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Antibiotics 13 (4): 320 (2024)
Abdel Hadi, Hamad
Dargham, Soha R.
Eltayeb, Faiha
Ali, Mohamed O. K.
Suliman, Jinan
Ahmed, Shiema Abdalla M.
Omrani, Ali S.
Ibrahim, Emad Bashir
Chen, Yuzhou
Tsui, Clement K. M.
Skariah, Sini
Sultan, Ali
Antimicrobial resistance is a global healthcare threat with significant clinical and economic consequences peaking at secondary and tertiary care hospitals where multidrug-resistant Gram-negative bacteria (MDR GNB) lead to poor outcomes. A prospective study was conducted between January and December 2019 for all invasive bloodstream infections (BSIs) secondary to MDR GNB in Qatar identified during routine microbiological service to examine their clinical, microbiological, and genomic characteristics. Out of 3238 episodes of GNB BSIs, the prevalence of MDR GNB was 13% (429/3238). The predominant MDR pathogens were Escherichia coli (62.7%), Klebsiella pneumoniae (20.4%), Salmonella species (6.6%), and Pseudomonas aeruginosa (5.3%), while out of 245 clinically evaluated patients, the majority were adult males, with the elderly constituting almost one-third of the cohort and with highest observed risk for prolonged hospital stays. The risk factors identified included multiple comorbidities, recent healthcare contact, previous antimicrobial therapy, and admission to critical care. The in-hospital mortality rate was recorded at 25.7%, associated with multiple comorbidities, admission to critical care, and the acquisition of MDR Pseudomonas aeruginosa. Resistant pathogens demonstrated high levels of antimicrobial resistance but noticeable susceptibility to amikacin and carbapenems. Genomic analysis revealed that Escherichia coli ST131 and Salmonella enterica ST1 were the predominant clones not observed with other pathogens.
Citation: Abdel Hadi, H.; Dargham,S.R.; Eltayeb, F.; Ali, M.O.K.; Suliman,J.; Ahmed, S.A.M.; Omrani, A.S.;Ibrahim, E.B.; Chen, Y.; Tsui, C.K.M.;et al. Epidemiology, Clinical, andMicrobiological Characteristics ofMultidrug-Resistant Gram-NegativeBacteremia in Qatar. Antibiotics 2024,13, 320. https://doi.org/10.3390/antibiotics13040320Academic Editor: Jamie WagnerReceived: 28 February 2024Revised: 25 March 2024Accepted: 26 March 2024Published: 31 March 2024Copyright: © 2024 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).antibioticsArticleEpidemiology, Clinical, and Microbiological Characteristics ofMultidrug-Resistant Gram-Negative Bacteremia in QatarHamad Abdel Hadi 1,2,* , Soha R. Dargham 3, Faiha Eltayeb 4, Mohamed O. K. Ali 5, Jinan Suliman 6,Shiema Abdalla M. Ahmed 1, Ali S. Omrani 1,2 , Emad Bashir Ibrahim 4,7, Yuzhou Chen 8,Clement K. M. Tsui 8,9,10, Sini Skariah 11 and Ali Sultan 111 Communicable Diseases Centre, Hamad Medical Corporation, Doha P.O. Box 3050, Qatar;sahmed84@hamad.qa (S.A.M.A.); aomrani@hamad.qa (A.S.O.)2 College of Medicine, Qatar University, Doha P.O. Box 2713, Qatar3 Department of Medical Education, Weill Cornell Medicine, Qatar Foundation, Doha P.O. Box 24144, Qatar;srd2003@qatar-med.cornell.edu4 Division of Microbiology, Department of Laboratory Medicine and Pathology, Hamad Medical Corporation,Doha P.O. Box 3050, Qatar; feltayeb1@hamad.qa (F.E.); eelmagboul@hamad.qa (E.B.I.)5 Department of Internal Medicine, University Health Truman Medical Centre, Kansas City, MO 64108, USA;mabm4@umsyste.edu6 Department of Community Medicine, Hamad Medical Corporation, Doha P.O. Box 3050, Qatar;jsuliman@hamad.qa7 Biomedical Research Centre, Qatar University, Doha P.O. Box 2713, Qatar8 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore;ychen114@e.ntu.edu.sg (Y.C.); clement_km_tsui@ncid.sg (C.K.M.T.)9 Infectious Diseases Research Laboratory, National Centre for Infectious Diseases, Singapore 308442, Singapore10 Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada11 Department of Microbiology and Immunology, Weill Cornell Medicine-Qatar, Doha 2713, Qatar;sis2013@qatar-med.cornell.edu (S.S.); als2026@qatar-med.cornell.edu (A.S.)* Correspondence: habdelhadi@hamad.qaAbstract: Antimicrobial resistance is a global healthcare threat with significant clinical and economicconsequences peaking at secondary and tertiary care hospitals where multidrug-resistant Gram-negative bacteria (MDR GNB) lead to poor outcomes. A prospective study was conducted betweenJanuary and December 2019 for all invasive bloodstream infections (BSIs) secondary to MDR GNBin Qatar identified during routine microbiological service to examine their clinical, microbiological,and genomic characteristics. Out of 3238 episodes of GNB BSIs, the prevalence of MDR GNB was13% (429/3238). The predominant MDR pathogens were Escherichia coli (62.7%), Klebsiella pneumoniae(20.4%), Salmonella species (6.6%), and Pseudomonas aeruginosa (5.3%), while out of 245 clinicallyevaluated patients, the majority were adult males, with the elderly constituting almost one-third ofthe cohort and with highest observed risk for prolonged hospital stays. The risk factors identifiedincluded multiple comorbidities, recent healthcare contact, previous antimicrobial therapy, andadmission to critical care. The in-hospital mortality rate was recorded at 25.7%, associated withmultiple comorbidities, admission to critical care, and the acquisition of MDR Pseudomonas aeruginosa.Resistant pathogens demonstrated high levels of antimicrobial resistance but noticeable susceptibilityto amikacin and carbapenems. Genomic analysis revealed that Escherichia coli ST131 and Salmonellaenterica ST1 were the predominant clones not observed with other pathogens.Keywords: antimicrobial resistance; Gram-negative bacteria; multidrug resistance; bacteremia;bloodstream infection; Qatar1. IntroductionThe escalating challenges of antimicrobial resistance (AMR) is a global public healthpriority with significant clinical and economic outcomes [1–3]. Over the coming decades,Antibiotics 2024, 13, 320. https://doi.org/10.3390/antibiotics13040320 https://www.mdpi.com/journal/antibioticsAntibiotics 2024, 13, 320 2 of 16evolving AMR is expected to create critical short- and long-term