RESEARCH ARTICLE Open AccessEffectiveness of contrast-associated acutekidney injury prevention methods; asystematic review and network meta-analysisKhalid Ahmed1,2* , Terri McVeigh1, Raminta Cerneviciute1, Sara Mohamed1, Mohammad Tubassam2,Mohammad Karim3 and Stewart Walsh1,2,4AbstractBackground: Different methods to prevent contrast-associated acute kidney injury (CA-AKI) have been proposed inrecent years. We performed a mixed treatment comparison to evaluate and rank suggested interventions.Methods: A comprehensive Systematic review and a Bayesian network meta-analysis of randomised controlledtrials was completed. Results were tabulated and graphically represented using a network diagram; forest plots andleague tables were shown to rank treatments by the surface under the cumulative ranking curve (SUCRA). A stackedbar chart rankogram was generated. We performed main analysis with 200 RCTs and three analyses according tocontrast media and high or normal baseline renal profile that includes 173, 112 & 60 RCTs respectively.Results: We have included 200 trials with 42,273 patients and 44 interventions. The primary outcome was CI-AKI,defined as ≥25% relative increase or≥ 0.5 mg/dl increase from baseline creatinine one to 5 days post contrastexposure. The top ranked interventions through different analyses were Allopurinol, Prostaglandin E1 (PGE1) & Oxygen(0.9647, 0.7809 & 0.7527 in the main analysis). Comparatively, reference treatment intravenous hydration was rankedlower but better than Placebo (0.3124 VS 0.2694 in the main analysis).Conclusion: Multiple CA-AKI preventive interventions have been tested in RCTs. This network evaluates data for all theexplored options. The results suggest that some options (particularly allopurinol, PGE1 & Oxygen) deserve furtherevaluation in a larger well-designed RCTs.Keywords: Contrast induced acute kidney injury, Contrast nephropathy, Prevention methods, Contrast associatedacute kidney injuryBackgroundRationaleContrast Associated acute kidney injury (CA-AKI) alsoknown as Contrast-induced acute kidney injury (CI-AKI)previously known as contrast induced nephropathy(CIN) is the third leading cause of hospital-acquiredacute renal injury, accounting for 12% of cases [1]. It isdefined as an abrupt deterioration in renal functionfollowing exposure to contrast media (CM) in the ab-sence of other aetiological factors [2]. The absolute andrelative values used to define CI-AKI vary, but are mostcommonly quoted as a relative increase of > 25% or anabsolute increase of 0.5 mg/dL and ≥ 0.3 mg from base-line serum creatinine measurement within 1–3 (4–5 daysless frequently used) of contrast exposure [3–7]. InCI-AKI, the serum creatinine level begins to rise within24 h of contrast exposure, peaking after 72 h, andusually returning to baseline within 1–3 weeks [6].The proposed pathophysiology of CI-AKI is acute tubu-lar necrosis. The underlying mechanisms are thought tobe vasoconstriction, leading to cellular hypoxia, or direct* Correspondence: Khalidmd20@gmail.com1Lambe Institute for Translational Research, Discipline of Surgery NationalUniversity of Ireland, Galway, Republic of Ireland2Department of Vascular surgery, Galway University Hospital, Galway,Republic of IrelandFull list of author information is available at the end of the article© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Ahmed et al. BMC Nephrology (2018) 19:323 https://doi.org/10.1186/s12882-018-1113-0toxicity of contrast media to renal tubular cells [8, 9].Multiple therapies have been postulated to preventCI-AKI act by affecting these mechanisms or their meta-bolic mediators.There is ongoing discussion about the impact of newcontrast media on the size of the problem and the out-comes of prevention methods or even the existence ofthe problem, on the other side these conclusions werechallenged as coming only from retrospective studiesthat does not take in account patients factors or indica-tions for using contrast media in deferent cases with def-erent baseline renal profile [10, 11].In recent years, there have been many systematic re-views and meta-analyses for direct pair-wise compari-sons of individual interventions suggested for CI-AKIprevention. With so many options explored, it is difficultto determine the treatment options most likely to showbenefit in large-scale trials. Unlike conventionalmeta-analysis, Network facilitates simultaneous compari-son of indirect relationships between multiple interven-tions. The network can establish an estimate ofcomparative efficacy between two or more treatmentscompared to the same control intervention [12–14]. Weundertook a network-meta-analysis of preventive strat-egies for CA-AKI to determine the treatment most likelyto be beneficial based upon currently available evidence.MethodsWe conducted a systematic review and networkmeta-analysis in accordance with the PRISMA extensionfor Network Meta-Analyses [15].Protocol and registrationNo registered protocol.Eligibility criteriaWe consider all randomized controlled trials in whichpatients underwent a