohibit the effective use of solely ventilator-based management strategies to mitigate post-cardiac arrest brain injury. vi Preface Sections of Chapter 1 are published. Schoenthal T, Hoiland RL, Griesdale DG, Sekhon MS. Cerebral Hemodynamics After Cardiac Arrest: Implications for Clinical Management. Minera Anesthesiolog. 2023;89:824-33. DOI: 10.23736/S0374-9393.23.17268-3. I conducted the literature review and wrote the original manuscript. Editing of the manuscript was completed by Hoiland, RL, Griesdale. DG, and Sekhon, MS. Chapter 2: The effect of normobaric hyperoxia on cerebral oxygen uptake and metabolism in hypoxic ischemic brain injury, was approved by the UBC Clinical Research Ethics Board (H16-03076). M. Sekhon developed the original research question. The data analysis in Chapter 2 are my original work. Chapter 3: The effect of mild hypercapnia on mitigating secondary hypoxic ischemic brain injury following cardiac arrest, was approved by the UBC Clinical Research Ethics Board (H17-02823). M. Sekhon developed the original research question. The data analysis in Chapter 3 are my original work. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ............................................................................................................................... xii List of Figures ............................................................................................................................. xiii List of Symbols ........................................................................................................................... xiv List of Abbreviations ...................................................................................................................xv Acknowledgements .................................................................................................................. xviii Dedication ................................................................................................................................... xix Chapter 1: Introduction ................................................................................................................1 1.1 The Etiology of Cardiac Arrest ....................................................................................... 1 1.2 Pathophysiology of HIBI ................................................................................................ 2 1.2.1 Primary Injury and Cellular Effects ........................................................................ 2 1.2.2 Secondary Injury and Hemodynamic Phases .......................................................... 3 1.3 Clinical CDO2 Variables and HIBI ................................................................................. 6 1.3.1 Arterial Carbon Dioxide Tension (PaCO2) ............................................................. 7 1.3.2 Arterial Oxygen Tension (PaO2) ............................................................................. 8 1.3.3 Mean Arterial Pressure (MAP) ............................................................................... 9 1.3.4 Hemoglobin (Hgb) Concentration ........................................................................ 12 1.3.5 Targeted Temperature Management (TTM) ......................................................... 13 viii 1.4 Patient-Specific Phenotypes of HIBI ............................................................................ 15 1.4.1 Cerebral Edema ..................................................................................................... 17 1.5 Methodology ................................................................................................................. 18 1.5.1 Neuromonitoring ................................................................................................... 18 1.5.1.1 Near Infrared Spectrometry (NIRS) .................................................................. 19 1.5.1.2 Jugular Venous Bulb Oximetry (SjvO2) ........................................................... 20 1.5.1.3 Transcranial Doppler Ultrasonography (TCD) ................................................. 21 1.5.1.4 ICM+ Software Program .................................................................................. 23 1.5.1.5 Utilizing an Arterial to Venous Difference in Measurements .......................... 23 1.5.2 Blood-Based Biomarkers of Brain Injury ............................................................. 25 1.5.2.1 Current Use of Blood-Based Brain Injury Biomarkers ..................................... 25 1.5.2.2 Location of Blood-Based Brain Injury Biomarkers .......................................... 26 1.5.2.3 Inflammatory Cytokines ................................................................................... 26 1.5.2.4 Measuring Blood-Based Brain Injury Biomarkers ........................................... 27 1.5.2.5 Advantages and Limitations of Blood-Based Brain Injury Biomarkers ........... 27 1.5.2.6 Sensitivity and Specificity ................................................................................ 28 1.5.3 Cardiovascular and Respiratory Physiology Measures ......................................... 29 1.5.3.1 Arterial Blood Gases ......................................................................................... 29 1.5.3.2 End-tidal CO2 .................................................................................................... 30 1.5.3.3 Dynamic End-tidal Forcing ............................................................................... 32 1.5.4 Physiologic Metrics of CO2 Reactivity ................................................................. 33 1.6 Thesis Aims and Hypotheses ........................................................................................ 34 ix 1.7 Study 1: The Effect of Normobaric Hyperoxia on Cerebral Oxygen Uptake and Metabolism in Hypoxic Ischemic Brain Injury ........................................................................ 34 1.7.1 Study 1 Aims ........................................................................................................ 34 1.7.2 Study 1 Hypothesis ............................................................................................... 34 1.8 Study 2: The Effect of Mild Hypercapnia on Mitigating Secondary Hypoxic Ischemic Brain Injury Following Cardiac Arrest ..................................................................................... 35 1.8.1 Study 2 Aims ........................................................................................................ 35 1.8.2 Study 2 Hypothesis ............................................................................................... 35 Chapter 2: The effect of normobaric hyperoxia on cerebral oxygen uptake and metabolism in hypoxic ischemic brain injury ................................................................................................36 2.1 Study 1: Introduction .................................................................................................... 36 2.2 Study 1: Methods .......................................................................................................... 37 2.2.1 Study 1: Population ............................................................................................... 37 2.2.2 Study 1: Cardiac Arrest Management ................................................................... 38 2.2.3 Study 1: Neurophysiologic Monitoring ................................................................ 38 2.2.4 Study 1: Data Collection ....................................................................................... 38 2.2.5 Study 1: Blood-Based Biomarker of Brain Injury Analysis ................................. 39 2.2.6 Study 1: Calculations ............................................................................................ 40 2.2.7 Study 1: Statistical Analysis ................................................................................. 40 2.3 Study 1: Results ............................................................................................................ 41 2.4 Study 1: Discussion ...................................................................................................... 51 2.5 Study 1: Conclusion ...................................................................................................... 54 x Chapter 3: The effect of mild hypercapnia on mitigating secondary hypoxic ischemic brain injury following cardiac arrest ...................................................................................................55 3.1 Study 2: Introduction .................................................................................................... 55 3.2 Study 2: Methods .......................................................................................................... 56 3.2.1 Study 2: Population ............................................................................................... 57 3.2.1.1 Study 2: Healthy Control Population ................................................................ 57 3.2.2 Study 2: Cardiac Arrest Management ................................................................... 57 3.2.3 Study 2: Neurophysiologic Monitoring ................................................................ 58 3.2.3.1 Study 2: Healthy Control Monitoring ............................................................... 58 3.2.4 Study 2: Data Collection ....................................................................................... 59 3.2.4.1 Study 2: Healthy Control Data Collection ........................................................ 59 3.2.4.2 Study 2: Blood-Based Biomarkers of Brain Injury Analysis ............................ 59 3.2.5 Study 2: Calculations ............................................................................................ 60 3.2.6 Study 2: Statistical Analysis ................................................................................. 62 3.3 Study 2: Results ............................................................................................................ 63 3.3.1 Study 2: Results - Middle Cerebral Artery Data in HIBI Patients ........................ 68 3.3.2 Study 2: Results - O2EF Data in HIBI Patients ..................................................... 68 3.3.3 Study 2: Results – Blood-Based Biomarker of Brain Injury Data in HIBI Patients… .............................................................................................................................. 68 3.3.4 Study 2: Results - Comparing Middle Cerebral Artery Data of Controls to HIBI Patients… .............................................................................................................................. 71 3.3.5 Study 2: Results – Blood-Based Biomarkers of Brain Injury Data in Healthy Controls… ............................................................................................................................. 74 xi 3.4 Study 2: Discussion ...................................................................................................... 76 3.5 Study 2: Conclusion ...................................................................................................... 79 Chapter 4: Conclusion .................................................................................................................80 References .....................................................................................................................................85 xii List of Tables Table 2-1: HIBI patient demographics for hyperoxia study ......................................................... 42 Table 2-2: Clinical management of HIBI patients during hyperoxia ........................................... 43 Table 2-3 HIBI blood gas data during hyperoxia ......................................................................... 46 Table 3-1 HIBI patient demographics for hypercapnia study ....................................................... 64 Table 3-2 Clinical management of HIBI patient during hypercapnia ........................................... 65 Table 3-3 Healthy control demographics ...................................................................................... 65 Table 3-4 HIBI patient blood gas data during hypercapnia .......................................................... 67 xiii List of Figures Figure 1-1: Cerebral hemodynamics and cardiac arrest.. ............................................................... 6 Figure 1-2: Differential phenotypes of hypoxic ischemic brain injury. ........................................ 16 Figure 1-3: A picture of a jugular venous bulb catheter in a healthy participant. ........................ 21 Figure 1-4: An Example of TCD being used on a healthy participant. ........................................ 22 Figure 1-5: Blood-based biomarkers of brain injury. ................................................................... 24 Figure 1-6: Example of a radial arterial line ................................................................................. 30 Figure 1-7: An example of a capnography. ................................................................................. 32 Figure 2-1:Interventional variables during normobaric hyperoxia exposure.. ............................. 44 Figure 2-2:Indices of cerebral oxygenation.. ................................................................................ 47 Figure 2-3:Serum brain injury biomarkers. .................................................................................. 49 Figure 2-4:Serum brain injury inflammatory markers. ................................................................. 51 Figure 3-1:Comparing the effects of elevated arterial carbon dioxide on the middle cerebral artery, jugular venous oxygen saturation, and oxygen extraction fraction in healthy controls (Panel A series) to patients with HIBI (Panel B series).. .............................................................. 66 Figure 3-2: Serum brain injury biomarkers in the HIBI patients. ................................................. 70 Figure 3-3: Serum inflammatory biomarkers in the HIBI patients. .............................................. 71 Figure 3-4:Comparing absolute and relative MCACVR and absolute and relative MCA CVC reactivity in controls (blue) to HIBI patients (red). ...................................................................... 73 Figure 3-5: Serum brain injury biomarkers in the healthy patients. ............................................. 75 Figure 3-6: Serum inflammatory biomarkers in the healthy patients. .......................................... 76 xiv List of Symbols ~ Approximately C Celsius ˚ Degrees ≥ Equal to or greater than > Greater than < Less than xv List of Abbreviations a-v Arterial to venous difference ANOVA Analysis of Variance AQP4 Aquaporin 4 BL Baseline CaO2 Arterial oxygen content CBF Cerebral blood flow CDO2 Cerebral delivery of oxygen CO2 Carbon dioxide Cox Cerebral oximetry index CPC Cerebral performance category CPP Cerebral perfusion pressure CPR Cardiopulmonary resuscitation CvO2 Venous oxygen content EDTA Ethylenediaminetetraacetic acid ELISA Enzyme-linked immunosorbent assay FiO2 Fraction of inspired oxygen GFAP Glial fibrillary acidic protein Hgb Hemoglobin HIBI Hypoxic ischemic brain injury Hx Hypercapnia ICM+ Multimodal Neuro-Intensive care monitoring xvi ICP Intracranial pressure ICU Intensive care unit IL-10 Interleukin 10 IL-1β Interleukin 1 beta IL-6 Interleukin 6 IQR Interquartile range MAP Mean arterial pressure MCAv Middle cerebral artery velocity MCACVR Middle cerebral artery reactivity MCA CVC Middle cerebral artery cerebrovascular conductance Nf-L Neurofilament light chain NH Normobaric hyperoxia NIRS Near infrared spectrometry NSE Neuron specific enolase O2 Oxygen O2EF Oxygen extraction fraction PaCO2 Arterial carbon dioxide tension PaO2 Arterial oxygen tension PbtO2 Brain tissue oxygen tension PRx Pressure reactivity index PvCO2 Venous carbon dioxide tension PvO2 Jugular venous bulb oxygen tension rmANOVA Repeated measures Analysis of Variance xvii ROSC Return of spontaneous circulation rSO2 Regional saturation of oxygen SaO2 Arterial oxygen saturation Simoa Single-molecule assay technology SjvO2 Jugular venous bulb oximetry SpO2 Peripheral oxygen saturation SST Serum separator tube TCD Transcranial Doppler ultrasonography TNF-α Tumor necrosis factor alpha TTM Targeted temperature management UCH-L1 Ubiquitin carboxy terminal hydrolase L1 V1 Arginine receptor V2 Arginine receptor xviii Acknowledgements To my supervisor, Dr. Mypinder Sekhon, thank you for giving me the opportunity to pursue my goal of getting a graduate degree. Not only do I have the privilege of having you as my supervisor, but I’ve had the pleasure to work alongside you in the ICU. Your continued support as a role model and encouragement has helped me tremendously through this journey and I cannot thank you enough. To Dr. Ryan Hoiland, if it wasn’t for you, I would have never been introduced to Myp in an academic setting and the idea of me doing a masters with the ICU Research Group would have never happened. Without you, none of this would have been possible. To Dr. Don Griesdale and Dr. Sonny Thiara, Denise Foster, Rebecca Grey, and the rest of the ICU Research Group, thank you for your continued support and guidance during this journey. To my fellow colleagues in the Respiratory Therapy Department, thank you for your support and curiosity in what I was doing. To my parents, Dave and Heather Schoenthal, thank you for your support and raising me to try and achieve my goals, I will always be in debt to your generosity, your love, and support you have shown me over the past 31 years. To my wife, Julie, thank you for pushing me to become the best version of myself and for being by my side during this journey. It may not have been always easy to support me, but I am forever grateful for you. xix Dedication I dedicate this to my parents, Thank you for everything you two do for me. 1 Chapter 1: Introduction Hypoxic ischemic brain injury (HIBI) is a devastating injury that results from cerebral ischemia during cardiac arrest and reperfusion injury following the return of spontaneous circulation. Clinical outcomes remain poor with survival rates for out-of-hospital or in-hospital cardiac arrest, ranging between 10 and 25%,12 respectively. In patients resuscitated from cardiac arrest, HIBI is the primary determinant of outcome with approximately 70-80% of post-cardiac arrest mortality attributable to HIBI.3 In survivors, long term sequalae manifest as moderate to severe functional impairments with considerable neuropsychiatric co-morbidities.2,4 The relative paucity of effective clinical interventions in this field, coupled with the dismal outcomes, underscores the urgent need to identify novel and efficacious therapies and patient management strategies. In doing so, a focus on the pathophysiology of HIBI is required to provide clinicians and researchers with the requisite foundation to conduct translational studies. 