consequences that over-shadow the outcomes from all other acute as well as chronic diseases [4,5]. To anticipatethe forthcoming challenges, the scale of the problem has attracted noticeable commitmentand action plans from all aspects of healthcare, including public health, direct clinical careat all levels, specialized societies, governments, and policy-makers, as well as internationalorganizations such as the World Health Organization [6]. These joint efforts have beentranslated into a wider consensus to combat the problem through multiple comprehen-sive approaches, including global and regional surveillances strategies [6–8]. In frontlinehealthcare settings, the challenges of AMR peak in Gram-negative bacteria (GNB), sincethe pathogens display multiple resistance mechanisms leading to serious consequencesin terms of morbidity, mortality, limited therapeutic options, increased length of hospi-tal stay, and the increased cost of management [2,9]. Furthermore, GNB are among theforemost pathogens associated with both community- and healthcare-associated infections(HCAIs), while bloodstream infections (BSIs) constitute the ultimate clinical hazard directlylinked to secondary septicemia, septic shock, admission to critical care, and eventually pooroutcomes [10–12]. From primary infection sites, specific virulence factors in GNB allowthe pathogens to propagate into BSI through the triad of direct invasion of the affectedsites, overcoming the host’s defensive barriers, and survival following invasion of thebloodstream despite opposing immune defense mechanisms [13]. In secondary and tertiarycare, the acquisition of GNB infection is a real threat, facilitated by the three-way links ofspecific pathogen-related factors such as virulence and resistance, vulnerable hosts suchas patients with chronic and immunocompromised states, and the hazardous environ-ment, such as critical care settings that facilitate accumulating risks for the transmissionof HCAIs [14]. Moreover, the subsets of MDR GNB pathogens are more critical, sincethey are associated with poor clinical outcomes when compared with susceptible isolates,especially following delaying the initiation of appropriate antimicrobial therapy, as well asrepresenting a serious challenge for antimicrobial stewardship and infection control andprevention programs [12,14–17].In clinical practice, the distinction between susceptible and resistant bacterial isolatesis of paramount importance, since it aids in the initial clinical evaluation and in institutingappropriate therapy, as well as quantifying an assessment of the risks for their safe clin-ical management [18]. Consequently, most prominent specialized international societiesregularly advocate and update appropriate evaluations to direct management specificallyaimed at MDR pathogens [19,20].Despite the importance of the problem from global and local perspectives at alllevels, there is a paucity of data specifically from our region of MDR GNB manifesting asBSIs [21]. To bridge such gaps, experts advocate strengthening surveillance methods tocomprehend the scale of the problem and to evaluate its different local aspects, including themicrobiological and clinical characteristics [22]. The present study aimed to prospectivelyevaluate the epidemiology, clinical, and microbiological characteristics of bloodstreaminfections caused by MDR GNB from Qatar which started in 2019.2. Materials and Methods2.1. SettingsHamad Medical Corporation (HMC) is the main healthcare provider in the country,acting through 14 acute and specialized hospitals with a total capacity of almost 2500 bedsthat serve the country’s population of almost three million. In HMC, there is a nationalelectronic health information system that allows for the retrieval of data on patients andpathogens [23]. The microbiology division of the department of pathology and laboratorymedicine handles all specimens for microbiological identification, antimicrobial suscepti-bility tests (AST), and reporting through a major central facility and few peripherals. Thelaboratory is equipped with modern electronic and diagnostic equipment that complieswith international standards and receives regular inspections and accreditation [24].Antibiotics 2024, 13, 320 3 of 162.2. Epidemiology and Clinical DemographicsFor the study year of 2019, the electronic records of patients from the main generalhospital identified with positive BSI were reviewed to include the patients’ demographics,risk factors, evaluation, and management including the severity of the infection as well asthe microbiological and genomic characteristics. In total, 386 non-duplicate cases of BSIwere identified in the year 2019; out of these, clinical details and antibiotic susceptibilitytests were retrieved for 245 cases hosted in the central HMC database. The cascade of thestudy flow chart is outlined in Supplementary Figure S1.2.3. Bacterial Identification and Antimicrobial Susceptibility Testing (ASTs)All isolates were collected from positive blood culture specimens from all age groupsreceived at the central and peripheral microbiology laboratories across the HMC’s sites.Microbiological identification and ASTs were performed using automated MALDI-TOFspectrometry (Bruker Daltonics, Billerica, MA, USA) and BD Phoenix™ Microbiology Sys-tems (BD Diagnostics, Durham, NC, USA). Interpretation of the susceptibility results wasbased on the breakpoints of the Clinical Laboratory Standards Institute (CLSI), along withHMC’s internal institutional guidelines [25]. Consecutive BSIs were prospectively reportedto identify clinically relevant GNB, which were furtherly subclassified into MDR on thebasis of their resistance to at least one antimicrobial agent from three different antimicro-bial classes, as widely agreed, while ESBLs were identified with a MIC of >2 µg/mL forthird-generation cephalosporins and confirmed by double-disc diffusion methods [25,26].2.4. Molecular and Genomic Evaluation through WGS MethodsFor whole-genome sequencing, MDR-GNB BSIs with available AST data were rankedon the basis of their decreasing resistance