contrast-enhanced procedure withCI-AKI as a primary or secondary outcome. We evaluatestudies in which a prevention method was compared toplacebo, control or other intervention. Excluded fromthe analysis were other research designs, includingnon-randomised control trials; clinical trials; trials com-paring different doses of the same intervention and trialsusing re-randomization of the same sample (Crossoverdesign). For this review, we defined CI-AKI as an in-crease of more than or equal to 0.5 mg/dl and/or 25%increase in baseline serum Creatinine one to 5 days postcontrast exposure [3].Information sourcesWe searched for English-language trials in PubMed,Embase and Cochrane Central Register of ControlledTrials without any date restrictions. The final search wasundertaken on 25th April 2017.Search strategy and study selectionTwo authors (Ahmed, Walsh) searched Electronic data-bases using Mesh terms “contrast nephropathy”, “con-trast nephropathy prophylaxis”, “contrast nephropathyprevention”, with the Boolean operator “OR” as appro-priate. Titles and abstracts of identified studies wereassessed first, with full texts reviewed thereafter. Thestudy was included if the methodology fulfilled inclusioncriterion.Data collectionData were recorded concerning sample size, adverseevents, procedures performed, study inclusion and ex-clusion criteria, intervention type and dose, contrastmedia volume, CI-AKI definition, and contrast mediumtype and osmolality.The geometry of the networkA network diagram was created using NetMetaXL tool tographically represent the size of the trial and the numberof pairwise comparisons between interventions. The sizeof each intervention node is proportional to a number ofpatients included in the trial, while the thickness of inter-connecting lines is proportional to the number of pairwisecomparisons between any two interventions.Risk of biasThe Cochrane tool for risk of bias assessment (RevMan5.3) was used to assess bias within individual studies. Abias graph was generated to portray the risk of bias over-all across the included trials.Summary measuresOdds ratios with 95% confidence intervals were calcu-lated and presented in the form of Forest plots we gen-erated a league table, which ranks summary estimates inorder of the impact of the intervention on the primaryoutcome measure [10]. In the league table, interventionswere ranked from those with the highest effect to thelowest. A stacked bar chart rankogram was also createdto represent ranking probabilities and their uncertainty.Analysis methodsData with respect to events and number of patients inindividual trials were prepared and entered using Net-MetaXL [16], to facilitate completion of a Bayesian net-work meta-analysis using WinBUGS version 1.4.3 fromwithin Microsoft excel. We used the Markov ChainMonte Carlo method of parameter estimation to obtainposterior estimates of effects. Both vague prior and in-formative prior results were presented in the Forest Plot.Ahmed et al. BMC Nephrology (2018) 19:323 Page 2 of 18Zero cells were adjusted using an adjusted continuitycorrection factor accounting for potential differences insample size, centered around 0.5.As NetMetaXL is a relatively new tool, we run a separ-ate set of analyses for the same data on GeMTC R pack-age to validate our results with no noticeable differences.We performed analysis with both fixed effects modelsand random effects random-effect hierarchical models.For Bayesian computation; detailed statistical approachand diagnostics are provided in Additional file 1.Assessment of consistency, model fit, and convergenceIn NetMetaXL, ‘inconsistency plot’ was generated to fa-cilitate visual assessment of conflicts between direct andindirect evidence with limitation in our analysis due to asubstantial number of nodes on excel. Heterogeneity forvague and informative priors was provided within theforest plot results & Monte Carlo error < 5% of thestandard deviation (SD) used to assess convergence.For GeMTC R package Gelman-Rubin statistics usednumerically and graphically to evaluate convergence whiledeviance information criterion (DIC) was used for deter-mining model fits and the model with smaller DIC valuewas considered better.Additional analysesIn addition to the main analysis we performed three otheranalysis, the first excluding RCTs with any partial use ofhyperosmolar contrast media and in the other two RCTswere divided according to baseline renal profile.For each of the four analyses we performed sub-analysisexcluding studies with zero values as corresponding ef-fects estimates may be subject to numerical instability,generally over-estimate the effect, and that can be ob-served in the wide associated confidence intervals.ResultsStudy selectionA total of 32,596 study titles were identified in the initialliterature search, of which 200 fulfilled criteria for inclu-sion [4, 5, 7, 17–209] (Fig. 1). Some studies were excludedas some data were partially included or re-analyzed in aFig. 1 Flow DiagramAhmed et al. BMC Nephrology (2018) 19:323 Page 3 of 