1.1 The Etiology of Cardiac Arrest Cardiac arrest presents as either a shockable rhythm, such as ventricular fibrillation and pulseless ventricular tachycardia, or non-shockable rhythm, including pulseless electrical activity and asystole. Individuals suffering from a cardiac arrest with an initial shockable rhythm have improved chances of survival and favourable outcomes compared to those who experience non-shockable rhythms.5 The etiology of cardiac arrest with non-shockable rhythms includes respiratory failure (severe hypoxia, asphyxia), trauma, toxicologic ingestions, severe hemorrhage, electrolyte disturbances or severe derangements in body temperature.6 2 1.2 Pathophysiology of HIBI The pathophysiology of HIBI is characterized by primary and secondary injuries that occur during circulatory arrest (cerebral ischemia) and following return of spontaneous circulation (cerebral reperfusion).7 During cardiac arrest, cessation of cerebral blood flow (CBF) and cerebral delivery of oxygen (CDO2) leads to brain tissue ischemia,8 while return of spontaneous circulation and the associated cerebral reperfusion consequently initiates a multitude of secondary injury cascades. A core aspect of secondary injury is the dysregulation of cerebral hemodynamics, wherein physiologic perturbations that increase the potential for inadequate CDO2 (e.g., hypotension, hypocapnia, and/or anemia) are associated with worse outcomes following return of spontaneous circulation.9–11 The human brain is particularly vulnerable to reductions in CDO2 (especially in the injured state) due to its high metabolic demand and inherently limited storage of metabolic substrates.12 As such, increased attention has been directed towards management strategies that are thought to augment CDO2 in an effort to mitigate secondary injury and improve outcomes in post-cardiac arrest patients with HIBI. Regrettably, clinical trials have not observed clinical efficacy of management strategies that would be expected to increase CDO2.13–15 The discordance between the perceived importance of optimizing CDO2 and lack of improved clinical outcomes observed to date may be explained by nuances of HIBI pathophysiology. 1.2.1 Primary Injury and Cellular Effects The primary ischemic injury that occurs during circulatory arrest is often short in duration (i.e., minutes), whereas the secondary injury may occur over a period of hours to days following return of spontaneous circulation.8,16 Following the cessation of CBF and CDO2 during cardiac arrest,17 aerobic metabolism is halted with a resultant decline of adenosine triphosphate.8 This 3 abrupt depletion of adenosine triphosphate leads to the dysfunction of membrane ion channels, aberrant ion gradients, and the near immediate absence of action potential propagation, which acutely manifests as loss of consciousness. This ionic disturbance, wherein neuronal cells undergo mass depolarization, leads to an excessive influx of sodium and calcium,18 hyperosmolarity, and consequent cytotoxic edema.19 Increased intracellular calcium concentration will also lead to excessive glutamate release and excitotoxic damage. With the initiation of cardiopulmonary resuscitation (CPR), partial resumption of CBF and CDO2 ensues. If initiated prior to complete reversal of neuron ion gradients (i.e. immediate bystander CPR, witnessed cardiac arrest), the partial resumption of CDO2 with CPR can provide sufficient energy substrate and oxygen delivery to injured neurons to sustain cellular integrity.8 During the CPR phase of resuscitation (partial reperfusion) additional mechanisms implicated in HIBI pathophysiology include generation of reactive oxygen species,20 activation of lipases and proteases,18 mitochondrial dysfunction,21 and cellular death.22 1.2.2 Secondary Injury and Hemodynamic Phases Following the restoration of cardiac output, cerebral hemodynamics are dynamic over time and characterized by three phases: a) early hyperemia (~0-30min after return of spontaneous circulation); b) no-reflow (~30min to 72hr after return of spontaneous circulation); and c) restoration of normal CBF (~ > 72hr after return of spontaneous circulation) (Figure 1.1A).8,23 During early hyperemia, the exaggerated reperfusion of the previously ischemic brain tissue triggers a series of injurious signaling cascades.18 Concomitant administration of exogenous vasopressors and inotropes (e.g., adrenaline) may partially account for the supranormal CBF during this immediate post-resuscitation phase. Other potential contributors to early hyperemia 4 include the inflammatory cascade,18 arterial blood gas disturbances (mild post-resuscitation hypercapnia),24 and loss of cerebral autoregulation.23 The pathophysiologic consequences of cerebral hyperemia during this phase are numerous including exaggerated release of excitatory neurotransmitters,25 blood brain barrier breakdown,26 and increased generation of reactive oxygen species with ensuing mitochondrial injury.7,21 Thereafter, a protracted phase of cerebral hypoperfusion ensues, termed the “no-reflow” period.27 Recent work in humans suggests that reduced CBF and CDO2 during this period may account for ongoing brain tissue hypoxia (brain tissue oxygen tension [PbtO2] < 20mmHg) and neuroglial injury.28 Using direct intra-parenchymal neuromonitoring, Sekhon et al., demonstrated a considerable burden of brain tissue hypoxia in HIBI patients, wherein brain tissue hypoxia was observed ~ 40% of the monitoring time.29,30 This burden of brain tissue hypoxia occurred despite the implementation of goal-directed care.29,30 At an individual patient level, a portion of HIBI patients exhibited brain tissue hypoxia despite restoring hemodynamics (e.g. mean arterial pressure [MAP] > 65mmHg) and arterial blood gases to normative levels (arterial carbon dioxide tension [PaCO2] 35–45mmHg and arterial oxygen tension [PaO2] 80–100mmHg) during the no-reflow period.28–31 The observation that HIBI patients may suffer a prolonged period of brain tissue hypoxia following return of spontaneous circulation, and this brain tissue hypoxia is associated with additive brain injury,28 suggests that the no-reflow period contributes to ongoing injury to the brain. Multiple disease mechanisms have been suggested to account for the observed reduction in CBF during the no-reflow period. Among these, clinically relevant variables include arterial hypocapnia,32 normobaric hyperoxia (NH),33 and reduced cerebral perfusion pressure (CPP).29 Given that this no-reflow phase is temporally associated with admission of HIBI patients to 5 intensive care units (ICU), it represents a logistically feasible point to implement clinical interventions and therapeutics to restore CDO2 to an optimal level. In this vein, manipulating clinical variables (e.g., MAP) in an attempt to optimize CDO2 as early as possible during intensive care has received substantial focus in clinical trials. However, these clinical trials have not demonstrated definitive efficacy,13–15 while additional trials are ongoing to further clarify this question (NCT 05564754). Cerebral hemodynamics appears to eventually progress from the no-reflow phase to then return to normal or near normal levels around 72 hours post-arrest.34,35 During this phase, return of hemostatic mechanisms occur with activation of adaptive immune responses, selective reformation of synaptic clefts, and regeneration of axons.36 Intuitively, such processes would require resumption of ‘normal’ cerebral hemodynamics with requisite oxygen and substrate supply to sustain neuronal repair mechanisms, however, considerable opportunity exists to further clarify this physiology in survivors longitudinally. 6 Figure 1-1: Cerebral hemodynamics and cardiac arrest. Panel A Showing relative baseline of CBF and MAP pre-arrest, at cardiac arrest and ROSC, until 72 hours. Panel B Graphs looking at CBF in healthy (red line) and HIBI (blue line) as it relates to blood pressure, and PaCO2. The red shaded area in panel B represents an “intact zone of autoregulation”, whereas the blue shaded region shows the narrow and right shifted zone of autoregulation The horizontal dotted line in A represents baseline of CBF and MAP. The first vertical dotted line in A represents arrest, the second vertical dotted line represents initiation of CPR, and the third vertical dotted line represents ROSC. The grey shaded area in A represents the intra-cardiac arrest to ROSC period. The red shaded areas represent the range of current clinical targets of MAP. Abbreviations: Cerebral blood flow (CBF); mean arterial pressure (MAP); return of spontaneous circulation (ROSC); cardiopulmonary resuscitation (CPR); partial pressure of arterial carbon dioxide (PaCO2); hypoxic ischemic brain injury (HIBI). 1.3 Clinical CDO2 Variables and HIBI Regulation of CBF is governed by numerous mechanisms including arterial blood gas tension, systemic hemodynamics, cerebral metabolism, arterial oxygen content (CaO2), the autonomic nervous system, and myogenic control of the cerebral vasculature (i.e., cerebral autoregulation).37 Within this paradigm, clinically relevant physiologic variables include: a) PaCO2; b) PaO2; c) MAP; d) hemoglobin (Hgb) concentration; and e) targeted temperature 7 management (TTM). Herein, each of these variables will be discussed within the context of HIBI pathophysiology and management in the post-resuscitation setting. 1.3.1 Arterial Carbon Dioxide Tension (PaCO2) Maintaining the PaCO2 of mechanically ventilated patients within physiological normal ranges (35–45mmHg) is the current standard of care for HIBI management.24 Regulation of CBF by PaCO2 has garnered significant interest in recent years as a potential therapeutic modulator for optimizing CBF. In health, PaCO2 is linearly and proportionally related to changes in CBF.37 For every 1mmHg increase in PaCO2, there is an accompanying vasodilatory response and 6-8% increase in CBF.37,38 In particular, the vasoactive effect of PaCO2 mediated CBF regulation predominantly occurs in the grey matter of the cerebrum.37,39 Anatomically, this represents key structures pertaining to the cerebral cortex, thalami and basal ganglia which are all responsible for essential neurologic functions. In HIBI, CO2 vascular reactivity remains ostensibly intact, albeit the relationship between the magnitude change in CBF per mmHg of PaCO2 fluctuation is less than that which would be expected in a healthy setting (Figure 1.1B).38,40,41 Importantly, structures within the grey matter are especially vulnerable to HIBI.42 In a physiologic study of 10 HIBI patients, increased middle cerebral artery blood flow velocity and jugular venous bulb oxygen saturation (SjvO2) were noted during a hypercapnic stimulus (PaCO2 > 45mmHg).40 Conversely, during hypocapnia (PaCO2 < 35mmHg), middle cerebral artery blood flow velocity remained unchanged and a decrease in the SjvO2 was noted.40 This, coupled with an increase in the cerebral veno-arterial lactate difference suggested an anerobic state of the brain parenchyma reflective of additional cerebral ischemia.40 In another physiologic study of 10 HIBI patients managed with mild hypothermia, manipulation of PaCO2 to hypo or 8 hypercapnic levels was associated with concomitant alterations in the middle cerebral artery blood flow velocity and SjvO2.41 Clinical trials have recently investigated the therapeutic efficacy of mild hypercapnia in HIBI. The COMACARE 43 trial randomized post-cardiac arrest patients to low-normal PaCO2 (34–35mmHg) versus high-normal PaCO2 (44–45mmHg) for 36 hours in the ICU. No difference in the serum concentration of neuron specific enolase (NSE) (primary outcome), 30-day mortality, or neurological outcome at 6 months was observed between the two groups.43 The Carbon Control and Cardiac arrest (CCC) 44 trial randomized patients to normocapnia and to mild hypercapnia (50–55mmHg) and found the mild hypercapnia group to have modestly lower NSE concentration but no improvement in neurologic outcome at 6 months was observed. The TAME trial (NCT03114033) has completed enrollment and randomized post-cardiac arrest patients to normocapnia versus mild hypercapnia (PaCO2 50–55mmHg). This trial’s results are expected in the near future and will inform the efficacy of mild hypercapnia in HIBI. In the absence of data demonstrating clear therapeutic benefit of PaCO2 manipulation, adherence to current guidelines recommending normocapnic ventilatory goals should be followed. 1.3.2 Arterial Oxygen Tension (PaO2) Current post-cardiac arrest management guidelines recommended maintaining peripheral pulse oximetry saturation (SpO2) ≥ 94%24 and both hypoxemia (PaO2 < 60mmHg), as well as hyperoxemia (PaO2 > 300mmHg) should be avoided. The use of normobaric hyperoxemia to increase CaO2 to improve oxygenation is controversial in the setting of HIBI. Administration or inadvertent exposure to hyperoxemia in the post-resuscitation setting may lead to oxygen toxicity with production of increased reactive oxygen species that are central to HIBI pathophysiology.45 9 In a multicentered prospective cohort study, exposure to hyperoxemia (PaO2 ≥ 300mmHg) was associated with worse neurological outcome in HIBI patients.46 Interestingly, the COMACARE 43 trial randomized HIBI patients to normoxemia (70–113mmHg) and to moderate hyperoxemia (150–188mmHg) and found no significant differences in NSE or other secondary outcomes. In a recent randomized control trial that compared restrictive (PaO2 68–75mmHg) to liberal supplemental oxygen (PaO2 of 98–105mmHg) in post-cardiac arrest patients, no differences were noted in outcomes (death or survival with poor neurological outcome).47 Additionally, no difference in the serum concentration of NSE was noted at 48 hours after return of spontaneous circulation.47 Therefore, the magnitude of hyperoxemia exposure may be relevant to the adverse effects of oxygen toxicity (e.g. PaO2 > 300mmHg) but the benefit of mild to moderate hyperoxemia does not seem to be an efficacious therapeutic approach in HIBI. Given the current state of literature, adherence to normoxemia should be utilized in the post-resuscitation setting. 1.3.3 Mean Arterial Pressure (MAP) Current guidelines recommend maintaining MAP ≥ 65mmHg in patients with HIBI.24 Physiologically, MAP is a key determinant of CDO2 as it is directly proportional to CPP and CBF. The relationship between MAP and CBF is also modulated by autoregulation, which is the inherent capability of the cerebral vasculature to undergo cyclical vasodilation and vasoconstriction over a range of MAP to maintain stable CBF. In health, traditional literature has advocated the Lassen curve, which suggests that the intact zone of autoregulation is 50–150mmHg, however, contemporary healthy human research demonstrates that the ‘intact’ zone is narrowed, slightly right shifted, and highly individualized.37,48,49 In the setting of HIBI, cerebral autoregulation is often impaired and the intact zone is even further right shifted and narrowed, meaning that CBF 10 may be approximated as somewhat proportionally to MAP.24,50 Impaired autoregulation, as determined by measures of the pressure reactivity index (PRx) has been associated with worse outcome in HIBI patients.51 In recent years, considerable research has been targeted towards the concept of identifying the ‘optimal MAP’ for HIBI patients derived by indices of autoregulation monitoring. Rikhraj et al.,52 conducted a systematic review aimed at identifying the autoregulation derived optimal MAP in HIBI patients. The authors found marked differences between study values and the methodologies employed to determine optimal MAP.52 Across all studies, the reported range of optimal MAP was between 70–114mmHg.52 Sekhon et al., has used invasive neuromonitoring to determine the optimal MAP in HIBI. In a prospective study, the authors found highly individualized degrees of dysfunctional autoregulation after return of spontaneous circulation which were dynamic over time.29 By using PRx (a moving Pearson’s correlation coefficient between MAP and intracranial pressure [ICP]), the authors found that the optimal MAP was ~ 89mmHg, with lower and upper limits of autoregulation being approximated at 85mmHg and 96mmHg, respectively.29 Further, by simultaneously comparing PRx to a non-invasive surrogate (cerebral oximetry index [COx] derived from near infrared spectroscopy [NIRS]), the authors found that the agreement for identifying the ‘optimal MAP’ with invasive neuromonitoring (PRx) to non-invasive neuromonitoring (COx) was poor.53 Although an attractive concept, the notion of targeting the ‘optimal MAP’ in HIBI remains challenging as it pertains to the real time identification, methodologies used, and incorporation of non-invasive surrogates which would increase the generalizability of its implementation. A systematic review of observational studies reported an association between a higher MAP in the post-resuscitation setting and improved outcomes.54 Clinical trials have emerged in 11 recent years which have further shed light on the proposed efficacy of MAP augmentation in HIBI. In the NEURPROTECT 14 trial, 112 HIBI patients were randomized to MAP 85–100mmHg versus MAP > 65mmHg. The primary outcome selected was ischemic burden measured with magnetic resonance imaging, which was not different between study groups.14 Further, there were no appreciable differences in the clinical outcomes. The COMACARE 13 trial randomized 120 HIBI patients to a similar design (high MAP 80–100mmHg versus low-normal 65–75mmHg) and did not demonstrate differences in the serum concentration of NSE or clinical outcomes between both study groups. In both trials, the regional saturation of oxygen (rSO2) generated by NIRS was also not different between study groups, suggesting that either MAP augmentation does not alter brain oxygenation or that NIRS is not an accurate measure of brain oxygenation.13,14 The latter is supported by neuromonitoring data comparing invasive measures of PbtO2 to NIRS where these measurements show poor agreement.29,53 Finally, the recent BOX 15 trial randomized HIBI patients to MAP 77mmHg versus 63mmHg and did not demonstrate differences in the clinical outcomes. Cumulatively, trial evidence suggests adherence to guidelines recommending MAP > 65mmHg in HIBI. Future research is required to determine whether patient-specific physiology could be integral to selective implementation of high MAP strategies. Although MAP augmentation has been focused on the potential for improving CBF, the determinants of blood pressure require attention as well. Blood pressure is determined by total systemic vascular resistance and cardiac output, with the latter being directly related to stroke volume and heart rate. The usage of vasopressors to maintain MAP is common in the post-cardiac arrest population, however increasing the peripheral vascular resistance may not improve cerebral blood flow if cardiac output is low. This occurrence would result from acutely increasing left ventricular afterload in the setting of concomitant dysfunction and would reduce stroke volume. 