against the total number of antibiotics tested, andthe top 100 resistant isolates were selected on the basis of budget constraints; for example,all carbapenem-resistant (CR) GNB were included. Genomic DNA was extracted using aDNeasy Blood and Tissue Kit (Qiagen, Germany), and the DNA libraries were sequencedon the Illumina NextSeq 550 platform using 2 × 150 bp PE at SeqCenter (Pittsburgh, PA,USA) [27]. The raw reads were assembled de novo using SPAdes v.3.9.0 implemented inshovill (https://github.com/tseemann/shovill (accessed on 1 March 2024)) [28,29]. Se-quence types, (ST), plasmid replicons, and AMR genes were predicted from the assembledcontigs using the multilocus sequence typing (MLST) (https://github.com/tseemann/mlst(accessed on 1 March 2024)), Plasmidfinder v2.1, and ResFinder v3.2 databases imple-mented in ABRicate v0.9 (https://github.com/tseemann/abricate (accessed on 1 March2024)), on the basis of >70% coverage and 90% sequence identity [30]. Previously unre-ported Klebsiella species ST were submitted to BIGSDB (https://bigsdb.pasteur.fr/klebsiella/(accessed on 1 March 2024)) for ST assignment.2.5. Statistical AnalysisAnalysis of the data was conducted using IBM-SPSS version 27.0 (Armonk, NY, USA).The samples’ characteristics were summarized using frequency and percentage distribu-tions, while Fisher’s exact and Chi-square tests were conducted to identify the bivariateassociations of the duration of hospital stay and in-hospital mortality. To examine for theinfluence of different variables on the outcomes, a multivariable regression model wasperformed using the variables of age, gender, pathogens, admission to critical care, andduration of hospital stay, and records of comorbidity scores were examined against the out-come of in-hospital mortality. Furthermore, collinearity was tested among the categoricalindependent variables using Chi-square and/or Fisher’s exact tests, with the estimates ofthe adjusted odds ratio (OR) and confidence intervals set at 95%. Covariates with p-valuesof ≤0.05 in the multivariable analysis were regarded as strong evidence for associations.Antibiotics 2024, 13, 320 4 of 163. ResultsDuring the year 2019, out 3238 episodes of Gram-negative bloodstream infections, 429fulfilled the criteria for multidrug resistance (MDR), with a prevalence of 13% (429/3238);of these, 386 were non-duplicates isolates representing monomicrobial infections in 95%of cases and polymicrobial infections in 5%. The key identified pathogens were E. coli(62.7%), Klebsiella species (20.4%), Salmonella species (6.6%), and P. aeruginosa (5.3%), whileothers were 5% (comprising Klebsiella species other than Klebsiella pneumoniae, Enterobactercloacae, Serratia marcescens, Bacteroides fragilis, Citrobacter freundii, Acinetobacter baumannii,and Proteus mirabilis) (Table 1). In the evaluation of 245 patients enrolled for the firstyear of the study, most patients were adults (98.4%) and males (61.6%), while the elderlyaged >65 years, who had the highest risk of prolonged hospital stays, constituted 36.6%(Table 1). The majority of patients had multiple comorbidities, dominated by diabetesmellitus (46.6%), coronary heart diseases (29.4%), neoplastic diseases (27.8%), and chronicand end-stage kidney diseases (26.6%), who were admitted to or in critical care settingsduring the study period in 73.8% of cases and were treated with >2 antimicrobials in morethan half of the cases (51.4%). Risk factors for the acquisition of invasive MDR includedprevious healthcare contact (67.8%) and previous antimicrobial exposure in the preceding90 days. The major sources of BSI were the urinary tract (45.5%), intrabdominal infections(19.6%), and the related central lines (10.2%), with an in-hospital mortality rate of 25.7%(Table 2). In almost 50% of the cohorts, the patients were exposed to different classesof antimicrobials as therapy before and during their hospital admission preceding theisolation of MDR GNB BSI. Following that, carbapenems and aminoglycosides were themain directed therapy for the treatment of MDR GNB BSI (Figure 1).Table 1. Frequency and percentage of multidrug-resistant invasive Gram-negative organisms. Theincidence of individual organisms includes both single (95%) and polymicrobial infections (5%)among the 386 non-duplicate cases of invasive MDR GNB infections identified in the year 2019.Organism N %Escherichia coli 249 62.7Klebsiella pneumoniae 81 20.4Salmonella Typhi 26 6.6Pseudomonas aeruginosa 21 5.3* Others 20 5Total 100* Klebsiella species other than Klebsiella pneumoniae, Enterobacter cloacae, Serratia marcescens, Bacteroides fragilis,Citrobacter freundii, Acinetobacter baumannii, and Proteus mirabilis.Table 2. Demographic profile of 245 patients with invasive multidrug resistant Gram-negativebacterial bloodstream infections collected during 2019.DemographicsTotalDuration of Hospital Stay p-ValueShort Stay Medium Stay Long StayN (%) (<30 Days)N (%)(30–90 Days)N (%)(90+ Days)N (%)Age Pediatric (<14 years) 4 (1.7) 3 (1.9) 0 (0.0) 1 (2.4) 0.121 aAdult (14–65 years) 147 (61.8) 99 (64.3) 29 (69.0) 19 (45.2)Geriatric (>65 years) 87 (36.6) 52 (33.8) 13 (31.0) 22 (52.4)Gender Male 151 (61.6) 93 (58.1) 33 (78.6) 25 (58.1) 0.047 bFemale 94 (38.4) 67 (41.9) 9 (21.4) 18 (41.9)ICU stay Present 180 (73.8) 131 (81.9) 21 (50.0) 28 (66.7) <0.001 bSource HAP c 6 (2.4) 4 (2.5) 0 (0.0) 2 (4.7) <0.001 aVAP d 8 (3.3) 1 (0.6) 4 (9.5) 3 (7.0)CAUTI e 11 (4.5) 4 (2.5) 4 (9.5) 3 (7.0)CLABSI f 21 (8.6) 3 (1.9) 10 (23.8) 8 (18.6)Other 199 (81.2) 148 (92.5) 24 (57.1) 27 (62.8)Antibiotics 2024, 13, 320 5 of 16Table 2. Cont.DemographicsTotalDuration of Hospital Stay p-ValueShort Stay Medium Stay Long StayN (%) (<30 Days)N (%)(30–90 Days)N (%)(90+ Days)N (%)Acquisition HCAI 89 (37.9) 29 (18.8) 28 (70.0) 32 (78.0) <0.001 bExtensive healthcare contact Present 166 (67.8) 86 (53.8) 39 (92.9) 41 (95.3) <0.001bReadmissionwithin 28 days Present 36 (14.8) 25 (15.8) 8 (19.0) 3 (7.0) 0.259bComorbidities DM 118 (48.6) 72 (45.6) 21 (50.0) 25 (58.1) 0.343 bHeart disease/heart failure/CHD 72 (29.4) 38 (23.8) 21 (50.0) 13 (30.2) 0.004 bChronic