12 Left ventricular dysfunction occurs frequently after cardiac arrest,55 with more severe dysfunction in patients who do not survive hospitalization.56 Alternatively, there may be benefits to increased MAP post-resuscitation for left ventricular function by augmenting coronary perfusion. In a pooled analysis of the NEUROPROTECT and COMACARE patients who had cardiogenic shock, the authors found that the higher MAP group had lower area under the curve for increased high-sensitive cardiac troponin levels T (p = 0.04) when compared to the lower MAP group, indicating less myocardial injury.57 This is indicative that vasopressor support may be associated with reduced myocardial injury by augmenting coronary perfusion in the post-return of spontaneous circulation phase.57 Considerable further research is required into delineating the hemodynamic benefits of augmented MAP in patients with and without left ventricular dysfunction and cardiogenic shock after resuscitation. 1.3.4 Hemoglobin (Hgb) Concentration In a general critically ill population, the accepted transfusion threshold is a Hgb concentration < 70g/L, although there is equipoise about a more liberal threshold in specific patient populations.58 In HIBI, the literature assessing the optimal transfusion threshold is limited to observational data. A prospective observational study found that an admission Hgb concentration of < 12g/dL (Mean 12.3g/dL) was associated with worse neurological outcome and a Hgb < 10g/dL was associated with lower rSO2 derived from NIRS.59 Similarly, a retrospective study found an association between admission Hgb concentration ≥ 10g/dL and favourable neurological outcome.60 Johnson et al., demonstrated an association between Hgb concentration and neurological outcome within the first 6 hours after circulatory arrest (OR 1.23; 95% CI 1.09–1.38) and survival to hospital discharge (OR 1.20; 95% CI 1.08–1.34).11 Wormsbecker et al., 61 found 13 that 48-hour and 7-day Hgb concentrations were higher in patients experiencing a favourable versus unfavourable outcome. It is imperative to note that the associations between adverse neurological outcome and admission anemia may be attributable to overall chronic severity of illness instead of the impact of anemia on inciting post-return of spontaneous circulation reductions of CDO2. Given the paucity of interventional studies examining optimal transfusion thresholds, current guideline recommendations for maintaining a Hgb concentration of > 7g/dL in non-bleeding critically ill patients should be followed in HIBI. 1.3.5 Targeted Temperature Management (TTM) Guidelines recommend maintaining normothermia in adults who remain unresponsive despite return of spontaneous circulation following cardiac arrest. The use of TTM has been shown to have neuroprotective benefits in animal models, including the suppression of excitotoxicity, a reduction in oxidative stress, and a reduction in secondary inflammation post-insult.62 Additionally, hypothermia has been shown to reduce the secondary energy failure (i.e. elevated lactate/pyruvate ratio) in post-cardiac arrest pigs.63 Treatment of post-cardiac arrest patients with HIBI came into clinical practice after two clinical trials were published in 2002. The Hypothermia After Cardiac Arrest (HACA) 64 group randomized out-of-hospital cardiac arrest patients to therapeutic hypothermia (32–34° C) for 24 hours to normothermia. The primary outcome was favourable neurological outcome (i.e., cerebral performance category [CPC] 1–2) and secondary end points included mortality at 6 months and complications of therapeutic hypothermia during the first 7 days after cardiac arrest.64 The authors found that 55% (75 of 136) of individuals in the hypothermic group had favourable outcomes compared to 39% (75 of 136) in the normothermic group, and that mortality at 6 months was 41% (56 of 136) and 55% (76 of 14 137) in the hypothermic and normothermic groups, respectively.64 Similarly, Bernard et al., 65 performed targeted hypothermia of 33° C for 12 hours and compared that to normothermia treated patients with the primary outcome being survival to hospital discharge. The authors found that 49% (21 of 43) patients treated with hypothermia survived and had favourable outcome compared to 26% of patients undergoing normothermia (9 of 34).65 Given the relatively small numbers for the aforementioned trials, the TTM group compared 33° C to 36° C in out-of-hospital cardiac arrest patients.66 The authors demonstrated that 50% (235 of 473) of patients in the 33° C group had died compared to 48% (225 of 466) of patients in the 36° C group.66 The HYPERION 67 trial investigated the use of TTM (33° C for the first 24 hours) in non-shockable rhythm post-cardiac arrest patients compared to normothermia. The primary outcome was survival with favourable neurological outcome assessed at 90 days.67 The authors found that patients treated with hypothermia demonstrated higher rates of favourable outcomes (CPC 1–2; 10.2%; 29 of 284) when compared to the normothermia group (5.7%; 17 of 297).67 In 2021, the TTM2 68 trial group compared targeted hypothermia (33° C) to normothermia (< 37.5° C). The primary outcome was mortality at 6 months. At the 6-month mark, 50% (465 of 925) of patients in the hypothermic group and 48% (446 of 925) of patients in the normothermic group had died.68 Additionally, the authors found patients treated with targeted hypothermia had increased rates of cardiac arrhythmias compared to the normothermic group (24% versus 17%).68 These findings contradict the previous paradigm that TTM is widely beneficial to HIBI patients after cardiac arrest. Future research is required to identify potential sub-groups in whom hypothermia may be beneficial. 15 1.4 Patient-Specific Phenotypes of HIBI As mentioned, clinical trials aimed at optimizing CDO2 have not demonstrated improvements in clinical outcomes. Nonetheless, physiologic evidence from invasive neuromonitoring studies demonstrate that increasing MAP is associated with improved PbtO2 in a subset of HIBI patients.29 The discrepancy between the perceived importance of optimizing post-return of spontaneous circulation CDO2 and lack of clinical efficacy with such approaches suggests that there are knowledge gaps in our understanding of HIBI. In health, coupling between CDO2 and brain oxygenation is a central physiologic function.37 In the setting of acute brain injury, the uncoupling of this relationship was first described by Menon et al., in patients who sustained a traumatic brain injury, a concept termed ‘diffusion limitation’.69 In this instance, as CDO2 fluctuates, brain oxygenation remains relatively unaltered due to impairments in the anatomic or functional diffusion barrier. In HIBI, Sekhon et al., 31 demonstrated preliminary evidence of diffusion limitation using invasive neuromonitoring in a post-hoc study, where the authors stratified HIBI patients based upon the degree of PbtO2 (normoxia – PbtO2 ≥ 20mmHg and hypoxia – PbtO2 < 20mmHg). The oxygen diffusion gradient can be approximated by the difference in the jugular venous bulb oxygen tension (PvO2) minus the PbtO2. In the setting of preserved diffusion of oxygen from the cerebrovascular bed into the parenchyma, the PvO2–PbtO2 gradient will be inversely related to fluctuations in CDO2. As diffusion takes place, oxygen leaves the blood (reflected in a lower PvO2) and enters the brain (reflected in an elevated PbtO2), thereby decreasing the PvO2–PbtO2 gradient. The authors determined that in HIBI patients with brain tissue hypoxia, the PvO2–PbtO2 gradients were greater than those with brain tissue normoxia.31 The pathophysiology for this observed increase in PvO2–PbtO2 gradient may be a result of cerebral edema, mitochondrial dysfunction, or blood brain barrier 16 breakdown.28,70 Further, in HIBI patients with brain tissue normoxia, increasing CPP was associated with improvements in brain oxygenation and a decreased PvO2–PbtO2 gradient.31 This association between increased CPP and reduced PvO2–PbtO2 gradient was not observed in patients with brain tissue hypoxia, thereby confirming the presence of diffusion limitation (Figure 1-2).25 Figure 1-2: Differential phenotypes of hypoxic ischemic brain injury. Panels A and B represent a HIBI panel exhibiting preserved coupling between augmentation of CDO2 and concomitant brain oxygenation. This physiology indicates intact diffusion of oxygen from the cerebral microvasculature into the brain parenchyma. In panel B, fluctuation of cerebral perfusion is show in red with concomitant increases in PbtO2 (white) and SjvO2 (blue). The X-axis represents time intervals in 5-minute bins. In panel A, the conceptual physiology underpinning intact diffusion of oxygen (blue dots) is shown diffusing out of the cerebral capillary and into the brain parenchyma. In panel D, fluctuations of CPP shown without corresponding changes to PbtO2 (white) or SjvO2 (blue). Panel C demonstrates the conceptual depiction of limited oxygen diffusion from the cerebral capillary into the brain parenchyma and resultant brain tissue hypoxia. Abbreviations: Hypoxic ischemic brain injury (HIBI); cerebral delivery of oxygen (CDO2); brain tissue oxygenation (PbtO2); Jugular bulb venous oximetry (SjvO2); Oxygen (O2); Hemoglobin (Hgb); Cerebral perfusion pressure (CPP). 17 This pathophysiology has important clinical implications as it pertains to the interpretation of clinical trials of CDO2 optimization.71 For example, HIBI patients exhibiting diffusion limitation of oxygen delivery would not be expected to benefit from CDO2 optimizing interventions (MAP augmentation or mild hypercapnia) as compared to those who exhibit preserved coupling between CDO2 and brain oxygenation.71 The results of the clinical trials described in this thesis should be viewed in the context of individual patient-specific phenotypes such as diffusion limitation that may have played in a role in the neutral results. Considerable future work is required to further describe these pathophysiologic phenotypes, characterize the natural history and to identify their presence in vivo in humans with non-invasive and generalizable methods. 1.4.1 Cerebral Edema One of the attributable causes of diffusion-limitation that is suggested in HIBI is possibly due to cerebral edema.70 The accumulation of fluid in the brain parenchyma is caused by the intracellular accumulation of sodium ions leading to cytotoxic edema.72 Cerebral edema can develop within minutes after cardiac arrest and may additionally be driven by cerebrospinal fluid influx.72 A computed tomography scan of the brain in post-cardiac arrest patients can assess the severity of HIBI by detecting cerebral edema,8 or by detecting a reduction of grey to white matter ratio.24 Hoiland et al., performed osmotherapy using hypertonic saline in 9 HIBI patients with brain tissue hypoxia, and found an improved PbtO2 from 17.0mmHg [9.1–19.7] to 20.2mmHg [11.9–22.2; p = 0.04] without changing systemic hemodynamic variables (i.e., MAP, ICP), indicating an improved diffusion of oxygen across the brain parenchyma.28 18 Aquaporin 4 (AQP4) is the main water channel in neuronal tissue, it is found in perivascular astrocytic end-feet, and it is the rate limiting factor in water influx during ischemia induced cerebral edema in a mice knockout model.73 Nakayama et al., showed that 7.5% hypertonic saline to maintain serum osmolality of 350mOsm/L is beneficial for the attenuation of cerebral edema in a wild-type mouse model when compared to a AQP4 knockout model, which may be beneficial for treatment of cerebral edema.73 Additionally, the authors demonstrated the importance of perivascular AQP4 plays in water movement out of the brain, and how hypertonic saline can attenuate blood-brain barrier disruption through this mechanism.73 Similarly, using continuous intravenous infusions of conivaptan, this selective arginine receptor antagonist (specifically V1 and V2 receptors) has been shown to attenuate cerebral edema and blood brain barrier disruption following cardiac arrest.74 With the same AQP4 knockout mouse model, the effects of conivaptan are dependent on the presence of AQP4, which are mediated through its effect on V1 and V2 receptors.74 1.5 Methodology For this thesis work, the methods that are used will be listed subsequently below, starting with the use of neuromonitoring, measuring blood-based brain injury biomarkers, and cardiovascular and respiratory physiologic measures. 1.5.1 Neuromonitoring The methods used in the following studies to assess neuromonitoring and measure cerebral oxygenation and CBF are NIRS, SjvO2, transcranial Doppler ultrasonography (TCD), 19 neuro-intensive care monitoring software, and arterial to venous (a-v) differences in blood sampling. Each neuromonitoring method is described below. 1.5.1.1 Near Infrared Spectrometry (NIRS) NIRS is a non-invasive monitoring technique to estimate cerebral oxygenation, yielding a numerical value noted as the rSO2. NIRS uses the transmission and absorption of light in the near-infrared wavelength spectrum (700–950nm) that goes through tissue and relies on the absorbing pattern of oxyhemoglobin and deoxyhemoglobin in the blood.75 This technique measures a weighted average of arterial, capillary, and venous blood in proportion to their intracranial volumes within its plane of view and assumes a fixed ratio of either 70%:30% or 75%:25% for venous to arterial flow, neglecting capillaries.75 Physiologic factors that influence rSO2 include arterial oxygenation, PaCO2, blood pressure, hematocrit, CBF and volume, and the cerebral metabolic rate of oxygen.76 The validity of NIRS is based on different algorithms available, meaning that different manufactures may have differences in rSO2 values.75 Additional limitations include extracranial tissue contamination and normal ranges vary between 60% – 75% that can differ from individual to individual, meaning it may serve better as a trending tool rather than guiding therapy.75,77 An in-hospital cardiac arrest study showed that between the first and second hours, patients with favourable outcomes (CPC 1–2) had significantly higher rSO2 values compared to patients with unfavourable outcomes (CPC 3–5) (75% versus 69%; p = 0.03), however, at other time intervals, showed no difference.77 Although NIRS has limitations such as extracranial blood flow contamination, adherence of the pads to the skin, ambient light interference,78 and skin pigmentation effecting the NIRS value,79 it remains a suitable and non-invasive way to trend cerebral oxygenation. 20 1.5.1.2 Jugular Venous Bulb Oximetry (SjvO2) SjvO2 monitoring measures oxygen saturation of Hgb in the cerebral venous circulation. This monitoring technique is performed by placing a catheter retrograde in the jugular vein and positioning the tip at the jugular bulb which is anatomically located just distal to the sigmoid sinus (Figure 1-3).80 Measurements of cerebral oxygenation from blood sampled from the jugular bulb have been used to reflect the balance between CDO2 and utilization.80,81 The normal range of SjvO2 have been described as between 55% and 75%,81 and abnormalities outside this range can be the result from various systems, including cardiopulmonary sources, at the brain, and cellular function.82 Causes of elevated SjvO2 (> 75%) include hypercapnia, decreased metabolic demand (i.e., sedation or hypothermia), mitochondrial dysfunction and neuronal injury.82 A reduced SjvO2 (< 55%) can be a result from decreased CDO2 stemming from anemia, hypocapnia, reduced CBF, increased cerebral oxygen utilization from fever and seizures, and dysfunctional neurovascular coupling.82 In post-cardiac arrest patients with jugular bulb catheters in situ, SjvO2 has been shown to be increased in non-survivor/unfavourable groups when compared to survivor/favourable groups,80,83 and is thought to reflect loss of viable brain tissue with decreased cellular metabolism.83 Hypothermia has been shown to increase SjvO2 compared to normothermia in resuscitated post-cardiac arrest pigs, indicating the low oxygen extraction (O2EF) can be associated with decreased cerebral metabolism and potentially offering neuroprotection.63 Wallin et al., used jugular bulb monitoring in post-cardiac arrest patients treated with TTM (33˚ C) and showed that oxygen delivery and extraction differed from patients with favourable neurological outcome (CPC 1–2) compared to those with unfavourable outcome (CPC 3–5) at single timepoints.81 21 Figure 1-3: A picture of a jugular venous bulb catheter in a healthy participant. 