liver disease/biliary disease 27 (11.0) 18 (11.3) 3 (7.1) 6 (14.0) 0.572 aCKD/ESRD 65 (26.6) 36 (22.6) 11 (26.2) 18 (41.9) 0.040 bMalignancy 68 (27.8) 34 (21.3) 19 (45.2) 15 (34.9) 0.004 bPost-transplantation 9 (3.7) 4 (2.5) 1 (2.4) 4 (9.3) 0.115 aNeutropenic 25 (10.2) 10 (6.3) 9 (21.4) 6 (14.0) 0.009 aCystic fibrosis 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) N/ARenal stones/urinary tract abnormality 23 (9.4) 19 (11.9) 2 (4.8) 2 (4.7) 0.270 aChronic lung disease 24 (9.8) 15 (9.4) 5 (11.9) 4 (9.3) 0.818 aInvasive devices Central line 83 (34.0) 27 (17.0) 31 (73.8) 25 (58.1) <0.001 bFoly’s d 64 (26.3) 25 (15.7) 17 (41.5) 22 (51.2) <0.001 aNGT d 46 (18.9) 9 (5.7) 16 (38.1) 21 (48.8) <0.001 aDJ stent/PCN 5 (2.0) 4 (2.5) 1 (2.4) 0 (0.0) 0.829 aMechanical ventilator (intubated) 38 (15.5) 8 (5.0) 12 (28.6) 18 (41.9) <0.001 aTracheostomy tube 18 (7.3) 1 (0.6) 6 (14.3) 11 (25.6) <0.001 aPEG tube 5 (2.0) 1 (0.6) 0 (0.0) 4 (9.3) 0.007 aOther invasive device 28 (11.5) 17 (10.7) 6 (14.3) 5 (11.6) 0.385 aNumber ofantibiotics 0 8 (3.3) 8 (5.0) 0 (0.0) 0 (0.0) 0.023a1 11 (45.3) 79 (49.4) 16 (38.1) 16 (37.2)2+ 126 (51.4) 73 (45.6) 26 (61.9) 27 (62.8)Source ofbacteremia Present 206 (84.1) 131 (81.9) 37 (88.1) 38 (88.4) 0.444bIntraabdominal 48 (19.6) 36 (22.5) 8 (19) 4 (9.3) 0.154 bUrinary system 111 (45.5) 89 (56) 12 (28.6) 10 (23.3) <0.001 bSkin and soft tissue 22 (9.0) 5 (3.1) 6 (14.3) 11 (25.6) <0.001 aLine related 25 (10.2) 3 (1.9) 10 (24.4) 12 (27.9) <0.001 aCNS 2 (0.8) 0 (0) 0 (0) 2 (4.7) 0.060 aOther sites 7 (2.9) 3 (1.9) 2 (4.8) 2 (4.7) 0.305 aa p-value estimated using Fisher’s exact test; b p-value estimated using the Chi-square test. c HAP, hospital-acquired pneumonia; d VAP, ventilation-associated pneumonia; e CAUTI, catheter-associated urinary tractinfection; f CLABSI, central line-associated bloodstream infection; HCAIs, healthcare-associated infections; DM,diabetes mellitus; CHD, coronary heart disease; CKD, chronic kidney disease; ESRD, end-stage renal disease;NGT, nasogastric tube; PCN, percutaneous nephrostomy; PEG, percutaneous endoscopic gastrostomy; CNC,central nervous system.Microbiological evaluation of 245 isolates revealed a high level of resistance to peni-cillin’s (100%), cephalosporins (75–100%), and quinolones (41.7–68.6%) as well as moderateresistance to β-lactam β-lactamase inhibitors (BLBLIs) (11.3–15.7%) compared with highantimicrobial susceptibility to aminoglycosides and carbapenems (74.2–100%) (Table 3).Antibiotics 2024, 13, 320 6 of 16Antibiotics 2024, 13, x FOR PEER REVIEW 5 f 16 Figure 1. Graph showing the antibiotic treatment profile of 245 patients with multidrug-resistant invasive Gram-negative infections collected in the current study. For each antimicrobial class, the blue bars represent antimicrobials received before hospital admission and orange are those received during hospital admission before the isolation of the resistant pathogens, while the green are those received following the isolation of MDR GNB bacteremia. Carbapenems and aminoglycosides were the main classes used for targeted therapy. Table 3. Antimicrobial susceptibility test (AST) results of 245 invasive multidrug-resistant Gram-negative bacteria isolates collected during 2019. Antibiotic Interpreta-tion of Re-sistance Escherichia coli Klebsiella pneu-moniae/spp. Pseudomonas aeruginosa Salmonella enterica ssp./Salmonella sp. Enterobacter cloacae Serratia marcescens N (%) N (%) N (%) N (%) N (%) N (%) Amikacin S 159 (100) 54 (91.5) 11 (91.7) 0 (0) 3 (100) 2 (100) R 0 (0) 5 (8.5) 1 (8.3) 10 (100) 0 (0) 0 (0) I 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) Cefoxitin S 125 (78.5) 35 (59.3) 0 (0) R 23 (14.5) 21 (35.6) * NA 10 (100) * NA * NA I 11 (7) 3 (5.1) 0 (0) Ertapenem S 148 (93.1) 43 (72.9) 10 (100) 3 (100) 0 (0) R 7 (4.4) 15 (25.4) * NA 0 (0) 0 (0) 2 (100) I 4 (2.5) 1 (1.7) 0 (0) 0 (0) 0 (0) Imipenem S 152 (95.6) 43 (72.9) 0 (0) 10 (100) 3 (100) 0 (0) R 1 (0.6) 15 (25.4) 12 (100) 0 (0) 0 (0) 2 (100) I 6 (3.8) 1 (1.7) 0 (0) 0 (0) 0 (0) 0 (0) Meropenem S 158 (99.4) 45 (76.3) 0 (0) 10 (100) 3 (100) 0 (0) R 1 (0.6) 14 (23.7) 11 (91.7) 0 (0) 0 (0) 2 (100) I 0 (0) 0 (0) 1 (8.3) 0 (0) 0 (0) 0 (0) Nitrofurantoin S 149 (93.7) 17 (28.8) 10 (100) 0 (0) R 5 (3.1) 27 (45.8) * NA 0 (0) 3 (100) * NA I 5 (3.1) 15 (25.4) 0 (0) 0 (0) Tigecycline S 158 (99.4) 22 (37.3) 10 (100) 3 (100) 0 (0) R 1 (0.6) 15 (25.4) * NA 0 (0) 0 (0) 0 (0) I 0 (0) 22 (37.3) 0 (0) 0 (0) 2 (100) S 88 (55.3) 19 (32.2) 10 (100) Figure 1. raph sho ing the antibiotic treat ent profile of 245 patients with multidrug-resistantinvasive Gram-negative infections collected in the current study. For each antimicrobial class, theblue bars represent antimicrobials received before hospital admission and orange are those receivedduring hospital admission before the isolation of the resistant pathogens, while the green are thosereceived following the isolation of MDR GNB bacteremia. Carbapenems and aminoglycosides werethe main classes used for targeted therapy.Table 3. Antimicrobial susceptibility test (AST) results of 245 invasive multidrug-resistant Gram-n gat ve bacteri isolates collected during 2019.AntibioticInterpretationofResistanceEscherichiacoliKlebsiellapneumoniae/spp.PseudomonasaeruginosaSalmonella entericassp./Salmonella sp.EnterobactercloacaeSerratiamarcescensN (%) N (%) N (%) N (%) N (%) N (%)AmikacinS 159 (100) 54 (91.5) 11 (91.7) 0 (0) 3 (100) 2 (100)R 0 (0 5 (8.5) 1 (8.3) 10 (100) 0 (0) 0 (0)I 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)CefoxitinS 125 (78.5) 35 (59.3) 0 (0)R 23 (14.5) 21 (35.6) * NA 10 (100) * NA * NAI 11 (7) 3 (5.1) 0 (0)ErtapenemS 148 (93.1) 43 (72.9) 10 (100) 3 (100) 0 (0)R 7 (4.4) 15 (25.4) * NA 0 (0) 0 (0) 2 (100)I 4 (2.5) 1 (1.7) 0 (0) 0 (0) 0 (0)ImipenemS 152 (95.6) 43 (72.9) 0 (0) 10 (100) 3 (100) 0 (0)R 1 (0.6) 15 (25.4) 12 (100) 0 (0) 0 (0) 2 (100)I 6 (3.8) 1 (1.7) 0 (0) 0 (0) 0 (0) 0 (0)MeropenemS 158 (99.4) 45 (76.3) 0 (0) 10 (100) 3 (100) 0 (0)R 1 (0.6) 14 (23.7) 11 (91.7) 0 (0) 0 (0) 2 (100)I 0 (0) 0 (0) 1 (8.3) 0 (0) 0 (0) 0 (0)NitrofurantoinS 149 (93.7) 17 (28.8) 10 (100) 0 (0)R 5 (3.1) 27 (45.8) * NA 0 (0) 3 (100) * NAI 5 (3.1) 15 (25.4) 0 (0) 0 (0)Antibiotics 2024, 13, 320 7 of 16Table 3. Cont.AntibioticInterpretationofResistanceEscherichiacoliKlebsiellapneumoniae/spp.PseudomonasaeruginosaSalmonella entericassp./Salmonella sp.EnterobactercloacaeSerratiamarcescensN (%) N (%) N (%) N (%) N (%) N (%)TigecyclineS 158 (99.4) 22 (37.3) 10 (100) 3 (100) 0 (0)R 1 (0.6) 15 (25.4) * NA 0 (0) 0 (0) 0 (0)I 0 (0) 22 (37.3) 0 (0) 0 (0) 2 (100)AmoxicillinclavulanateS 88 (55.3) 19 (32.2) 10 (100)R 25 (15.7) 23 (39) * NA 0 (0) * NA * NAI 46 (28.9) 17 (28.8) 0 (0)AmpicillinS 0 (0) 0 (0)R 159 (100) * NA * NA 10 (100) * NA * NAI 0 (0) 0 (0)AztreonamS 3 (1.9) 3 (5.1) 0 (0) 0 (0) 0 (0) 2 (100)R 156 (98.1) 56 (94.9) 12 (100) 10 (100) 3 (100) 0 (0)I 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)CefazolinS 0 (0) 0 (0) 0 (0)R 159 (100) 59 (100) * NA 10 (100) * NA * NAI 0 (0) 0 (0) 0 (0)CefepimeS 2 (1.3) 0 (0) 0 (0) 0 (0) 1 (33.3) 1 (50)R 157 (98.7) 58 (98.3) 12 (100) 10 (100) 2 (66.7) 1 (50)I 0 (0) 1 (1.7) 0 (0) 0 (0) 0 (0) 0 (0)CeftazidimeS 3 (1.9) 2 (3.4) 1 (8.3) 0 (0) 0 (0) 2 (100)R 156 (98.1) 57 (96.6) 9 (75) 10 (100) 3 (100) 0 (0)I 0 (0) 0 (0) 2 (16.7) 0 (0) 0 (0) 0 (0)CeftriaxoneS 3 (1.9) 1 (1.7) 0 (0) 0 (0) 0 (0)R 156 (98.1) 57 (96.6) * NA 10 (100) 3 (100) 2 (100)I 0 (0) 1 (1.7) 0 (0) 0 (0) 0 (0)CefuroximeS 2 (1.3) 0 (0) 0 (0) 0 (0)R 157 (98.7) 59 (100) * NA 10 (100) * NA * NAI 0 (0) 0 (0) 0 (0) 0 (0)CephalothinS 0 (0) 0 (0) 0 (0) 0 (0)R 158 (99.4) 59 (100) * NA) 10 (100) * NA * NAI 1 (0.6) 0 (0) 0 (0) 0 (0)CiprofloxacinS 48 (30.2) 8 (15.4) 7 (58.3) 0 (0) 1 (50) 2 (100)R 109 (68.6) 42 (80.8) 4 (33.3) 9 (100) 1 (50) 0 (0)I 2 (1.2) 2 (3.8) 1 (8.3) 0 (0) 0 (0) 0 (0)GentamicinS 118 (74.2) 41 (69.5) 9 (75) 0 (0) 2 (66.7) 2 (100)R 40 (25.2) 18 (30.5) 1 (8.3) 10 (100) 1 (33.3) 0 (0)I 1 (0.6) 0 (0) 2 (16.7) 0 (0) 0 (0) 0 (0)LevofloxacinS 49 (30.8) 12 (30.8) 4 (33.3) 0 (0) 1 (100) 2 (100)R 109 (68.6) 25 (64.1) 5 (41.7) 7 (100) 0 (0) 0 (0)I 1 (0.6) 2 (5.1) 3 (25) 0 (0) 0 (0) 0 (0)Piperacillin–tazobactamS 136 (85.5) 26 (44.1) 1 (8.3) 0 (0) 3 (100) 0 (0)R 18 (11.3) 28 (47.5) 9 (75) 10 (100) 0 (0) 2 (100)I 5 (3.1) 5 (8.5) 2 (16.7) 0 (0) 0 (0) 0 (0)Trimethoprimsul-famethoxa-zoleS 53 (33.3) 11 (18.6) 0 (0) 3 (100) 2 (100)R 106 (66.7) 48 (81.4) * NA 10 (100) 0 (0) 0 (0)I 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)ColistinS 1 (100) 0 (0) 0 (0) 0 (0) 0 (0)R 0 (0) 2 (100) 0 (0) 0 (0) 1 (100) * NAI 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)PolymyxinS 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)R 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) * NAI 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)* NA: These organisms are intrinsically resistant to the designated antimicrobials, and their AST results should beinterpreted as categorically resistant or ineffective.The genomic characterization of the 100 selected isolates displaying the highest an-timicrobial resistance revealed that the most frequent pathogens were E. coli (n = 38) andAntibiotics 2024, 13, 320 8 of 16K. pneumoniae (n = 34), followed by P. aeruginosa (n = 12) and Salmonella enterica (n = 10).Isolates of E. coli belonged to 16 different sequence types (ST), and ST131 (n = 13) waspredominant, followed by ST167 (n = 4) and ST410 (n = 4). K. pneumoniae was representedby 26 different STs, and the most frequent one was ST16 (n = 3), with no specific clustering.Similarly, all 12 P. aeruginosa isolates belonged to different STs, in contrast to all Salmonellaenterica samples, which belonged to ST1 (n = 10). According to the genomic evaluation, E.coli and Salmonella enterica causing BSI appeared to exhibit a clonal propensity (Table 4). Todistinguish correlated factors associated with in-hospital mortality, we performed a regres-sion analysis, and identified multiple comorbidities (OR 17.38 CI: 2.4–123.8), admission tocritical care (OR 6.67, CI: 3–16.7), and infections secondary to MDR P. aeruginosa (OR 13.9,CI: 2.3–82.8) as having significant associations with poor outcomes (Table 5).Table 4. Regression analysis model identifying risk factors correlating with in-hospital mortality forinvasive MDR Gram-negative infections.DeathOR (95% CI) p-ValueAge Adult (14–65 years) Ref.Geriatric (>65 years) 2.01 (0.94–4.3) 0.073SexMale Ref.Female 1.23 (0.56–2.66) 0.606ICU stay No Ref.Yes 6.67 (3.03–16.67) <0.001Duration of stayShort stay (<30 days) Ref.Medium stay (30–90 days) 0.51 (0.18–1.49) 0.221Long stay (90+ days) 1.29 (0.48–3.52) 0.613Comorbidity score0 Ref.1 4.76 (0.69–32.59) 0.1122 9.62 (1.52–60.69) 0.0163 9.53 (1.37–66.56) 0.0234+ 17.38 (2.44–123.79) 0.004OrganismEscherichia coli Ref.Klebsiella 2.54 (1.1–5.88) 0.029Pseudomonas aeruginosa 13.94 (2.35–82.81) 0.004Table 5. Multilocus sequence typing results of 100 selected invasive multidrug resistant Gram-negative organisms collected in the current study.Organism ST N (%) Organism ST N (%)Escherichia coli 10 1 1 Klebsiella aerogenes ND 1 138 1 1 Klebsiella oxytoca 86 1 1131 13 13 194 1 1167 4 4224 1 1 Pseudomonas aeruginosa 16 1 1361 2 2 132 1 1405 1 1 234 1 1410 4 4 235 1 1450 1 1 244 1 1617 2 2 260 1 1648 2 2 500 1 11193 2 2 1417 1 12083 1 1 1992 1 12279 1 1 3045 1 12345 1 1 4117 1 1167-1LV 1 1 ND 1 1Antibiotics 2024, 13, 320 9 of 16Table 5. Cont.Organism ST N (%) Organism ST N (%)Klebsiella 13 1 116 3 3 Salmonella enterica 1 10 1017 1 129 2 2 Serratia marcescens ND 2 237 2 239 1 1 Enterobacter cloacae 513 1 145 2 254 1 1101 1 1147 1 1218 1 1231 1 1268 1 1307 2 2485 1 1690 1 1716 1 1870 1 1882 1 1987 1 12096 2 22944 1 13647 1 13702 2 24023 1 137-1LV 1 14. DiscussionThe impact of antimicrobial resistance (AMR) is a global healthcare challenge becauseof the direct clinical outcomes in terms of morbidity and mortality, as well as indirect se-quelae such as the economic and social consequences [2,3]. Amongst the spectrum of AMRpathogens, Gram-negative bacteria (GNB) represent a prominent aspect, since they possessunique resistance mechanisms allowing them to exhibit phenotypic multidrug resistance(MDR) profiles rendering them resistant to conventional and advanced antimicrobialswith limited therapeutic options [4,31]. Furthermore, the pathogens represent a leadingcause of community- and hospital-acquired infections (HAIs) such as urinary tract andintrabdominal infections, as well as HAIs such as pneumonia, urinary, and bloodstreaminfections (BSIs). Invasive GNB pathogens, particularly MDR BSIs, constitute a pivotalcategory, since they are almost always pathological, with frequent catastrophic clinicalconsequences such as septicemia, septic shock, and multiorgan dysfunctions, frequentlyleading to admission to critical care and with the highest mortality rate when comparedwith other pathogens [13,18,19].Our evaluation of MDR GNB bacteremia highlighted an overall prevalence of 13%of all invasive episodes. Although the overall prevalence of MDR GNB bacteremia issimilar to other regions, it is certainly higher for Enterobacterales [32]. The key top identifiedpathogens were E. coli, Klebsiella species, Salmonella species, P. aeruginosa, Serratia marcescens,and Enterobacter cloacae, constituting 98% of all MDR pathogens. While three out of the fourkey pathogens are commonly reported in different parts around the world, MDR Salmonellainfection is certainly a regional phenomenon reflecting imported travel-related infectionsfrom the neighboring Indian subcontinent and Africa, where resistant Salmonella infectionsare endemic and frequently reported [32,33]. This established link of imported MDRSalmonella bacteremia was observed in the country almost three decades ago, and hence ithas remained a substantial management challenge [32,33]. In multiple similar surveillancestudies, Salmonella BSI has been one of the leading causes of bacteremia in developingAntibiotics 2024, 13, 320 10 of 16countries, particularly in Asia and Africa [34]. Distinctively, although MDR Acinetobacterbaumanaii bacteremia has been reported as a leading entity in different global regions,including North America, South America, and Europe, it remains rare in our region [32–36].Despite the establishment of the clonal endemicity of Acinetobacter baumanaii in our clinicalsettings, as documented in a previous study almost a decade previously, there was a paucityof the related invasive diseases, with a predominance of those of respiratory origin, whichmight suggest the absence of virulent blood-invasive clones [37,38].Of note, although the study encompassed all age groups, it is noticeable that themajority of cases were adults (98%), pointing towards the observation that MDR GNBbacteremia was rare in the examined children, with supporting additional evidence thatthe majority of patients had multiple comorbidities, multiple previous encounters withhealthcare facilities, and exposure to previous antimicrobial therapy, conditions that areusually associated with older age groups. These risk factors for the acquisition MDR GNBincluding BSI have been reported before, pointing towards cumulative evolutionary shift ofGNB towards resistance [17,36,39,40]. Since the country’s demographics have a young maledistribution, the gender difference was probably not significant, but the high proportionof affected elderly patients was certainly related. The fact that the elderly (>65 years ofage) constituted more than one-third of the cohort is certainly significant, coupled withnoticeable prolonged hospital stays of >90 days [36]. Old-age and residence in long-termfacilities have been described before as being prime risk factors for the acquisition of MDRGNB bacteremia and are similarly associated with prolonged hospital stays as well as beingindependent risk factors of increased mortality [36,41–43].Regarding the risk factors for the acquisition of MDR BSI, patients with multiplecomorbidities, particularly immune suppression, and neoplastic diseases, have been linkedto infection with MDR GNB [44]. Likewise, the acquisition of invasive MDR GNB has beenassociated with previous exposure to antimicrobial therapy and previous admission tohealthcare facilities, leading to prolonged hospital stays [36,45]. It must be highlightedthat the observed in-hospital mortality rate for MDR GNB BSI was recorded as 25.7%,which is similar to that in other similar regional studies, although some recorded highmortality rates exceeding 50% that were linked to MDR K. pneumoniae and Acinetobacterbaumannii [46–48]. The predominance of MDR E. coli, coupled with a paucity of resistantAcinetobacter baumannii in our cohort probably contributed to the lower comparable mortal-ity rates. Additionally, examined risk factors correlating with mortality, namely age, gender,and duration of hospital stay, were not significant observed risk factors, while multipleand high comorbidity scores, admission to critical care, and acquisition of P. aeruginosa hadstrong associations.For the phenotypic review, the microbiological evaluation highlighted the prominentresistance (98–100%) of MDR GNB to all penicillin’s, monobactams such as aztreonam,and all classes of cephalosporins (except for cefoxitin), including fourth-generation agents,represented by cefepime. This was an expected finding, since the prime mechanism ofresistance in MDR GNB is the production of extended spectrum β-lactamases (ESBL)that inactivate almost all penicillin-based antimicrobials, including monobactams andcephalosporins [18,49,50]. Because carbapenems such as meropenem, imipenem, and er-tapenem are resistant to the inactivation of ESBL to the point of being considered the sinequa non for the management for ESBL-producing GNB, particularly invasive diseases,intriguingly, the results demonstrated noticeable overall differences as well as pathogen-specific activity profiles [51]. For example, the AST for the three highlighted carbapenemagents against E. coli was 99.4%, 95.6%, and 93.1%, respectively, while those for Klebsiellaspecies were 76.3%, 72.9%, and 72.9%, respectively. This can be partially explained by theprominent production of ESBL-resistant genes by E. coli when compared with Klebsiellaspecies, which tend to display more advanced resistance mechanisms, such as the geno-typic production of carbapenem-resistant genes (CRGs) that are capable of inactivatingcarbapenems [52,53]. Since the displayed results highlighted a high level of resistance inKlebsiella species against carbapenems, further evaluations revealed they were true CREs.Antibiotics 2024, 13, 320 11 of 16Nevertheless, the conspicuous resistance pattern of Klebsiella species compared with E. coliwas observed in other similar surveillance studies [52]. Moreover, as well as the productionof ESBL and CRGs conferring MDR, GNB also produce other non-enzymatic resistancemechanisms, such as porins and efflux pump mutations that impede antimicrobials’ entryand efflux into the targeted pathogens, leading to phenotypic resistance pattens. Since thereis a non-uniform susceptibility of different carbapenems to these mechanisms, most likelyit accounts for the inter-class variations [51,54]. Despite that, carbapenems were the mainselected therapeutic agents used for the management of invasive MDR GNB for the cohort.Comparatively, advanced BLBLIs represented by piperacillin–tazobactam demonstratedsuboptimal activity (85.5%) against MDR E. coli and 44.1% against Klebsiella, with pooractivity against MDR P. aeruginosa (8.3%). The historic position for piperacillin–tazobactamin treating MDR GNB bacteremia, particularly for Enterobacterales, was severely dentedwhen a large randomized clinical trial demonstrated that it was inferior to carbapenems,with increased mortality [55]. Despite concerns raised over the use of BLBLIs for thetreatment of invasive MDR GNB such as ESBL BSI, nevertheless, a collective analysisof retrospective clinical studies showed no observed differences, while ongoing clinicaltrials are still exploring this contentious concept [56,57]. Similarly, there were noticeableinter-class variations between the two main aminoglycosides, namely amikacin and gen-tamycin, as the former demonstrated wider AST activity against MDR GNB spanning E.coli (100%), Klebsiella species (91.5%), and P. aeruginosa (91.7%) compared with 74.2%, 69.5%,and 75%, respectively, for gentamycin. Despite the historic use of this antimicrobial classin clinical practice for almost 80 years, there is a paucity of data regarding comparativestudies between the different agents, particularly for MDR GNB, to guide clinical care, anarea that we recommend being explored further [58–61].In MDR GNB, the hallmark for resistance to aminoglycosides is enzymatic inactivationor modifications such as aminoglycoside-modifying enzymes (AMEs), which are readilyexpressed by many MDR GNB [59]. In the previous limited studies, amikacin’s ASTs wereusually higher than those of gentamycin against MDR GNB, despite the cautious calls forthe accurate interpretation of CLSI and EUCAST breakpoints for amikacins, especially dur-ing co-occurrence of AMEs with CRGs [62,63]. Additionally, Salmonella species, particularlyresistant strains, have poor permeability to aminoglycosides, reflected by the universalresistance in our cohort (100%) [64].It is certainly worth highlighting the high-level resistance of the MDR GNB in ourcohort to quinolones. For E. coli, identical resistance to ciprofloxacin and levofloxacin wasfound (68.6%), while for Klebsiella species, it was 80.8% and 64.1%, respectively. Quinolonesrepresent an attractive therapeutic alternative for GNB because of their unique mode ofaction, inhibiting DNA synthesis but hindered by the escalating resistance in MDR isolates,which started almost two decades ago [65]. This usually occurs because of the frequentco-transmission of plasmid-mediated quinolone-resistance genes (QRGs) that impede itsactivity [66]. In GNB bacteremia, quinolone resistance has been shown to be associatedwith MDR for related pathogens, as well as an independent risk factor for prolongedhospital stays [67]. This can be challenging during the management of invasive disease; forexample, although quinolones are classically associated with the management of Salmonellainfections, all the cohort’s isolates were resistant.From the review of the microbiological phenotypic characteristics, it must be high-lighted that certain pathogens possess intrinsic mechanisms of resistance that render thetested or used antimicrobials ineffective, such as the historic association between K. pneu-moniae and resistance to ampicillin, Enterobacter cloacae and Serratia marcescens havingresistance to most tested penicillin and cephalosporins, and the similar recognized spe-cific resistance of P. aeruginosa to ertapenem and tigecycline. Conversely, the paucity ofBSI caused by Acinetobacter baumanii, Enterobacter cloacae, and Serratia marcescens limitedaccurate comparisons of antimicrobial activity relating to these pathogens.Lastly, for MDR pathogens, the genomic evaluation revealed the predominance ofsequence types ST131 and ST167 for E. coli, and ST410 and ST1 for Salmonella species. E.Antibiotics 2024, 13, 320 12 of 16coli ST131 is a global MDR clone associated with both community-associated infectionsand HAIs, with a multitude of resistance genes, including ESBLs, particularly blaCXM-15,and quinolone resistance genes and virulence factors specifically associated with UTIsand bacteremia [68,69]. For E. coli, the results also reported ST167 and ST410, which areemerging global MDR bacterial clones associated with carbapenem resistance [70,71].Over the last decades, the sequential accumulation of multiple plasmid-mediatedresistance genes has conferred resistance almost to all penicillin, cephalosporins, andquinolones [72]. These observations are highlighted in our study, where the majority of BSIwere from urinary sources, and resistance to penicillin, cephalosporins, and quinoloneswere evidently pronounced for E. coli Similarly, the epidemic and resistant clone ofSalmonella ST1 is related to invasive enteric S. typhi, and is associated with spreadingMDR in different endemic regions around the world, including the Indian subcontinent,as reported in our cohort [73–75]. Intriguingly, despite previous studies from our institu-tion highlighting circulating endemic clones for hypervirulent and MDR Klebsiella speciessuch as ST383, genomic