1.5.1.3 Transcranial Doppler Ultrasonography (TCD) TCD is a non-invasive, real-time measurement of cerebrovascular blood flow characteristics and hemodynamics within the cerebral arteries and can be performed at the bedside.84 TCD is based on using the Doppler effect principle, using ultrasound waves emitted from a probe that is transmitted through the skull and reflected by moving red blood cells within the insonated cerebral vessel.84 The velocity is calculated using the difference between emitted and reflected waves, which is referred to as the Doppler shift frequency and is directly proportional to the speed of moving red blood cells.84 The main arteries of interest include the middle cerebral artery, internal carotid artery, posterior cerebral artery, and anterior cerebral artery, and can be insonated through four acoustic windows, the transtemporal window, the transorbital window, submandibular window, and the suboccipital window.84,85 The insonation of cerebral arteries can occur in thinner regions of the skull using a 2 MHz frequency ultrasound probe (Figure 1-4).85 The physiologic variables that impact blood flow velocity include age, gender, hematocrit, viscosity of the blood, PaCO2, and 22 blood pressure.84 Clinical applications of TCD include assessing subarachnoid hemorrhage and cerebral vasospasm, intracranial steno-occlusive disease, ischemic stroke, sickle cell disease, micro-emboli detection, and cerebral circulatory arrest.84 The middle cerebral artery can be viewed at a depth range of 25–50mm85 [35–55mm84], and has a mean velocity of 62cm/sec ± 12cm/sec, based on data published by Aaslid et al.,.86 Limitations of TCD include the examiners technical skill and knowledge of anatomy (cerebral vessel anatomy, common insonation depths, and blood flow velocities of various arteries) to provide accurate, reliable, and reproducible measurements.85 Additionally, TCD does not measure absolute flow through a vessel, but rather cerebral blood velocity due to the diameter of the insonated vessel being unknown, therefore it is recommended to insonate the middle cerebral artery at a near-zero angle to provide better measurements.85 Figure 1-4: An Example of TCD being used on a healthy participant. The middle cerebral artery is being insonated by the two Doppler ultrasound probes, which are fastened to a headband to ensure stability. 23 1.5.1.4 ICM+ Software Program Our lab utilizes the software program, multimodal neuro-Intensive Care Monitoring (ICM+) and waveform analysis to encapsulate the many sources of raw data into one format that is required for study purposes. This software program was developed in the mid 1980’s and can be used to in a variety of neurological pathologies which include hydrocephalus, stroke, traumatic brain injury, and HIBI.87 The program can interface with the vast range of bedside monitors using a digital to analogue converter and RS232 serial interface that can collect raw data and calculate time trends of summary parameters.87 It can be used to identify variables such as CPP (using the difference of MAP and ICP), and describe other variables such as cerebrospinal compensatory reserve, pressure autoregulation, and vascular reactivity.87 The data that is processed from the ICM+ can be displayed as time trends, histograms, cross histograms, and correlations.87 The software program allows the researchers the ability to input observations directly into the program that can mark important times or events.87 Artifacts in the raw data can arise from temporary disconnects and disturbances of individual input signals (i.e., arterial line flushing).87 Importantly, ICM+ files are strongly encrypted, allowing for safe storage of data, protects the privacy and confidentiality of patients, and allows for safe collaboration with researchers.87 For the studies included in this thesis, ICM+ was used to record TCD data, rSO2, MAP, SjvO2, and temperature. 1.5.1.5 Utilizing an Arterial to Venous Difference in Measurements To minimize the potential for extracerebral sources of blood-based biomarkers, our lab utilizes a simultaneous blood draw of arterial and jugular venous bulb samples (Figure 1-5). By 24 taking the difference between arterial and venous (a-v) samples, we can isolate the cerebrovascular system and evaluate what is occurring at the time of sampling. A positive a-v difference would then indicate cerebral uptake (more blood-based biomarkers in arterial circulation), whereas a negative value would indicate cerebral release (higher venous concentration of blood-based biomarkers).28 Figure 1-5: Blood-based biomarkers of brain injury. The left image shows the sampling of arterial and venous blood. The right image indicated where each biomarker is coming from. Abbreviations: GFAP, glial fibrillary acidic protein; Nf-L, neurofilament light, UCHL-1, ubiquitin carboxyl terminal hydrolase; NSE, neuron specific enolase; IL-6, interleukin 6. Image adapted from Hoiland RL, Ainslie PN, Wellington CL, et al. Brain Hypoxia Is Associated with Neuroglial Injury in Humans Post-Cardiac Arrest. Circulation Research. Published online 2021:583-597. doi:10.1161/CIRCRESAHA.121.319157 Ó 2021, Wolters Kluwer Health, Permission not required. 25 1.5.2 Blood-Based Biomarkers of Brain Injury In this thesis, the novel blood-based brain injury biomarkers of interest are glial fibrillary acidic protein (GFAP), neurofilament light chain (Nf-L), Tau, and ubiquitin carboxy terminal hydrolase L1 (UCH-L1). These blood-based biomarkers are used as markers of brain injury based on the administration of NH and mild hypercapnia. The following section will discuss how biomarkers are used in the setting of HIBI, how they are measured, inflammatory cytokines, and the advantages and disadvantages of using blood-based biomarkers. 1.5.2.1 Current Use of Blood-Based Brain Injury Biomarkers Current cardiac arrest guidelines recommend the use of serial measurements of NSE as the only blood-based brain injury biomarker to predict outcome, with increasing values between 24–72 hours indicating a poor prognosis.24 It is not recommended as the sole predictor, but mainly to be used in addition to the multimodal process of determining prognostication. The ability to neuro-prognosticate in post-cardiac arrest HIBI patients is crucial in critical care medicine. Currently, the process for prognostication is multimodal, beginning with assessing if the patient remains unconscious after 72 hours from return of spontaneous circulation without sedation and absent motor reflexes, no pupillary or corneal reflexes, burst-supressed electroencephalogram, status myoclonus, diffuse anoxic injury on a computerized tomography or magnetic resonance imaging, and high NSE after 72 hours.88 Recently, novel blood-based biomarkers of brain injury have been suggested to be more effective than NSE at predicting poor outcome. These biomarkers include GFAP, Nf-L, Tau, and UCH-L1. 26 1.5.2.2 Location of Blood-Based Brain Injury Biomarkers Neuron specific enolase is found mainly in neuronal and neuroendocrine cells in the neuron cell body, however, can also be found in red blood cells and platelets, and additionally serve as a biomarker for small cell lung cancer.89 GFAP is a structural astrocytic protein that is specific to the brain and it has been used in traumatic brain injury and stroke patients as a possible marker for good outcome prediction.89 Tau and Nf-L are axonal proteins of neurons.90,91 In a systemic review done in 2022, Nf-L had a higher accuracy of predicting favourable versus unfavourable neurological outcome in post-cardiac arrest HIBI patients when compared to NSE, GFAP, and UCH-L1.92 In the same review, Tau was deemed to have the next highest predicting capabilities when compared to the same blood-based brain injury biomarkers.92 UCH-L1 is found in the neuronal cell body and released during injury (Figure 1-5).92 1.5.2.3 Inflammatory Cytokines Additional inflammatory markers were measured in this thesis, and these include interleukin 6 (IL-6), interleukin 10 (IL-10), interleukin 1 beta (IL-1β), and tumor necrosis factor alpha (TNF-α). The measurement of these inflammatory cytokines is due to the occurrence of a systemic inflammatory response in post-cardiac arrest patients from the ischemic/reperfusion injury.24 During reperfusion injury after successful resuscitation, endothelial and leukocytes sense tissue damage and release pro-inflammatory cytokines IL-1β and TNF-α.93 IL-6 is a secondary inflammatory cytokine released by leukocytes 93 and is a mediator on the acute inflammatory response with development of fever via effects on temperature regulation.94 IL-10 is also a secondary cytokine that is released due to IL-1β and TNF-α and is known for its anti-inflammatory effects.93 27 1.5.2.4 Measuring Blood-Based Brain Injury Biomarkers The detection and measurement of blood-based brain injury biomarkers is performed using single-molecule array technology (Simoa). The Simoa analyzer is a completely automated system that is designed to minimize operator intervention.95 It relies on single-molecule arrays along with the simultaneous counting of singulated capture microbeads.95 The arrays in the Simoa contain 216,000 femtoliter sized microwells that can obtain thousands of data points simultaneously, allowing for rapid data acquisition.95 Each microwell contains a singulation of microbeads, and when a single enzyme catalyzes the substrate conversion to a fluorescent product, this reaction is confined to the well allowing for a measurable fluorescent signal.95 The Simoa contains a digital camera that can count thousands of these single-molecule signals in the array simultaneously.95 The Simoa analyzer utilizes the low cost of enzyme-linked immunosorbent assay (ELISA) reagents along with optics, consumables, and advanced robotics to maximize efficiency, sensitivity, and data quality.95 The automation of the Simoa analyzer is a large benefit compared to the ELISA, as the ELISA requires a 450nm wavelength reader to interpret the results.96 To emphasize the value of Simoa in terms of sensitivity, a study which compared ELISA, electrochemiluminescence immunoassays, and Simoa for the quantification of Nf-L in blood samples showed that the Simoa platform was 126-fold and 25-fold more sensitive than ELISA and electrochemiluminescence immunoassays, respectively.97 1.5.2.5 Advantages and Limitations of Blood-Based Brain Injury Biomarkers Each biomarker has different kinetics and half-lives and are produced and secreted continuously with brain damage, meaning sampling should occur at optimal time points; 28 however serial sampling can obtain a release curve and yield optimal results.89 Advantages to using blood-based brain injury biomarkers are the ease of sampling and interpretation, results are quantitative, and the use of sedation does not have an effect.24,89 The limitations of using biomarkers include a lack of standardization of methods and cut-off values, laboratory limitations, the need for serial measurements, and the possibility of non-cerebral sources of the biomarkers influencing results.24,89 1.5.2.6 Sensitivity and Specificity It is important to mention the accuracy of diagnostics based on the specificity and sensitivity of prognostication. The accuracy of a test is defined by the test’s ability to differentiate the cases that are positive for a disease and the cases that are negative for a disease.98 The sensitivity for a test is the ability of the test to determine the disease cases correctly, and the specificity of a test is the ability of the test to determine absence of disease correctly.98 True positives are defined as the number of cases that have correctly identified the disease, whereas true negatives are the number of cases that have correctly identified the absence of the disease.98 There are situations where incorrect identification of the presence or absence of disease can arise, with a false positive being an incorrect detection of a disease, and a false negative, where the test incorrectly predicts the absence of a disease.98 In clinical medicine, 100% specificity (false positive rate of 0) does not exist.89 29 1.5.3 Cardiovascular and Respiratory Physiology Measures The methods to assess cardiovascular and respiratory physiologic measures include arterial blood gases, end-tidal CO2, dynamic end-tidal forcing breathing system, and cerebrovascular reactivity to CO2 assessed with TCD and PaCO2. These methods are further described below. 1.5.3.1 Arterial Blood Gases Arterial blood gases are collected by performing an arterial blood draw from either an arterial puncture of the radial or brachial artery, or by drawing a sample from an existing indwelling arterial catheter (Figure 1-6). The sample is then analyzed using a blood gas analyzer that can give clinical data from the patient such as pH, PaCO2, PaO2, bicarbonate, SaO2, Hgb, as well as electrolytes and metabolites to assess a patient’s physiological status.99 The importance of being able to obtain an arterial blood gas sample and analyze it gives valuable information of the patient’s pulmonary gas exchange, acid-base balance, and blood oxygenation.99 30 Figure 1-6: Example of a radial arterial line 1.5.3.2 End-tidal CO2 End-tidal CO2 is the exhaled partial pressure of CO2 at the end of expiration. CO2 is produced by cells via aerobic metabolism and diffuses into the blood, where it is then transported to the pulmonary circulation and diffuses across the alveoli and removed via respiration.100 The major determinants of end-tidal CO2 include CO2 production from the cells in the body, cardiac output, perfusion of the lungs, and alveolar ventilation.100 In healthy individuals, end-tidal CO2 closely approximates PaCO2 at the end of exhalation, in which end-tidal CO2 is between 2–5mmHg lower than PaCO2, which is due to a combination of dead space CO2 and alveolar CO2 31 mixing during exhalation.101,102 There are four phases in the end-tidal CO2 capnography waveform, where phase 1 is the anatomical dead space and should not contain CO2, phase 2 is a rise in CO2 as exhalation is started and alveolar gas begins to mix with the dead space gas, phase 3 is where the only gas that is being exhaled is from the alveoli and causes a plateau and the maximum value is determined as the end-tidal CO2, and phase four is where inspiration begins (Figure 1-7).100–102 The difference between end-tidal CO2 and PaCO2 can be a function of assessing an individual’s ventilation-perfusion relationship.101 Therefore, in health, end-tidal CO2 can be used as a surrogate for arterial CO2 as it is only approximately 2–5mmHg lower. In this thesis, end-tidal CO2 was used to monitor the HIBI patients while on a mechanical ventilator in Studies 1 and 2 (Chapters 2 and 3), along with the healthy control group during dynamic end-tidal forcing in Study 2 (Chapter 3). Arterial blood gases were performed in all study subjects, and PaCO2 was used for all calculations and data representation. 32 Figure 1-7: An example of a capnography. The graph shows the normal difference between PaCO2 and ETCO2. The Y-axis is CO2 in mmHg and the X-axis is phases of respiration (i.e., inspiration in green and exhalation in blue). Phase 1 indicates the anatomical dead space and CO2 should be negligible. Phase 2 is the anatomical dead space and alveolar gas beginning to mix showing a rise in CO2. Phase 3 is the alveolar plateau where only alveolar gas is being exhaled and the maximum point being ETCO2. Phase 4 is the start of inspiration leading to a decline in measured CO2. Abbreviations: PaCO2, arterial carbon dioxide tension; ETCO2, end-tidal carbon dioxide. 1.5.3.3 Dynamic End-tidal Forcing Altering the arterial blood gases (i.e., PaO2 or PaCO2) of a mechanically ventilated patient is performed by adjusting the fraction of inspired O2 (FiO2) or increasing or decreasing the minute ventilation (by changing respiratory rate or tidal volume), respectively. However, manipulating and monitoring these changes in a healthy subject cannot be performed the same way as a mechanically ventilated patient. One method of altering arterial blood gases is by controlling end-tidal gases using a dynamic end-tidal forcing breathing system.103 By using dynamic end-tidal forcing, it allows for ways of investigating control breathing, along with the 33 effects of breathing has on cerebral, pulmonary, and cardiac vascular function.103 The dynamic end-tidal forcing system uses a mixture of three gases, O2, CO2, and nitrogen, controlled by solenoid valves to deliver the desired inspiratory gas volume into a reservoir bag.103 It uses predictive algorithms to control the end-tidal partial pressures of O2 and CO2 by adjusting the FiO2 and fraction of inspired CO2 on each breath.103 Additionally, the dynamic end-tidal forcing system uses a software program to determine the end-tidal partial pressures of O2 and CO2, tidal volume, respiratory rate, and minute ventilation.103 The dynamic end-tidal forcing system was used in Study 2 (Chapter 3) to induce hypercapnia in the healthy test subjects. 1.5.4 Physiologic Metrics of CO2 Reactivity Cerebrovascular reactivity to CO2 is a reflective index of the cerebral vasculature’s ability to dilate or constrict with alterations in CO2.104 The brain blood vessels have a differential effect to PaCO2, with more reactivity occurring in the grey matter than white matter, and mainly occurring in the small arterioles and capillaries than larger vessels.104 As the CO2 stimulus has a differential effect across the cerebral vasculature, the use of TCD to measure cerebrovascular reactivity to CO2 is a global measure of reactivity.85 Cerebrovascular CO2 reactivity is calculated by the change in CBF divided by the change in CO2,85 whereas the change in CBF is measured using TCD to determine flow velocity through the middle cerebral artery, and the changes in CO2 are measured from either end-tidal CO2 monitoring or from arterial CO2 measured from arterial blood gases. Cerebrovascular reactivity to CO2 is thought to be unaltered in patients suffering from post-cardiac arrest HIBI patients.40,41 These studies incorporate the use of TCD and hypercapnic stimulus to determine the cerebrovascular reactivity to CO2, however, the authors do not compare to healthy controls. In 34 this thesis, measuring cerebrovascular reactivity to CO2 is applicable as the comparison of HIBI patients to healthy controls is performed to assess if the HIBI group does in fact have an unaltered cerebrovascular reactivity to CO2. 1.6 Thesis Aims and Hypotheses Therefore, the purpose of this thesis was to investigate the utility of modifying arterial blood gases to increase CBF and CDO2 to the brain in post-cardiac arrest patients with HIBI. Study one investigates administering increased PaO2, and study two investigates increasing the PaCO2. The aims and hypotheses for study 1 and study 2 are outlined below. 1.7 Study 1: The Effect of Normobaric Hyperoxia on Cerebral Oxygen Uptake and Metabolism in Hypoxic Ischemic Brain Injury 1.7.1 Study 1 Aims The specific aims for this study are to investigate the effect of NH on: a) cerebral oxygen uptake and metabolism; b) rSO2 using NIRS; c) a-v differences of blood-based biomarkers of brain injury pertaining to cellular components of the neurovascular unit. 1.7.2 Study 1 Hypothesis We hypothesized that brief exposure to NH would be associated with: a) increased CDO2 by utilizing measurements of SjvO2 as a surrogate of CDO2; b) improved rSO2 using NIRS; c) decreased a-v differences of blood-based brain injury biomarkers. 35 1.8 Study 2: The Effect of Mild Hypercapnia on Mitigating Secondary Hypoxic Ischemic Brain Injury Following Cardiac Arrest 1.8.1 Study 2 Aims The specific aims of this study were to investigate the effect of mild hypercapnia on: a) middle cerebral artery blood flow velocity using TCD; b) cerebral O2EF; c) a-v differences of blood-based brain injury biomarkers pertaining to cellular components of the neurovascular unit. Additional aims were to compare middle cerebral artery reactivity (MCAv) and conductance (MCAv CVC) of HIBI patients to healthy controls. 1.8.2 Study 2 Hypothesis We hypothesized that mild hypercapnia would be associated with: a) increased middle cerebral artery blood flow velocity as a surrogate of CBF; b) decreased cerebral O2EF; c) decreased a-v differences of blood-based brain injury biomarkers. 36 Chapter 2: The Effect of Normobaric Hyperoxia on Cerebral Oxygen Uptake and Metabolism in Hypoxic Ischemic Brain Injury 2.1 Study 1: Introduction Following cardiac arrest, HIBI following return of spontaneous circulation is a major determinant of neurological outcome.3,7,24 Current HIBI management strategies focus on the optimization of CDO2 and utilization.24 Clinical investigations involved in the management of HIBI patients focused on augmenting CDO2 such as MAP13,14 and permissive hypercapnia,43,44 with these interventional studies yet to demonstrate improved clinical outcomes. A possible explanation for the lack of successful trials that aimed at augmenting CDO2 and improving the secondary injury could be due to the heterogenous pathophysiology of HIBI.70 Recently, our lab has demonstrated that diffusion limitation of CDO2 is associated with secondary brain hypoxia, despite improving MAP.31 Thus, augmenting CDO2 by means of increased MAP cannot appreciably decrease the secondary hypoxic insult. Therefore, alternative strategies to improve post-resuscitation management of HIBI need to be evaluated. One method that has garnered interest to potentially overcome this diffusion limitation is using NH. In traumatic brain injury patients, elevated PaO2 were associated with improved oxidative cerebral energy metabolism using microdialysis.105 Although evidence for the use of NH is controversial with the exacerbation of oxygen free radicals, associated oxygen toxicity, and worsening outcomes,46 conflicting evidence in the literature of HIBI is apparent, with retrospective studies showing early exposure to hyperoxemia was not associated to long term outcomes.106 37 Therefore, we conducted a prospective interventional study using NH administration in post-cardiac arrest patients that achieved return of spontaneous circulation with the primary aims of investigating the effect of NH on the indices of cerebral oxygenation using SjvO2 and rSO2 using NIRS as surrogates to CDO2. The secondary aims were to investigate the effect of NH on the release/uptake of blood-based biomarkers of brain injury and inflammation. We hypothesized that the use of NH will increase the indices of cerebral oxygenation as well as mitigate the release of blood-based brain injury biomarkers. 2.2 Study 1: Methods We conducted a prospective study using NH in twelve post-cardiac arrest patients with HIBI who achieved return of spontaneous circulation. The study was approved by the University of British Columbia Clinical Research Ethics Board (H16-03076). The study was conducted with standards set forth by the Helsinki declaration. The study was performed at Vancouver General Hospital ICU, a closed 34 bed mixed medical-surgical unit with affiliation to the University of British Columbia. The Registered Nurses to patient ratio are 1:1.2. 2.2.1 Study 1: Population Patients were enrolled in the study from January 2018 to January 2019. Enrolment into the study occurred following the inclusion criteria of a) age > 18 years old; b) return of spontaneous circulation > 10 minutes; c) post-resuscitation Glasgow coma score < 9 and motor score < 5. Patients were excluded from the study if a) anticipated withdrawal of life-sustaining therapies within the next 24 hours; b) known pregnancy; c) related or pre-existing history of 38 central nervous system injury (stroke, traumatic brain injury, intracranial hemorrhage, or subarachnoid hemorrhage). 2.2.2 Study 1: Cardiac Arrest Management Vancouver General Hospital ICU adheres to cardiac arrest guidelines that follow temperature management of < 37˚C for 24–48 hours using cooling blankets and allow for a gradual return to normal temperature after cooling protocol. MAP goals are greater than 65mmHg and the use of norepinephrine for blood pressure management. The primary sedative used is propofol. Normocapnic ventilation (PaCO2 35–45mmHg) and normoxia (PaO2 80–100mmHg) are targeted. All clinical decisions are made by the attending physician. 2.2.3 Study 1: Neurophysiologic Monitoring Patients had continuous SpO2, heart rate, and end-tidal CO2 monitoring. Patients were lined with a 20-gauge radial arterial catheter (Arrow) for continuous blood pressure monitoring as well as frequent arterial blood gas sampling. Patients were also equipped with a jugular venous catheter (Arrow), placed retrograde at the level of the sigmoid sinus, and placement was confirmed with a skull base X-ray. Lastly, patients were also equipped with bilateral NIRS (INVOS, Medtronic) as an index for cerebral oxygenation as derived from the rSO2 value. 2.2.4 Study 1: Data Collection Once patients were instrumented, concurrent baseline arterial and jugular venous bulb blood sampling occurred, to measure arterial and venous oxygen, as well as baseline samples for blood-based biomarkers of brain injury. Patients were then exposed to an increased FiO2 to 39 achieve a PaO2 between 200–300mmHg. Patients were then maintained for 6 hours at this higher level of FiO2, with additional blood samples taken at the 2-, 4-, and 6-hour mark, before being returned to their respective baseline FiO2. Additional simultaneous blood samples were taken 6- and 18-hours post exposure. Blood-based brain injury and inflammatory biomarker samples were taken at the 6-hour mark, and again at 6-hours post NH exposure. 2.2.5 Study 1: Blood-Based Biomarker of Brain Injury Analysis Section 1.5.2 of this thesis describes the blood-based biomarkers of brain injury of interest for this study. Briefly, the biomarkers of brain injury that were being investigated include GFAP, Nf-L, Tau, and UCH-L1. Additional inflammatory markers from the blood that were collected include IL-6, IL-10, IL-1β, and TNF-α. At each time point, blood samples were obtained using 1 SST vial (Vacutainer, USA) and 1 EDTA vial (Vacutainer, USA) from both the arterial and jugular bulb catheters simultaneously. After these samples were collected, they were stored in a dark area, upright, for 10 minutes. After storage, samples were then centrifuged at 3600rpm for 10 minutes, and the samples were then pipetted into 2ml cryovials. Once the samples were in the cryovials, samples were then stored at -80˚C until analysis, which was performed using Simoa HD (Quanterix®) at the Djavad Mowafaghian Centre for Brain Health located at the University of British Columbia. Data was then inputted into Microsoft Excel® (USA) and further statistical analysis was performed using Prism® (GraphPad v9.5.1). 40 2.2.6 Study 1: Calculations Biomarkers were compared using a-v differences, with positive values indicating cerebral uptake, and negative values indicating cerebral release. The data is presented as an arterial concentration and an a-v difference. Additional calculations were calculated using Microsoft Excel® (USA). CaO2 was calculated using the formula: CaO2 = (1.34 + Hgb + (SaO2/100)) + (PaO2 x 0.003) Where SaO2 stands for arterial oxygen saturation. Venous oxygen content (CvO2) was calculated using the formula: CvO2 = (1.34 + Hgb + (SvO2/100)) + (PvO2 x 0.003) O2EF percentage was calculated using the formula: O2EF% = (CaO2 – CvO2 / CaO2) x 100% 2.2.7 Study 1: Statistical Analysis All statistical analysis was performed using Prism® (Graphpad v.9.5.1). A p-value of < 0.05 was deemed statistically significant. First, data was analyzed for normal distribution using the Shapiro-Wilks test. If it passed the normality test, then a repeated measures one-way Analysis of Variance (ANOVA). If the ANOVA was deemed statistically significant, a Dunnett’s multiple comparisons test was performed, comparing the time points to baseline to find which comparison was significant. If the data did not pass the normality test, a non-parametric Friedman test was performed. If the Friedman test showed a significant p-value, a Dunn’s multiple comparisons test was performed, comparing all time points to baseline to find which comparison was significant. All data are represented in median values (interquartile range 41 [IQR], 25–75). All figures have individual data superimposed at each time point, and p-values are included, regardless of significance for the comparison of baseline to the 6-hour mark for consistency. 2.3 Study 1: Results Twelve patients were enrolled into the study, with 2 of the patients being female (16.7%). The median [IQR,25–75] age of the patients was 67.5 [58–70]. The patient information can be found in Table 2-1. Ten of the 12 patients (83.3%) had an initial non-shockable rhythm (i.e., pulseless electrical activity or asystole), whereas the remainder were found to be in ventricular tachycardia or ventricular fibrillation. The median time for return of spontaneous circulation was 15 min [12–19.5]. Nine patients had blood-based brain injury biomarkers collected during the study period. 42 Table 2-1: HIBI patient demographics for hyperoxia study Study number Sex Age Cause of Arrest Initial rhythm Time to ROSC (min) 1 Male 66 ACS PEA 40 2 Male 58 ACS VT/VF 23 3 Male 61 Hemorrhage PEA 15 4 Female 78 ACS VT/VF 20 5 Male 70 Hypoxia PEA 18 6 Female 70 Hypoxia PEA 12 7 Male 58 Hypoxia PEA 14 8 Male 69 Hyperkalemia PEA 12 9 Male 82 Hemorrhage PEA 5 10 Male 70 Hypoxia PEA 15 11 Male 52 Hypoxia PEA 17 12 Male 21 Hypoxia PEA 11 Abbreviations ROSC, return of spontaneous circulation; ACS, acute coronary syndrome; PEA, pulseless electrical activity; VT, ventricular tachycardia; VF, ventricular fibrillation The median dose of intravenous propofol was 60mcg/kg/min [35–80] and at the 6-hour time point was 65mcg/kg/min [35–80; p = 1.0]. The median dose of norepinephrine at baseline was 3.5mcg/min [0.5–6.5] and at the 6-hour time point was 4.0mcg/min [2.5–6.5; p = 0.48]. The 43 median temperature was 36.1˚C [35.7–36.4] at baseline and at the 6-hour mark was 36.3˚C [35.9–36.4; p = 0.40]. The median MAP at baseline was 79mmHg [76–84] and was 77mmHg [74–89; p = 1.0] (Figure 1-D). Additionally, Hgb remained statistically unchanged from baseline to the 6-hour mark (Figure 1-E, Table 2-2). Table 2-2: Clinical management of HIBI patients during hyperoxia Variable, units, median (IQR) p-value Baseline 2-hour 4-hour 6-hour 12-hour 24-hour Statistical test p value Temperature, ˚ C 36.1 (35.7-36.4) 36.1 (35.8-36.5) p = 1.0 36.2 (35.9-36.4) p = 1.0 36.3 (35.9-36.4) p = 0.40 36.2 (35.9-36.7) p = 0.19 36.3 (36.1-36.8) p = 0.05 Friedman 0.04 Propofol, mcg/kg/min 60 (35-80) 60 (35-80) p = 1.0 60 (35-80) p = 1.0 65 (35-80) p = 1.0 70 (35-80) p = 1.0 70 (35-80) p = 1.0 Friedman 0.42 Norepinephrine, mcg/min 3.5 (0.5-6.5) 4.5 (2-6.5) p = 0.78 4.5 (2-6.8) p = 0.09 4 (2.5-6.5) p = 0.48 5 (2.5-6.8) p = 0.53 5 (2.5-7.8) p = 0.57 rmANOVA 0.25 MAP, mmHg 79 (76-84) 79 (78-88) p = 1.0 80 (77-89) p = 1.0 77 (74-89) p = 1.0 75 (72-84) p = 1.0 78 (74-90) p = 1.0 Friedman 0.21 HgB, g/dL 105 (95-117) 103 (97-119) p = 0.49 103 (96-119) p = 0.98 103 (95-118) p = 1.0 102 (92-118) p = 0.65 102 (91-117) p = 0.61 rmANOVA 0.06 Abbreviations MAP, mean arterial pressure; Hgb, hemoglobin; rmANOVA, repeated measures ANOVA The baseline FiO2 used was 40% [30–45] and the median FiO2 required to achieve a PaO2 between 200-300mmHg was 73% [65–75%; p = 0.0004] (Figure 2-1B). The median PaO2 increased from 98mmHg [78–110] to 249mmHg [206–274; p <0.001] from baseline to the 6-hour mark, respectively (Table 2-3, Figure 2-1A). Additionally, PaCO2, remained unaltered throughout the study period (p = 1.0) (Table 2-3, Figure 2-1C). 44 Figure 2-1:Interventional variables during normobaric hyperoxia exposure. The X-axis of each graph represents the period of the study, and each Y-axis has the corresponding variable in their respective values. Each bar graph is represented in median values with individual data superimposed on. All graphs have p values accompanying the comparison from baseline to the 6-hour mark. Panels C-E contain a shaded area that indicates the period of hyperoxia exposure. Panel A represents the median PaO2 in mmHg during the duration of the study. Panel B represents the FiO2 in % that was required to achieve hyperoxia in our patient group. Panels C-E represent PaCO2, MAP, and hemoglobin, respectively, showing that these potential variables remained unchanged during the interventional period, indicating that cerebral blood flow or oxygen carrying capacity was unaltered. Abbreviations: BL, baseline; PaO2, arterial oxygen tension; FiO2, fraction of inspired oxygen; PaCO2, arterial carbon dioxide tension; MAP, mean arterial pressure. Additional blood gas data can be found in Table 2-3. SaO2 at baseline was 95% [93–96] and at the end of hyperoxia exposure was 98% [97–98; p = 0.001]. The PvO2 at the end of hyperoxia exposure was 51mmHg [43–93], which was not significantly increased from baseline 45mmHg [40–50; p = 0.08]. The CaO2 and CvO2 at baseline were 13.9vol% [12.6–15.5] and 10.6vol% [9.7–10.9], respectively, and at the 6-hour mark of the study, the CaO2 significantly 45 increased to 14.6vol% [13–16; p = 0.005], whereas the CvO2 did not significantly change (10.8vol% [10.7–11.8; p = 0.07]). The O2EF% had no significant change from baseline to the end of hyperoxia exposure (23.7% [17.5–29.2] to 23.5% [12.9–30.2; p = 0.98]) (Figure 2-2C). 46 Table 2-3 HIBI blood gas data during hyperoxia Variable, units, median (IQR) p-value Baseline 2-hour 4-hour 6-hour 12-hour 24-hour Statistical test p value pH 7.38 (7.29-7.44) 7.38 (7.30-7.44) p = 1.0 7.37 (7.31-7.41) p = 0.96 7.37 (7.34-7.40) p = 1.0 7.38 (7.34-7.42) p = 0.89 7.40 (7.35-7.44) p = 0.42 rmANOVA 0.10 PaO2, mmHg 98 (78-110) 239 (203-280) p < 0.0001 242 (204-271) p < 0.0001 249 (206-274) p < 0.0001 109 (97-128) p = 0.06 94 (84-120) p = 0.85 rmANOVA < 0.0001 PaCO2, mmHg 41 (38-55) 40 (38-53) p = 1.0 42 (38-53) p = 1.0 43 (39-50) p = 1.0 42 (38-50) p = 1.0 41 (39-51) p = 1.0 Friedman 0.61 HCO3-, mmol/L 25 (23-27) 25 (23-27) p = 1.0 25 (23-27) p = 1.0 25 (23-27) p = 1.0 25 (23-27) p = 1.0 25 (23-27) p = 1.0 Friedman 0.70 SaO2, % 95 (92.5-95.75) 98 (97-98) p < 0.0001 98 (97-99) p < 0.0001 98 (97-98) p = 0.0005 96 (96-96) p = 0.95 96 (96-96) p = 0.63 Friedman < 0.0001 PvO2, mmHg 45 (40-50) 50 (38-67) p = 0.13 51 (39-69) p = 0.14 51 (43-63) p = 0.08 51 (35-55) p = 0.96 48 (36-53) p = 1.0 rmANOVA 0.01 PvCO2, mmHg 49 (43-60) 50 (43-57) p = 1.0 52 (46-59) p = 0.91 50 (45-59) p = 1.0 50 (41-53) p = 0.46 51 (44-55) p = 0.98 rmANOVA 0.20 CaO2, vol% 13.9 (12.6-15.5) 14.4 (13.6-16.3) p = 0.0007 14.3 (13.5-16.5) p = 0.0001 14.6 (13.0-16.3) p = 0.005 13.8 (12.1-15.7) p = 1.0 13.7 (12.3-15.6) p = 1.0 rmANOVA < 0.0001 CvO2, vol% 10.6 (9.7-10.9) 11.3 (10.7-12.0) p = 0.11 10.8 (10.5-11.5) p = 0.08 10.8 (10.7-11.8) p = 0.07 10.5 (9.7-11.3) p = 1.0 10.3 (9.4-11.2) p = 1.0 Friedman 0.01 O2EF, % 23.7 (17.5-29.2) 24.2 (11.4-33.8) p = 1.0 23.4 (11.9-35.4) p = 1.0 23.5 (12.9-30.2) p = 0.98 19.7 (13.9-34.6) p = 1.0 22.4 (16.0-33.5) p = 0.99 rmANOVA 0.88 Abbreviations PaO2, partial pressure of arterial oxygen; PaCO2, partial pressure of arterial carbon dioxide; HCO3-, bicarbonate; SaO2, saturation or arterial oxyhemoglobin; PvO2, venous oxygen tension; PvCO2, venous carbon dioxide tension; CaO2, content of arterial oxygen; CvO2, content of venous oxygen; O2EF, oxygen extraction fraction; rmANOVA, repeated measures ANOVA 47 Figure 2-2:Indices of cerebral oxygenation. The X-axis of each graph represents the period of the study, and each Y-axis has the corresponding variable in their respective values. Each graph is represented with median lines and minimum to maximum bars with individual data superimposed onto the corresponding graphs. The shaded area represents hyperoxia exposure. All graphs have p values accompanying the comparison from baseline to the 6-hour mark. Panel A represents jugular venous bulb oximetry in %. Panel B shows the bilateral average of rSO2 derived from NIRS in %. Panel C represents the O2EF as %. The equation used for O2EF% can be found in the methods. Abbreviations: BL, baseline; SjvO2, jugular venous bulb oximetry; rSO2, regional saturation of oxygen, O2EF, oxygen extraction fraction. The median SjvO2 at baseline was 71% [66–73] and at the 6-hour mark had a non-significant change to 72% [68–85; p = 0.53] (Figure 2-2A). The bilateral median rSO2 value at baseline also underwent a non-significant change from baseline at 62% [55–68] to 66% [57–73; p = 0.12] at the end of hyperoxia exposure (Figure 2-2B). The next aim of our study was to investigate the effect of NH on the release of serum brain injury biomarkers. Arterial GFAP at baseline was 448.9pg/mL [228.1–58465], at the 6-hour mark was 461.1pg/mL [256.4–46639; p = 0.32], and at 12-hours was 434.1pg/mL [269.1–42490; p = 0.32], showing a non-significant change throughout the duration of the study. Similarly, the a-v GFAP at pre-exposure to NH was -4.0pg/mL [-62–8.8], the 6-hour mark difference was -16.0pg/mL [-49.5–3.1; p = 0.96], and at 12-hours mark was -7.2pg/mL [-570–32.1; p = 0.96]. Tau was also found to have a non-significant change throughout the study period 48 with the median arterial level of Tau at baseline being 3.1pg/mL [1.4–49.9], the 6-hour mark was 3.6pg/mL [1.7–35.3; p = 0.32], and at the 12-hour mark was 3.8pg/mL [1.9–33.1; p = 0.96]. There also was no significance with the a-v Tau, with the baseline of -0.4pg/mL [-3.1– -0.04], the 6-hour mark of -0.3pg/mL [-9.1–0.09; p = 1.0], and the 12-hour mark being -0.3pg/mL [-3.3–0.2; p = 1.0]. Interestingly, arterial Nf-L did significantly increase from a median baseline value of 189.5pg/mL [94.2–842.8], to 493.8pg/mL [180.5–1045; p = 0.002] at the 12-hour mark of the study. There was no significant change at the 6-hour mark of arterial Nf-L (433.8pg/mL [130.3–874.9; p = 0.69]). There also was no significant difference in the a-v difference of Nf-L from baseline (-8.4pg/mL [-106.9–2.1]), the 6-hour mark (-15.0pg/mL [-60.2–1.9; p = 0.69]), and the 12-hour mark (-4.6pg/mL [-155.9–7.7; p = 1.0]). Similar to GFAP and Tau, Arterial and a-v difference of UCH-L1 showed no significance throughout all time periods of the study (Arterial UCH-L1 at baseline was 174.0pg/mL [49.4–537.9], at 6-hours was 112.3pg/mL [48.3–512.2; p = 1.0], and at the 12-hour mark was 90.6pg/mL [47.5–431.8; p = 0.12]; a-v UCH-L1 at baseline was -12.6pg/mL [-110.9– -0.1], the 6-hour mark was 1.4pg/mL [-12.9–5.2; p = 0.48], and the 12-hour mark was -7.1pg/mL [-13.5–1.9; p = 0.20] (Figure 2-3A-D). 