characterization of the invasive Klebsiella BSI did not reveal suchclustering patterns [76].Despite this national study being the largest and most comprehensive surveillance forMDR GNB bacteremia in the region and one of few globally, it has some limitations. For lo-gistic reasons, reported clinical and microbiological data were only available for two-thirdsof all identified bloodstream infections. However, the results are in line with other reportedbacteremia studies, which support their validity. Additionally, only about one-quarter ofthe isolates were processed for molecular studies, limited by budget constraints, althoughcomprehensive evaluations certainly would have added to our understanding of the inva-sive disease. Nevertheless, the study provides a new benchmark in epidemiology, clinicalprofiles, and antimicrobial characteristics, which will be a reference for the country and theregion for the important and well-defined condition of invasive bloodstream infection.In conclusion, this large prospective study of invasive MDR GNB associated with BSIfrom Qatar demonstrated significant multidrug resistance. Adults and elderly patients aremore likely to be affected by the invasive disease, usually those suffering from multipleclinical comorbidities linked to admission to critical care. The microbiological characteristicsand phenotypic profiles demonstrated that MDR E. coli, Klebsiella species, Salmonella species,and P. aeruginosa are the main pathogens with high-level resistance to most antimicrobialsand prime susceptibility to carbapenem and amikacin. Clonal clustering was observed forE. coli and Salmonella enterica, but not for the other pathogens.Supplementary Materials: The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/antibiotics13040320/s1, Figure S1: Study flow chart of MDR Gramnegative bacteria blood stream infections collected during 2019.Author Contributions: A.S., S.S., H.A.H., E.B.I. and A.S.O. are the study primary investigators forthe design and concepts. S.A.M.A., M.O.K.A. and J.S. collected antimicrobial and clinical data, F.E.and E.B.I. were responsible of collecting microbiological data including interpretation of antimicrobialsusceptibilities according to international and local guidelines. C.K.M.T. and Y.C. performed all thegenetic and bioinformatics interpretation of bacterial whole genome sequencing. S.R.D. performedstatistical analysis including the design of the regression model. H.A.H., C.K.M.T. and S.S. drafted theoriginal manuscript, which was subsequently reviewed and edited following the authors’ feedbackand contributions. All authors have read and agreed to the published version of the manuscript.Funding: This publication was made possible by an NPRP grant (NPRP12S-0219-190109) from theQatar National Research Fund (a member of Qatar Foundation). The submitted findings achievedherein are solely the responsibility of the author(s).Institutional Review Board Statement: The study and collaboration were approved by the indepen-dent research regulatory institutions of Qatar National Priority Research Fund, which is part of theQatar Foundation (QNPRF: NPRP12S-0219-190109), as well as the Medical Research Centre (MRC)of Hamad Medical Corporation (HMC), which abides by local and international research standards(MRC 01-20-252). The study also received approval from the ethical committee and institution reviewAntibiotics 2024, 13, 320 13 of 16board of HMC after demonstrating commitment towards observing the outlined standards for datamanagement and sharing, including limiting access to the nominated primary investigators, theanonymity of the data, and governance.Informed Consent Statement: Since the study was performed primarily on routine microbiologicalspecimens using only patient demographics and characteristics with no traceable identifiers, the IRBaccepted waving patients consent provided observing outlined regulations and data management.Data Availability Statement: Original research data are available upon reasonable request to theresearch team, after permission from regulatory institutions. The raw sequence reads of the bacterialWGS are available at NCBI under BioProject accession number PRJNA1005941.Acknowledgments: We would like to express our gratitude to all staff involved in the Divisionof Microbiology of the Department of Laboratory Medicine and Pathology at Hamad MedicalCorporation, spearheaded by Lolita Arisgado, who was pivotal in adhering to the study protocolthrough the timely processing of isolates, logging the details, and facilitating collaborative linksthroughout the study period. We would also like to thank our colleagues, in particular BernettLee and Eric Lim from the Centre for Biomedical Informatics, LKC School of Medicine, NanyangTechnological University, Singapore, for their support in terms of infrastructure and manpower. Thisresearch was supported in part by the computational resources and services provided by AdvancedResearch Computing at the University of British Columbia, Canada.Conflicts of Interest: The study group declares no conflicts of interest in relation to this academicresearch study.References1. Ahmad, M.; Khan, A.U. Global economic impact of antibiotic resistance: A review. J. Glob. Antimicrob. Resist. 2019, 19, 313–316.[CrossRef] [PubMed]2. Naylor, N.R.; Atun, R.; Zhu, N.; Kulasabanathan, K.; Silva, S.; Chatterjee, A.; Knight, G.M.; Robotham, J.V. Estimating the burdenof antimicrobial resistance: A systematic literature review. Antimicrob. Resist. Infect. Control 2018, 7, 58. [CrossRef] [PubMed]3. Global burden of bacterial antimicrobial resistance in 2019: A systematic analysis. Lancet 2022, 399, 629–655. [CrossRef] [PubMed]4. Bassetti, M.; Poulakou, G.; Ruppe, E.; Bouza, E.; Van Hal, S.J.; Brink, A. 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antimicrobial resistance
Gram-negative bacteria
multidrug resistance
bacteremia
bloodstream infection
Qatar
Epidemiology, Clinical, and Microbiological Characteristics of Multidrug-Resistant Gram-Negative Bacteremia in Qatar
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