49 Figure 2-3:Serum brain injury biomarkers. The X-axis of each graph represents the time of biomarker sampling, and the Y-axis has the corresponding biomarker concentration in picograms per millilitre. The second graph in each panel represents the arterial-venous difference. Each panel contains individual data superimposed onto the graph. A negative value indicates cerebral release, and a positive value indicates cerebral uptake. The p-values for each graph compare the pre-hyperoxia to 6-hours post hyperoxia. Panel A represents GFAP and the a-v difference at each time point. Panel B represents Tau and the a-v difference at each sampling time. Panel C represents Nf-L and the a-v difference at each time point. Panel D represents UCH-L1 and the a-v difference at each time point. Abbreviations: Pre, pre-intervention; a-v, arterial-venous; pg/mL, picograms per millilitre; GFAP, glial fibrillary acidic protein; Nf-L, neurofilament light chain; UCH-L1, ubiquitin carboxyl hydrolase L1. The serum levels of inflammatory markers that were measured during the study additionally showed no significant changes. Arterial IL-6 at baseline was 90.9pg/mL [51.0–117.8], at the 6-hour mark was 51.8pg/mL [40.6–116.5; p = 0.19], and at the 12-hour mark was 80.9pg/mL [15.4–113.3; p = 0.54]. The a-v difference of IL-6 at baseline was 0.7pg/mL [-11.3–2.4], at the 6-hour mark was -6.8pg/mL [-16.3–0.9; p = 0.69], and finally at the 12-hour mark 50 was -1.6pg/mL [-9.7– -0.58; p = 0.48]. The arterial IL-10 at baseline was 17.4pg/mL [11.3–24.4], the 6-hour mark was 17.0pg/mL [12.9–25.1; p = 1.0], and at the 12-hour mark was 9.2pg/mL [6.4–15.1; p = 0.12]. Similarly, the a-v difference of IL-10 showed no significant change from baseline of -0.1pg/mL [-0.4–1.5], to the 6-hour mark of 0.2pg/mL [-1.0–2.9; p = 0.48], and to the 12-hour mark of -0.03pg/mL [-0.3–1.7; p = 1.0]. The arterial and a-v difference of TNF-α also showed no significant difference, with arterial TNF-α at baseline being 6.4pg/mL [5.0–9.6], the 6-hour mark being 6.6pg/mL [4.1–10.9; p = 1.0], and the 12-hour mark being 6.6pg/mL [3.4–8.7; p = 0.54]. The a-v TNF-α at baseline was 0.0pg/mL [-1.3–0.9], the 6-hour mark was 0.3pg/mL [-0.4–0.8; p = 0.47], and the 12-hour mark was 0.1pg/mL [-0.6–0.7; p = 0.73]. Lastly, arterial IL-1β at baseline was 0.7pg/mL [0.4–0.7], the 6-hour mark was 0.6pg/mL [0.4–0.9; p = 1.0], and the 12-hour mark was 0.5pg/mL [0.3–0.7; p = 0.20], showing no significant change throughout. The a-v difference of IL-1β at baseline was -0.02pg/mL [-0.1–0.1], the 6-hour mark was -0.004pg/mL [-0.1–0.1; p = 0.96], and the 12-hour mark was -0.04pg/mL [-0.1–0.03; p = 0.32], also showing no significant change throughout the duration of the study (Figure 2-4A-D). 51 Figure 2-4:Serum brain injury inflammatory markers. The X-axis of each graph represents the time of biomarker sampling, and the Y-axis has the corresponding biomarker concentration in picograms per milliliter. The second graph in each panel represents the arterial-venous difference. Each panel contains individual data superimposed onto the graph. A negative value indicates cerebral release, and a positive value indicates cerebral uptake. The p-values for each graph compare the pre-hyperoxia to 6-hours post hyperoxia. Panel A represents IL-6 and the a-v difference at each time point. Panel B represents IL-10 and the a-v difference at each sampling time. Panel C represents TNF-α and the a-v difference at each time point. Panel D represents IL-1β and the a-v difference at each time point. Abbreviations: Pre, pre-intervention; a-v, arterial-venous; pg/mL, picograms per millilitre; IL, interleukin; TNF-α, tumor necrosis factor alpha. 2.4 Study 1: Discussion We performed a physiologic interventional study on 12 post-cardiac arrest HIBI patients using NH (PaO2 200-300mmHg) to assess the indices of cerebral oxygenation (SjvO2 and rSO2), as well as determine the effects of NH on blood-based brain injury biomarkers. We determined 52 that despite administering NH, SjvO2 and rSO2 did not significantly increase during exposure to NH. Additionally, we showed that the blood-based brain injury biomarker, Nf-L, did increase 6-hours post NH exposure in its arterial concentration. However, NH did not mitigate the release of the other brain injury biomarkers being investigated. Current guidelines in the management of post-cardiac arrest HIBI patients recommends avoiding hypoxemia (PaO2 < 60mmHg) and to avoid hyperoxemia (PaO2 > 300mmHg), while using the highest FiO2 until an adequate SpO2 or SaO2 can be measured.24 The controversy regarding NH or higher FiO2 to improve oxygen diffusion to mitigate secondary brain injury in HIBI patients is widely debated. One study compared the use of 30% FiO2 to 100% FiO2 for 1-hour in post-cardiac arrest in patients who achieved return of spontaneous circulation and showed that the 100% FiO2 group who was not treated with TTM had significantly higher NSE when compared to the 30% FiO2 group.107 Additionally, in a multicentered prospective cohort study, the researchers found that exposure to a PaO2 ≥ 300mmHg in the early stages of return of spontaneous circulation was associated with poor neurological outcome.46 Alternative to the negative effects of hyperoxemia exposure, a retrospective study showed that early exposure to hyperoxemia had no association to long term neurological outcome or mortality.106 In the COMACARE43 Trial, they randomized HIBI patients to normoxia (PaO2 75–113mmHg) to moderate hyperoxia (PaO2 of 150–188mmHg) and found no significant differences in serum NSE or other secondary outcomes. Although the evidence is conflicting, the use of NH is often avoided. Restrictive oxygen targets have also been investigated. Recently, the BOX Trial47 aimed to compare restrictive oxygen (PaO2 68-75mmHg) to liberal supplemental oxygen (PaO2 98–105mmHg) in individuals resuscitated from out-of-hospital cardiac arrest. The authors found 53 no significant difference in the primary outcomes of death or survival with poor neurological outcome as well as no difference with serum NSE levels at 48-hours.47 Our results showed no significant increase in the median rSO2 values during NH exposure. This is conflicting with the COMACARE43 trial, which found that exposure to moderate hyperoxia (PaO2 150–188mmHg) provided significantly higher rSO2 values when compared to the normoxia group (p<0.001). This discrepancy between our study and theirs could be largely due to the sample size (n=12 versus n=59), as well as comparing their moderate hyperoxia group to a normoxia group. In a prospective, multicentered, observational study of in-hospital cardiac arrest, higher rSO2 values within the first two hours of cardiac arrest were associated with favourable outcomes.77 Although there is an importance to solving non-invasive techniques to quantify cerebral oxygenation, the clinical applicability and validity of NIRS is questioned due to its limitations.75 During NH exposure, the median SjvO2 of our patients did not significantly increase. Richter et al.,80 used the jugular bulb and SjvO2 to differentiate between favourable and unfavourable outcome. They found that patients with favourable outcome had lower SjvO2 values after 18 hours when compared to unfavourable outcomes (mean +/- IQR, 83% [79–88] p = 0.0003 versus 75%[69–78]).80 As we did not follow outcomes of our patients who were enrolled in the study, we were unable to differentiate favourable to unfavourable outcomes regarding the indices of cerebral oxygenation. Currently, the only recommended blood-based brain injury biomarker for use in prognostication is NSE.24 However, novel blood-based biomarkers of brain injury have sparked interest. In a systemic review and meta-analysis of 86 studies, it was found that Nf-L had the highest accuracy of predicting neurological injury in patients with HIBI at 48 hours.92 In our 54 study, arterial Nf-L at 6 hours post NH exposure was the only blood-based brain injury biomarker that was significantly elevated at any time point. In a post-hoc analysis of COMACARE108, the researchers looked at the ability of serum Nf-L to determine outcomes. They found that at 24-, 48-, and 72 hours post-cardiac arrest, Nf-L concentrations were significantly higher in patients with poor outcome than those with good outcomes.108 Additionally, they found no significant differences among the groups treated with normoxia and moderate hyperoxia in terms of serum Nf-L concentrations.108 A potential for the elevated arterial Nf-L in our study could be due to Nf-L being a structural axon protein sub-unit of neurons,109 found heavily in the white matter of the brain. The white matter of the brain is also associated with extensive damage from HIBI as assessed with magnetic resonance imaging.110 2.5 Study 1: Conclusion In conclusion, the use of NH did not improve the indices of cerebral oxygenation as it pertains to jugular venous bulb oximetry and rSO2. NH also did not mitigate the release of blood-based brain injury biomarkers, however, during the study, it was found that at 6-hours post NH exposure, that Nf-L did significantly increase, which is one of the most accurate markers for neurological outcome. 55 Chapter 3: The Effect of Mild Hypercapnia on Mitigating Secondary Hypoxic Ischemic Brain Injury Following Cardiac Arrest 3.1 Study 2: Introduction HIBI following successful resuscitation from cardiac arrest is a major cause of mortality and neurological injury.7 After the restoration of cardiac output, a period of low cerebral perfusion exists, known as the “no-reflow” period.27 Additional secondary ischemic injury can be exacerbated during this period, which can lead to irreversible neuronal damage and brain hypoxia.24 Current clinical management of HIBI following cardiac arrest is aimed at optimizing CDO2 and to minimize secondary injury. Recent control trials have aimed to augment MAP13–15 in attempts to improve CDO2 and clinical outcomes in cardiac arrest but have been neutral in their findings. Another potential strategy that has gained interest is the use of therapeutic hypercapnia. In health, PaCO2 levels above physiologic normal values (PaCO2 > 45mmHg) have been found to increase CBF by 6-8%,37 meaning the possible intervention to overcoming the “no-reflow” period and augment CBF. Recent trials have suggested that therapeutic or elevated arterial CO2 levels can increase the indices of cerebral oxygenation (derived from NIRS)43 and have shown a reduction in serum NSE (a biomarker of neuron degradation).44 Two previous interventional studies have shown that in a hypercapnic state, the middle cerebral artery velocity in post-cardiac arrest patients does increase, suggesting that regulation of cerebrovascular reactivity to PaCO2 stimulus remains intact.40,41 56 Therefore, we conducted a prospective interventional study investigating the cerebrovascular physiology of mild hypercapnia on mitigating secondary injury in patients with HIBI following cardiac arrest. Specifically, our primary aims were to investigate the effect of mild hypercapnia on middle cerebral artery blood flow velocity using TCD as a surrogate to CBF, cerebral O2EF, a-v differences of blood-based brain injury biomarkers. The secondary aim of this study was to compare the middle cerebral artery reactivity (MCAv) and middle cerebral artery cerebrovascular conductance (MCAv CVC) in patients with HIBI to healthy controls. We hypothesized that mild hypercapnia would be associated with increased middle cerebral artery blood flow velocity, a decrease in cerebral O2EF, and a decrease in a-v differences in blood-based brain injury biomarkers. 3.2 Study 2: Methods We conducted a prospective interventional physiologic study of mild hypercapnia in patients with HIBI following cardiac arrest. The study was approved by the University of British Columbia Clinical Research Ethics Board (H16-03076) and conducted with standards set forth by the Helsinki declaration. The study was performed at Vancouver General Hospital ICU, a closed 34 bed mixed medical-surgical unit with affiliation to the University of British Columbia. The Registered Nurses to patient ratio are 1:1.2. The healthy control portion was performed at the University of British Columbia- Okanagan campus as a study that was approved by the University of British Columbia Clinical Research Ethics Board (H21-00773) and conducted with standards set forth by the Helsinki declaration. 57 3.2.1 Study 2: Population Twenty patients were enrolled from October 2018 to April 2022. Enrolment into the study occurred following the inclusion criteria of a) age > 18 years old; b) return of spontaneous circulation > 10 minutes; c) post-resuscitation Glasgow coma score < 9 and motor score < 5. Patients were excluded from the study if a) anticipated withdrawal of life-sustaining therapies within the next 24 hours; b) known pregnancy; c) related or pre-existing history of central nervous system injury (stroke, traumatic brain injury, intracranial hemorrhage, subarachnoid hemorrhage). 3.2.1.1 Study 2: Healthy Control Population The healthy controls were volunteers between the age of 20–35 as part of a study being conducted at the University of British Columbia – Okanagan campus. 15 participants were included, 7 being female. The individuals were told to be free of caffeine for 12 hours and physical exercise for 24 hours prior to the study commencing. The participants needed to be non-smoking, have a body mass index < 30 kg/m2, free of heart, lung, neurological, and blood vessel disease, have a normal blood pressure, and to not be taking any prescription drugs with the exception of oral contraceptives. 3.2.2 Study 2: Cardiac Arrest Management Vancouver General Hospital ICU adheres to cardiac arrest guidelines that follow temperature management of < 37˚C for 24–48 hours using cooling blankets and allow for a gradual return to normal temperature after cooling protocol. MAP goals are greater than 58 65mmHg and the use of norepinephrine for blood pressure management. The primary sedative used is propofol. Normocapnic ventilation (PaCO2 35–45mmHg) and normoxia (PaO2 80–100mmHg) are targeted. All clinical decisions are made by the attending physician. 3.2.3 Study 2: Neurophysiologic Monitoring Patients had continuous SpO2, heart rate, end-tidal CO2, and temperature monitoring. Patients were lined with a 20-gauge radial arterial catheter (Arrow) for continuous blood pressure monitoring as well as frequent arterial blood gas sampling. Patients were also equipped with a jugular venous catheter (Arrow), placed retrograde at the level of the sigmoid sinus, and placement was confirmed with a lateral X-ray. Additionally, patients were equipped with TCD (Spencer Technologies) to measure the middle cerebral artery velocity to determine CBF. 3.2.3.1 Study 2: Healthy Control Monitoring The healthy volunteers were lined with a 20-gauge radial arterial catheter (Arrow) to measure constant blood pressure and for frequent blood gas sampling. They were also equipped with a jugular venous bulb catheter (Arrow) to sample venous blood leaving the cerebral circulation. The volunteers additionally had TCD equipped to measure middle cerebral artery blood flow velocity, and bilateral ultrasound measurements of the vertebral and internal carotid arteries respectively. SpO2, end-tidal CO2, heart rate, and esophageal temperature were also constantly monitored. 59 3.2.4 Study 2: Data Collection Once patients met inclusion criteria and were instrumented, concurrent arterial and jugular venous blood samples were taken at baseline. Patients were then exposed to mild hypercapnia, defined as a PaCO2 of 45–50mmHg for 2 hours. This was performed by decreasing respiratory rate (i.e., to decrease minute ventilation) on the mechanical ventilator. Simultaneous blood samples were then taken at the 1- and 2-hour mark, where the patients were then returned to their baseline respiratory rate (minute ventilation) on the ventilator. The blood-based biomarkers of brain injury were also sampled at baseline, the 1-, and the 2-hour mark. 3.2.4.1 Study 2: Healthy Control Data Collection Once instrumented and equipped, the healthy controls were laying supine, and placed on a dynamic end-tidal forced breathing apparatus with the ability to control inspired levels of oxygen and carbon dioxide as well as monitor exhaled gases. Baseline blood samples were taken with patients breathing normally for 5 minutes and analyzed using an ABL immediately after sampling. The volunteers were then told to follow a breathing pattern, while being exposed to increased levels of carbon dioxide. Once a steady state was achieved, the end-tidal CO2 was clamped to minimize deviation from the target level. Simultaneous arterial and jugular blood samples were taken in a steady state of hypercapnia at the 5-minute mark, where the volunteers were then able to come off the breathing apparatus. 3.2.4.2 Study 2: Blood-Based Biomarkers of Brain Injury Analysis Section 1.5.2 of this thesis describes the blood-based biomarkers of brain injury of interest for this study. Briefly, the biomarkers of brain injury that were being investigated include 60 GFAP, Nf-L, Tau, and UCH-L1. Additional inflammatory markers from the blood that were collected include IL-6 and IL-1β. The blood-based brain injury biomarkers for the healthy controls that were being investigated include GFAP, Tau, and Nf-L, along with additional inflammatory markers including IL-6 and IL-1β. At each time point, blood samples were obtained using 1 SST vial (Vacutainer, USA) and 1 EDTA vial (Vacutainer, USA) from both the arterial and jugular bulb catheters simultaneously. After these samples were collected, they were stored in a dark area, upright, for 10 minutes. After storage, samples were then centrifuged at 3600rpm for 10 minutes, and the samples were then pipetted into 2ml cryovials. Once the samples were in the cryovials, samples were then stored at -80˚C until analysis, which was performed using Simoa HD (Quanterix®) at the Djavad Mowafaghian Centre for Brain Health located at the University of British Columbia. Data was then inputted into Microsoft Excel® (USA) and further statistical analysis was performed using Prism® (GraphPad v9.5.1). 3.2.5 Study 2: Calculations Biomarkers were compared using an a-v difference, with positive values indicating cerebral uptake, and negative values indicating cerebral release. The data is presented as arterial concentrations and as an a-v difference. Additional calculations were calculated using Microsoft Excel® (USA). CaO2 was calculated using the formula: CaO2 = (1.34 + Hgb + (SaO2/100)) + (PaO2 x 0.003) CvO2 was calculated using the formula: 61 CvO2 = (1.34 + Hgb + (SvO2/100)) + (PvO2 x 0.003) O2EF percentage was calculated using the formula: O2EF% = (CaO2 – CvO2 / CaO2) x 100% Middle cerebral artery reactivity (MCACVR) to PaCO2 in the health controls was calculated by: MCACVR (cm/s/mmHg) = (BL MCAv – Hx MCAv) / (BL CO2 - Hx CO2) Whereas BL is baseline, MCAv is middle cerebral artery flow velocity, and Hx is hypercapnia. For the HIBI group, both the right and left middle cerebral arteries were insonated, therefore, the reactivity was calculated for both sides then averaged. The percent change per unit CO2 was calculated using the formula: % Change MCACVR (%/mmHg) = (((Hx MCAv – BL MCAv)/BL MCAv) x100%) / (Hx CO2 – BL CO2) The middle cerebral artery cerebrovascular conductance (MCA CVC) was calculated using the formula: MCA CVC (cm/s/mmHg) = average MCAv / average MAP MAP for the HIBI group was collected in 10-minute intervals during the study period and averaged over each hour. The MCA CVC reactivity was calculated using the formula: MCA CVC reactivity (cm/s/mmHg/mmHg) = (BL MCA CVC – Hx MCA CVC) / (BL CO2 – Hx CO2). Finally, the last formula used to calculate the % change of MCA CVC reactivity is as follows: % Change MCA CVC reactivity (% change/mmHg) = (((Hx MCA CVC – BL MCA CVC)/BL MCA CVC) x100%) / (Hx CO2 – BL CO2) 62 3.2.6 Study 2: Statistical Analysis For the HIBI group, all statistical analysis was performed using Prism® (Graphpad v.9.5.1). A p-value of < 0.05 was deemed statistically significant. For the HIBI group the data was first analyzed for normal distribution using the Shapiro-Wilks test. If it passed the normality test, then a repeated measures one-way Analysis of Variance (ANOVA). If the ANOVA was deemed statistically significant, a Dunnett’s multiple comparisons test was performed, comparing the time points to baseline to find which comparison was significant. If the data did not pass the normality test, a non-parametric Friedman test was performed. If the Friedman test showed a significant p-value, a Dunn’s multiple comparisons test was performed, comparing all time points to baseline to find which comparison was significant. All data are represented in median values [IQR, 25–75]. All figures have individual data superimposed at each time point, and p-values are included, regardless of significance for the comparison of baseline to the 1- and 2-hour mark for consistency. The healthy control data was collected on a computer software program (Labchart®). Data was averaged 60 seconds prior to blood sampling to determine heart rate, blood pressure, end-tidal CO2, end-tidal oxygen, temperature, jugular venous blood pressure, and middle cerebral artery blood flow velocity. Values were then transferred into Prism® (GraphPad v9.5.1). The same method was used to determine if the data was normally distributed for the healthy controls as the HIBI group. If the healthy control data was distributed normally, a paired T-test was performed. If the data was not normally distributed, a Wilcoxon test was performed. To compare the healthy control data to the HIBI group data, a Mann-Whitney test was performed. 63 3.3 Study 2: Results Twenty HIBI patients were included in the study, with 10 having blood-based brain injury biomarkers collected. Of the 20 patients, 5 were female (25%) and the median age was 53 [42–66]. The patient information can be found in Table 3-1. Fifteen of the 20 patients (75%) had an initial non-shockable rhythm (i.e., pulseless electrical activity or asystole), whereas the remainder were found to be in ventricular tachycardia or ventricular fibrillation. The median time for return of spontaneous circulation was 17 min [17.3–29.8]. Intravenous dose of propofol and norepinephrine were not recorded for this study. Additional patient monitoring information can be found in Table 3-2, where temperature, MAP, and Hgb remained unchanged throughout the study duration. 64 Table 3-1 HIBI patient demographics for hypercapnia study Study number Sex Age Cause of arrest Initial rhythm Time to ROSC (min) 1 Male 66 Overdose PEA 21 2 Male 69 Hypoxia PEA 17 3 Male 46 Angioedema PEA 24 4 Female 46 VF VT/VF 30 5 Male 35 Hyperkalemia PEA 29 6 Male 63 Hypoxia PEA 18 7 Male 40 Overdose PEA 55 8 Male 50 Overdose VT/VF 34 9 Male 33 Overdose PEA 37 10 Female 31 Hypoxia PEA 20 11 Male 38 P.E. PEA 25 12 Male 65 Hyperkalemia PEA 23 13 Female 69 VT VT/VF 30 14 Male 53 Hypoxia PEA 15 15 Female 74 Hypoxia PEA 20 16 Male 65 Hemorrhage PEA 10 17 Male 54 VT VT/VF 11 18 Male 78 Hypoxia PEA 18 19 Female 46 VT VT/VF 24 20 Male 53 Hypoxia PEA 17 Abbreviations ROSC, return of spontaneous circulation; PEA, pulseless electrical activity; VT, ventricular tachycardia; VF, ventricular fibrillation; P.E., pulmonary embolus 65 Table 3-2 Clinical management of HIBI patient during hypercapnia Variables, units, median (IQR) p-value Baseline 1-hour 2-hour Statistical test p value Temperature, ˚C 36.2 (35.6-36.6) 36.2 (35.5-36.6) p = 0.46 36.2 (35.6-36.7) p = 0.54 rmANOVA 0.30 MAP, mmHg 80 (69-91) 79 (70-90) p = 1.0 79 (72-91) p = 0.80 rmANOVA 0.74 Hgb, g/dL 100 (89-117) 100 (89-117) p = 1.0 100. (89-117) p = 1.0 rmANOVA 1.0 Abbreviations MAP, mean arterial pressure; Hgb, hemoglobin; rmANOVA, repeated measures ANOVA Fifteen healthy individuals went through baseline breathing and 14 completed hypercapnia exposure. Of the 15 healthy individuals, 7 were female (46.7%) and the median age was 27 [23–30] (Table 3-3). Table 3-3 Healthy control demographics Subject number Sex Age Height (cm) Weight (kg) BMI (kg/m2) 1 Male 30 186 78 22.5 2 Male 24 186 72 20.8 3 Female 27 161 57 22.0 4 Female 23 168 57 20.2 5 Male 29 183 78 23.3 6 Male 31 180 74 22.8 7 Male 26 178 69 21.8 8 Male 27 175 74 24.2 9 Male 30 181.5 76.5 23.2 10 Male 28 183 73 21.8 11 Female 31 157.5 54 21.8 12 Female 22 170 76 26.3 13 Female 22 170 74 25.6 14 Male 21 188 93 26.3 15 Female 33 159 62 24.5 Abbreviations BMI, Body mass index 66 Baseline median PaCO2 was 37mmHg [34–40], which elevated to a median of 43mmHg [39–46; p = 0.0006] at the 1-hour mark, and to 45mmHg [41–47; p < 0.0001] at the 2-hour mark before returning the subjects to their baseline (Figure 3-1, panel B). PaO2 remained unchanged during the duration of the study (Table 3-4), with a baseline value of 109mmHg [86–136] to the 2-hour mark of 109mmHg [88–119; p = 0.37]. Figure 3-1:Comparing the effects of elevated arterial carbon dioxide on the middle cerebral artery, jugular venous oxygen saturation, and oxygen extraction fraction in healthy controls (Panel A series) to patients with HIBI (Panel B series). The First column of graphs represents PaCO2, the second column of graphs represents MCA velocity, the third column represents jugular venous bulb oxygen saturation, and the fourth column represents the O2EF in percentage. Abbreviations: BL, baseline; PaCO2, partial pressure of arterial carbon dioxide; MCA, middle cerebral artery; SjvO2, Jugular venous bulb oximetry, O2EF, oxygen extraction fraction. 67 Table 3-4 HIBI patient blood gas data during hypercapnia Variables, units, median (IQR) p-value Baseline 1-hour 2-hour Statistical test p value PaCO2, mmHg 37 (34-40) 42.50 (39-46) p = 0.0006 45 (41-47) p < 0.0001 Friedman < 0.0001 pH 7.41 (7.36-7.42) 7.37 (7.32-7.41) p = 0.018 7.36 (7.30-7.41) p = 0.004 Friedman 0.003 PaO2, mmHg 109 (86-136) 114 (87-130) p = 0.86 109 (88-119) p = 0.37 rmANOVA 0.29 SaO2, % 96 (94-97) 96 (94-97) p = 0.86 96 (94-97) p = 0.23 Friedman 0.19 CaO2, vol% 13.5 (12.1-15.6) 13.2 (12.0-15.6) p =0.97 13.4 (11.9-15.7) p = 0.36 rmANOVA 0.23 PvCO2, mmHg 43 (40-45) 47 (42-50) p = 0.0004 47 (43-51) p < 0.0001 Friedman < 0.0001 SjvO2, % 76.0 (64.5-78.75) 73.5 (66.0-82.5) p = 0.4432 75.5 (64.75-82.75) p = 0.7311 rmANOVA 0.57 CvO2, vol% 9.963 (8.719-11.69) 11.09 (8.427-12.11) p = 0.2995 11.09 (8.416-12.50) p = 0.5635 rmANOVA 0.41 O2EF, % 19.8 (17.3-33.3) 20.6 (14.2-30.3) p = 0.41 20.9 (13.1-31.5) p = 0.57 rmANOVA 0.44 Abbreviations PaCO2, partial pressure of arterial carbon dioxide; PaO2, partial pressure of arterial oxygen; SaO2, arterial oxygen saturation; CaO2, content of arterial oxygen; PvCO2, venous carbon dioxide tension; SjvO2, jugular venous bulb oximetry; CvO2, content of 68 venous oxygen; O2EF, oxygen extraction fraction; rmANOVA, repeated measures ANOVA 3.3.1 Study 2: Results - Middle Cerebral Artery Data in HIBI Patients The median baseline value for the average bilateral middle cerebral artery velocity in the HIBI patients before initiation of hypercapnia was 38.1cm/sec [32.8–48.2]. At the 1-hour mark of hypercapnia, the middle cerebral artery velocity was 39.2cm/sec [34.6–49.9; p = 0.14], and at the 2-hour mark showed a significant increase to 40.0cm/sec [34.6–52.0; p = 0.03] (Figure 3-1, panel B). 3.3.2 Study 2: Results - O2EF Data in HIBI Patients The cerebral O2EF was calculated as per the equation previous listed in the methods, with the CvO2 being derived from the jugular venous bulb blood gas data. The baseline O2EF% was 19.8% [17.3–33.3], and with the hypercapnia trial at 1-hour was 20.6% [14.2–30.3; p = 0.41] and at the 2-hour mark was 20.9% [13.1–31.5; p = 0.57], showing a non-significant change during the study period (Table 3-4; Figure 3-1, panel B). 3.3.3 Study 2: Results – Blood-Based Biomarker of Brain Injury Data in HIBI Patients The blood-based brain injury biomarkers of interest were GFAP, Tau, Nf-L, and UCH-L1, and were collected in 10 of the HIBI patients (Figure 3-2). The arterial GFAP had no significant change throughout the study period, with a median baseline of 673.6pg/mL [203.9–1739], the 1-hour mark of 666.4pg/mL [235.4–1845; p = 0.15], and at 2 hours being 767.6pg/mL [233.8–1678; p = 0.74]. The a-v difference for GFAP also was non-significant, with the baseline 69 of 11.1pg/mL [-37.8–65.5], the 1-hour mark of 25.6pg/mL [10.7–67.2; p = 0.15], and the 2-hour mark of 14.1pg/mL [-59.3–137.7; p = 1.0]. Arterial Tau levels throughout the study period also had non-significant changes. The median baseline value was 16.8pg/mL [9.5–58.3], the 1-hour mark was 11.5pg/mL [4.0–51.9; p =1.0], and the 2-hour mark was 14.4pg/mL [4.7–96.0; p = 1.0]. The a-v difference for serum Tau was also non-significant, with the median baseline of -0.47pg/mL (-4.2–5.8), the 1-hour mark difference of 0.4pg/mL [-1.1–14.2; p = 1.0], and the 2-hour mark of -0.3pg/mL [-1.0–3.1; p = 1.0]. The arterial Nf-L levels similarly had a non-significant change during the study period, with the median baseline of 224.9pg/mL [88.0–1235], a 1-hour mark of 220.6pg/mL [111.1–1241; p = 1.0], and the 2-hour mark of 174.3pg/mL [131.5–1225; p = 1.0]. The a-v difference of serum Nf-L additionally showed to be non-significant, with the median baseline being -6.9pg/mL [-42.7–24.6], the 1-hour mark difference of 11.4pg/mL [-13.4–63.1; p = 0.53], and the 2-hour difference of 3.4pg/mL [-113.0–18.2; p = 1.0]. Like the other three blood-based brain injury biomarkers, arterial UCH-L1 also showed to be non-significant during the study period. The median baseline was 104.5pg/mL [70.1–135.8], the 1-hour mark was 97.2pg/mL [55.9–134.8; p = 0.74], and the 2-hour mark was 85.5pg/mL [63.2–142.8; p = 1.0]. The a-v difference of UCH-L1 however, showed a significant cerebral uptake at the 1-hour mark from baseline. The median baseline value was -15.7pg/mL [-21.9–4.6], at the 1-hour mark was 0.2pg/mL [-9.0–5.3; p = 0.015], and at the 2-hour mark of 3.0pg/mL [-3.5–8.8; p = 0.09]. 70 Figure 3-2: Serum brain injury biomarkers in the HIBI patients. The X-axis of each graph represents the time of biomarker sampling, and the Y-axis has the corresponding biomarker concentration in picograms per millilitre. The bottom panel represents the a-v difference. Each panel contains individual data superimposed onto the graph. A negative value indicates cerebral release, and a positive value indicates cerebral uptake. The p-values for each graph compare the baseline to 1- and 2-hours of hypercapnia. Abbreviations: BL, baseline; a-v, arterial-venous; pg/mL, picograms per millilitre; GFAP, glial fibrillary acidic protein; Nf-L, neurofilament light chain; UCH-L1, ubiquitin carboxyl hydrolase L1 The additional inflammatory biomarkers being investigated were IL-6 and IL-1β. for both IL-6 and IL-1β, the arterial and a-v differences showed non-significant changes during the duration of the study (Figure 3-3). 71 Figure 3-3: Serum inflammatory biomarkers in the HIBI patients. The X-axis of each graph represents the time of biomarker sampling, and the Y-axis has the corresponding biomarker concentration in picograms per millilitre. The bottom panel represents the arterial-venous difference. Each panel contains individual data superimposed onto the graph. A negative value indicates cerebral release, and a positive value indicates cerebral uptake. Abbreviations: BL, baseline; a-v, arterial-venous; pg/mL, picograms per millilitre; IL-6, interleukin 6; IL-1β, interleukin 1 beta. 3.3.4 Study 2: Results - Comparing Middle Cerebral Artery Data of Controls to HIBI Patients In the healthy controls, PaCO2, middle cerebral artery velocity, SjvO2, and O2EF were measured (Figure 3-1, panel A). The median baseline PaCO2 was 43mmHg [42–44], and during the end of the hypercapnia trial, significantly increased to 51mmHg [50–53; p < 0.0001]. The 72 middle cerebral artery velocity of the healthy controls at baseline was 78.1cm/sec [67.9–96.5], and significantly increased to 105.0cm/sec [87.4–128.1; p < 0.0001]. The SjvO2 significantly increased from the baseline median of 69% [65–72] to 80% [79–83; p < 0.0001] at the end of hypercapnia. Additionally, the O2EF significantly decreased from the baseline of 27.9% [24.5–32.8] to 15.5% [13.9–17.4; p < 0.0001]. These results differ from the HIBI patients, as only the PaCO2 and the 2-hour mark middle cerebral artery velocity reached significant increases, whereas SjvO2 and O2EF did not reach significant changes during the hypercapnia study. Next, using the middle cerebral artery velocities and the PaCO2, we aimed to assess the MCACVR as it relates to CO2 (Figure 3-4). The healthy control MCACVR was significantly higher than the HIBI patients, with the median value for the controls being 3.0cm/sec/mmHg [2.4–3.8], and 0.14cm/sec/mmHg [-0.01–0.7; p < 0.0001] for the HIBI patients. We then aimed to assess the % MCACVR change per mmHg CO2, and again found that the healthy controls, with a median value 3.9%change/mmHg CO2 [3.1–4.9], was significantly higher than the HIBI patients 0.3%change/mmHg CO2 [0.02–1.7; p < 0.0001]. We next looked at MCA CVC reactivity by incorporating MAP to the equation (in methods). Again, we found that healthy control MCA CVC reactivity to CO2 was significantly higher, with a median of 0.03cm/sec/mmHg/mmHg [0.02–0.03] when compared to the HIBI groups median of 0.002 cm/sec/mmHg/mmHg [-0.002–0.01; p < 0.0001]. Lastly, we looked at the % change of MCA CVC reactivity per mmHg CO2 and again found a significant difference between the healthy controls (3.2%change/mmHg [2.3–4.5]) to the HIBI group (0.3%change/mmHg [-0.5–2.5; p = 0.0004]). 73 Figure 3-4:Comparing absolute and relative MCACVR and absolute and relative MCA CVC reactivity in controls (blue) to HIBI patients (red). Panel A shows the absolute MCACVR on the Y-axis in cm/sec/mmHg. Panel B shows the percentage change of MCACVR per unit change of PaCO2. Panel C shows the absolute MCA CVC using MCA velocity as it relates to MAP, divided by carbon dioxide. Panel D shows the percentage change of MCA CVC per unit change of carbon dioxide. Abbreviations: MCA, middle cerebral artery; MCACVR, middle cerebral artery reactivity; MCA CVC; middle cerebral artery conductance; HIBI, hypoxic ischemic brain injury; MAP, mean arterial pressure 74 3.3.5 Study 2: Results – Blood-Based Biomarkers of Brain Injury Data in Healthy Controls Fourteen of the 15 healthy controls underwent both baseline blood work and hypercapnia exposure. The blood-based biomarkers of brain injury and inflammation that were collected include GFAP, Tau, Nf-L (Figure 3-5), IL-6, and IL-1β (Figure 3-6). The median arterial GFAP in the healthy controls at baseline was 65.7pg/mL [55.7–83.9], and significantly increased to a median value of 83.2pg/mL [64.1–96.6; p = 0.0003] during hypercapnia exposure. The a-v difference however, showed no significant change with a median baseline of -3.9pg/mL [-8.7–3.5] to a hypercapnia value of -5.8pg/mL [-12.4– -0.1; p = 0.44]. The arterial Tau levels at baseline were 1.2pg/mL [0.8–1.5], and the hypercapnic levels, that had a nonsignificant change, was 1.2pg/mL [0.7–1.8; p = 0.99]. The a-v difference of Tau also had a nonsignificant change throughout, with the baseline value of 0.03pg/mL [-0.5–0.2] and the hypercapnic a-v difference being -0.1pg/mL [-0.4–0.4; p = 0.53]. The arterial Nf-L did rise, however did not reach significance, with the median baseline in the healthy controls being 5.7pg/mL [3.8–8.3] and the median during hypercapnia being 6.5pg/mL [3.8–9.2; p = 0.10]. The a-v difference of Nf-L also showed no significant changes, with the baseline of -0.8pg/mL [-1.3–0.2] and with hypercapnia exposure being -0.3pg/mL [-1.3–0.4; p = 0.46]. With the arterial IL-6, there was a significant increase from baseline to hypercapnia, going from 0.5pg/mL [0.4–0.8] to 0.9pg/mL [0.8–1.1; p < 0.0001]. However, this significance was not reached with the a-v difference, with baseline and hypercapnic values being -0.04pg/mL [-0.1– -0.001] and -0.02pg/mL [-0.13–0.01; p = 0.70], respectively. Lastly, the arterial IL-1β and a-v difference of IL-1β did not reach significance, with the arterial baseline and hypercapnia values being 0.1pg/mL [0.04–0.4] and 0.1pg/mL [0.1–75 0.4; p = 0.37], respectively, and the a-v differences of baseline to hypercapnia values being -0.02pg/mL [-0.05–0.01] and 0.004pg/mL [-0.02–0.04; p = 0.54], respectively. Figure 3-5: Serum brain injury biomarkers in the healthy patients. The X-axis of each graph represents the time of biomarker sampling, and the Y-axis has the corresponding biomarker concentration in picograms per millilitre. The bottom panel represents the arterial-venous difference. Each panel contains individual data superimposed onto the graph. A negative value indicates cerebral release, and a positive value indicates cerebral uptake. Abbreviations: BL, baseline; a-v, arterial-venous; pg/mL, picograms per millilitre; GFAP, glial fibrillary acidic protein; Nf-L, neurofilament light chain. 76 Figure 3-6: Serum inflammatory biomarkers in the healthy patients. The X-axis of each graph represents the time of biomarker sampling, and the Y-axis has the corresponding biomarker concentration in picograms per millilitre. The bottom panel represents the arterial-venous difference. Each panel contains individual data superimposed onto the graph. A negative value indicates cerebral release, and a positive value indicates cerebral uptake. Abbreviations: BL, baseline; a-v, arterial-venous; pg/mL, picograms per millilitre; IL-6, interleukin 6; IL-1β, interleukin 1 beta. 3.4 Study 2: Discussion We conducted a prospective physiologic interventional study using mild hypercapnia for 2 hours in post-cardiac arrest HIBI patients. Additionally, we were able to compare middle cerebral artery velocity data from our HIBI cohort to healthy controls. We found a significant increase in middle cerebral artery velocity at the 2-hour mark (prior to end of trial) from 38.1cm/sec [32.8–48.2] to 40.0cm/sec [34.6–52.0; p = 0.03]. However, we did not observe a 77 decrease in O2EF% with no changes from baseline at the 1- and 2-hour mark. Mild hypercapnia also did not mitigate the release of cerebral blood-based biomarkers of injury in arterial circulation, however, the a-v difference of UCH-L1 (marker of neuronal cell body injury) showed a significant rise at the 1-hour mark, indicating a cerebral uptake (a lower venous concentration leaving the cerebral microvasculature when compared to the arterial circulation) of UCH-L1. When comparing the middle cerebral artery dynamics between the HIBI and healthy groups, we found the healthy group to have a higher middle cerebral artery velocity at baseline and during exposure to hypercapnia. Additionally, in the healthy control group, SjvO2 significantly increased during hypercapnia with a subsequent significant decrease in O2EF, which was not observed in the HIBI group. When comparing the middle cerebral artery reactivity to CO2 and % change of middle cerebral artery reactivity per mmHg of CO2, there were significant differences between the healthy control group and the HIBI group, with the healthy control group being more elevated. The middle cerebral artery CVC and % change in the healthy control group was also significantly higher than the HIBI group, which could indicate a depressed response to CO2 regulation in CBF in the HIBI group. Carbon dioxide is a one of the main regulators of CBF, with CBF increases of 6-8% per mmHg CO2 above physiologic normal (PaCO2 > 45mmHg).37 This can provide the potential for overcoming the cerebral hypoperfusion that occurs, which can last up to 24 hours after successful resuscitation from cardiac arrest.27 However, elevated PaCO2 levels can create a state of acidosis by dropping the pH level below physiologic normal, therefore requiring close monitoring of arterial blood gases and ventilation status. 78 Two randomized trials compared the use of elevated PaCO2 levels (44–45mmHg;43 50–55mmHg44) for 24 to 36 hours in the ICU and compared to low normal or normal PaCO2 values. Jakkula et al., had a primary endpoint evaluating concentration of NSE (glycolytic enzyme found in neuronal cells) at 48 hours and found no difference among the high- and low CO2 groups.43 The authors did find that the high PaCO2 group did have a higher index of cerebral oxygenation, as derived from NIRS.43 In a post-hoc analysis of COMACARE, serum Nf-L concentrations did not differ among the two PaCO2 groups.108 In a systemic review, Nf-L had the highest accuracy predicting neurological injury in patients with HIBI at 48 hours.92 Eastwood et al., had a primary outcome of serum levels of NSE at 72 hours and found that when compared to the cardiac arrest patients maintained with normocapnia, the hypercapnia group had lower NSE levels at all time points.44 These randomized trials did not assess the a-v differences of the specified blood-based brain injury biomarkers, nor did they utilize TCD or jugular venous bulb monitoring. Two studies assessed cerebrovascular reactivity using TCD of the middle cerebral artery in cardiac arrest patients that exposed the patients to brief periods of hypercapnia (by reducing minute ventilation by 20%) during the first 24 hours after cardiac arrest. In the first study, Buunk et al., exposed 10 post-cardiac arrest patients to 4 periods of hypercapnia over 24 hours and found significant increases in middle cerebral artery mean flow velocity and SjvO2 at all time points.40 The authors presented their % change of middle cerebral artery mean flow velocity to unit of CO2 in %/kPa. By using the absolute values in which the authors provided and converting the PaCO2 from kPa to mmHg (using the equations listed in the methods), the % change middle cerebral artery mean flow velocity/mmHg CO2 in their study resembled more closely to the healthy control data from our study and had even higher values than the healthy controls. In the second study, Bisschops et al., used similar methodology and assessed cerebrovascular reactivity 79 in 10 post-cardiac arrest patients undergoing mild hypothermia treatment.41 They found an absolute increase in middle cerebral artery mean flow velocity of 49.2 ± 22.8cm/sec from 38.6 ± 16.9cm/sec (p <0.001) and described a mean change of 4.4 ± 3.5%/mmHg increase in middle cerebral artery mean flow velocity during hypercapnia.41 Similarly, their findings of % change of middle cerebral artery mean flow velocity per mmHg CO2 were greater than both our healthy controls and HIBI group. Both studies stated a preserved cerebrovascular reactivity in their post-cardiac arrest patients.40,41 When comparing our HIBI patients to the healthy controls, we did not see similar findings in terms of preserved cerebrovascular reactivity. 3.5 Study 2: Conclusion In conclusion, we conducted a prospective interventional study investigating the cerebrovascular physiology of mild hypercapnia on mitigating secondary injury in patients with HIBI following cardiac arrest. We found a significant increase in middle cerebral artery mean flow velocity only at the end of exposure to hypercapnia at the 2-hour mark. We did not see a decrease in cerebral O2EF% as we hypothesized to the exposure of mild hypercapnia. Only the a-v difference of UCH-L1 at 1 hour had a significant change, indicating a cerebral intake of the biomarker. When assessing the middle cerebral artery dynamics between the HIBI group and the healthy control group, the HIBI group had a decreased cerebrovascular reactivity and conductance during mild hypercapnia. 80 Chapter 4: Conclusion Hypoxic ischemic brain injury is a devastating injury following cardiac arrest with injuries occurring during both ischemic (primary injury) and reperfusion (secondary injury). Current patient care strategies focus on improving both CDO2 and utilization, which is done through interventions of augmenting MAP, ventilating patients to normocapnia and normoxemia, maintaining Hgb concentrations > 70g/dL, and by utilizing TTM. Current research has focused on modifiable variables (i.e., high MAP versus normal MAP; mild hypercapnia versus normocapnic ventilation; and moderate hyperoxia versus normoxia), however these studies have failed to demonstrate marked clinical improvements to patient outcomes with HIBI. Further studies are required to understand the heterogeneity of HIBI, with possibilities to capitalize on the different presentations of this injury. In study one, we hypothesized that exposure to NH would be associated with improving CDO2 by increasing the surrogate measures rSO2 and SjvO2. Although the PaO2 did increase to a median of 249mmHg [206–274; p < 0.0001] at the 6-hour mark of the study, we did not find an increase in either rSO2 or SjvO2. Therefore, the use of NH did not improve the indices of cerebral oxygenation. Additionally, the use of NH did not mitigate the release or decrease the a-v differences of blood-based brain injury biomarkers throughout the duration of the study. However, arterial Nf-L did increase 6-hours post NH exposure, which is one of the most accurate biomarkers for neurological outcome. In study two, we hypothesized that mild hypercapnia would be associated with an increased middle cerebral artery blood flow velocity accompanied with a decreased cerebral O2EF as surrogates to CBF. We demonstrated a significant increase in the middle cerebral artery 81 blood flow velocity at the end (2-hour mark) of the study, however, did not see a decrease in cerebral O2EF as hypothesized. Additionally, we demonstrated that the HIBI group had a decreased middle cerebral artery cerebrovascular reactivity to CO2 when compared to healthy controls. There was a significant decrease in a-v difference of UCH-L1 at the 1-hour mark, however, all additional blood-based biomarkers of brain injury did not have significant changes. The possible decrease of UCH-L1 in the a-v differences may be due to error in sampling or analyzing the sample which could have resulted in the significant change. The strengths of study one includes the use of paired arterial and venous blood samples that occurred simultaneously during the study. This allowed the ability to isolate the cerebral microvasculature, not only to see what was occurring at that time point, but also to reduce the possibility of contamination from extracranial organs with the blood gas sampling. Another strength of study one was the use of two separate monitoring techniques to assess the indices of cerebral oxygenation. By pairing jugular venous bulb oximetry and NIRS, we were able to compare the data points during the study. Limitations of study one is that the variable time point of start of study from the initial point of cardiac arrest and return of spontaneous circulation. The patients enrolled in the study may have been at different stages of the HIBI injury process, therefore the use of hyperoxia may have been ineffective or and even blood-based brain injury biomarker sampling could have additionally been affected by the time. We were additionally limited in sample size, which could have played a role in data analysis, as well as only 9 of the 12 HIBI patients had blood-based brain injury biomarkers sampled. Additionally, we did not compare our hyperoxia data to HIBI patients that were being ventilated at normoxia, therefore the blood-based brain injury biomarker 82 data should be interpreted with caution. Another possible limitation was the lack of a control group to compare to the hyperoxia group, as well as having a healthy control group. The strengths of study two include the ability to compare the hypercapnia data of the HIBI patients to a health control group undergoing hypercapnic breathing. This allowed us to compare the TCD results of the middle cerebral artery dynamics in the patients with HIBI to the healthy individuals, giving us a better understanding of the cerebrovascular reactivity to CO2 in the HIBI population. Additionally, similar to study one, we were able to pair a-v blood samples, in both HIBI and healthy controls, to isolate the cerebral microvasculature to compare what is going on in disease and in health. As well as in both the HIBI group and the healthy controls, the same investigator placed the TCD equipment on the study participants, allowing for consistency between in the TCD results. The limitations for study two are similar to study one. Sample size of the HIBI group was 20 patients, 10 of which we were able to collect a-v blood samples for blood-based brain injury biomarkers on. This again brings up caution with interpreting the data as it pertains to the blood-based biomarkers of brain injury. The healthy control subjects did not have UCH-L1 measured, which was one of the biomarkers being looked at in the HIBI population. Additionally, the use of healthy controls in comparing to disease states may create bias as the healthy controls were free of comorbidities and younger than the HIBI group. Lastly, the time of cardiac arrest to initiation of the hypercapnia study in the ICU was variable among HIBI patients, therefore each patient may have been at different stages of the injury prior to hypercapnia and blood sampling. As HIBI and the secondary injury involved is multifactorial and dynamic over time, a limitation of both studies only collects data during the patient’s first 24 hours of being in the 83 ICU, which may narrow the window of seeing a potential benefit to normobaric hyperoxia or mild hypercapnia. As of now, the informative results of our studies indicate that ventilating patients to normal ranges of PaO2 (80–100mmHg) and PaCO2 (35–45mmHg) should be adhered to, as stated in the current guidelines for cardiac arrest management.24 As attractive in theory as it may be in terms of increasing CBF, mild hypercapnia only modestly improved middle cerebral artery blood flow velocity at the 2-hour mark of the study, and when compared to the healthy control group, showed a depressed response in the cerebral vasculature reactivity to CO2. Until larger randomized clinical trials assessing mild hypercapnia and cerebrovascular reactivity in HIBI are done, HIBI patients should be ventilated to a normal PaCO2. The future direction of post-cardiac arrest HIBI research should focus on the understanding of the pathophysiology of the disease. Future research should also further investigate the blood-based brain injury biomarkers, by quantifying ‘normal ranges’ and by improving the ease of sampling within the hospital or at the bedside as it can be a potential method to better understand injury severity or patient outcomes. Current research is focused on single interventions or management strategies of HIBI; however, minimal improvements are seen in patient outcomes or advances in patient care within the critical care setting. As stated in the introduction, the concept of heterogeneity of HIBI can make one intervention, such as augmenting MAP, improve cerebral oxygenation in perfusion-dependent HIBI, however, not see the same improvement in diffusion-limited HIBI. Therefore, by better understanding the disease process, it will allow researchers to target specific injurious mechanisms of HIBI and allow for the possibility of combining therapeutic interventions to improve patient care in the critical care setting and ideally improve outcomes of this devastating injury. The current state of knowledge 84 based on HIBI as a disease and management practices is limited, as gaps in pathophysiology exist on a cellular and inflammatory level. As the pathophysiology of HIBI becomes better understood, so will the management of HIBI patients in critical care units. 85 References 1. Yan S, Gan Y, Jiang N, et al. The global survival rate among adult out-of-hospital cardiac arrest patients who received cardiopulmonary resuscitation: A systematic review and meta-analysis. Crit Care. 2020;24(1). doi:10.1186/s13054-020-2773-2 2. Sawyer KN, Camp-Rogers TR, Kotini-Shah P, et al. 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Thesis/Dissertation
eng
Experimental Medicine
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Sekhon, Mypinder S.
The effects of arterial oxygen and carbon dioxide tension on cerebral vascular physiology in hypoxic ischemic brain injury after cardiac arrest
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