18follow-up study involved in our review [210–215]. A totalof 32,399 studies were excluded after remove duplicationthe most common reasons for exclusions after full exam-ination included observational methodology; different out-come measures, inadequate definition of CI-AKI; unclearevidence of randomization; old studies that did not com-ply with eligibility criteria for more than one reason [216–279]. The twelve studies published in a non-English lan-guage included those from centers in Germany [280, 281],China [282–287], Spain [288], France [289], Turkey [290]and Italy [291]. Eight further potentially suitable studieswere identified in abstract form only, but were excludedas no full-text article could be identified [292–299].Study characteristicsAdditional file 2 outlines individual study characteristics(study inclusion and exclusion criteria; procedure per-formed; baseline renal function; definition of CI-AKIused in the study; contrast medium volume and osmolal-ity). In total, 197studies fulfilled the inclusion criteria,including three which had multiple trial arms requiringseparate analyses (Yang 2014, Kumar 2014 & Chen2008). A total of 200 comparative analyses were there-fore included in our analyses. Coronary angiographyaccounted for 145 (72.5%) of the contrast-dependentprocedures were. Less frequently reported proceduresincluded contrast-enhanced CT imaging (n = 16, 8%),peripheral angiography with/without angioplasty andstenting (n = 3, 1.5%) endovascular aneurysm repairs(EVAR) (n = 1, 0.5. %). Multiple procedures were in-cluded in 35 studies (17.5%). Low osmolar contrastagents were used in 111 (55.5%), iso-osmolar agents in44 studies (22%), and hi-osmolar media in 3 studies(1.5%). Twenty-six (13%) trials permitted physician dis-cretion in the selection of contrast media, while a fur-ther 16 (8%) did not specify the contrast mediumutilized. More recent studies we observed better designwith an exclusion for patients using alternative CI-AKIprevention interventions from participation or stratifiedthose methods among arms of the trial.Network structureThe relationship and comparisons between includedstudies are demonstrated in the network diagram (Fig. 2).Forty-four interventions are included in this network(Table 1).Network geometryData from 42,273 patients recruited to 200 trials investi-gating 44 interventions were included in our analyses; asummary of network characteristics is provided in(Table 2). Nine hundred and forty-six pair-wise compari-sons were possible, of which 81 used data from directcomparisons in Additional file 3. The most commonlyinvestigated comparisons are between N-acetylcysteine(NAC) and placebo (36 studies, 8,202patients); andintravenous normal saline and intravenous sodium bicar-bonate (24 studies, 5,481patients). The interventionsmost commonly investigated were NAC, NaHCO3, Sta-tins, Intravenous Hydration (I.V), and placebo or con-trol. The characteristics of individual interventions areoutlined in Additional file 3.Risk of biasRisk of bias assessed by two authors (Khalid, Walsh). Incase of disagreement, other authors were consulted. Sum-mary for individual studies provided in Additional file 4while (Fig. 3) shows the risk of bias graph across all stud-ies. Most of the studies demonstrated unclear to low riskof bias while most of the high risk of bias were observedin attrition bias domain. As the outcome measure (CA-AKI) is dependent on laboratory results it seems reason-able to assume the risk of bias attributed to blinding ofoutcome assessment domain was low by default.Synthesis of resultsThe Renal Association, British Cardiovascular Interven-tion Society and the Royal College of Radiologists amongmany other medical bodies recommend using intravenousvolume expansion as a prevention method for CA-AKI[300]. Thus, we considered intravenous hydration clinic-ally the reference intervention in this analysis, in additionto the node size and the multiple arms within the networkwhich make it very good comparator.A forest plot was generated to demonstrate odds ratiogenerated from direct and indirect pair-wise compari-sons. Effect estimates, and confidence intervals were in-cluded for both vague and informative priors using arandom effects model. The overall heterogeneity for thevague prior was 0.54 (95% CI 0.41–0.69), while that forinformative prior was 0.498 (95% CI 0.366–0.6403). TheSUCRA (surface under the cumulative ranking curve)was utilized to generate a stacked bar chart rankogram(Fig. 4). A league table arranging summary of effectestimate, and ranking interventions according to impacton the outcome can be found in Additional file 3 inaddition to the Forest Plot, characteristics of interven-tions and comparisons and analysis specifications. Theprobabilities of being ranked for the best each interven-tion is summarized in (Table 3) while the numericalvalues follow the Rankogram results the list of interven-tions in the first column follow the league table hier-archy and a good example is Allopurinol which includedin 4 studies ranked best in both Rankogram (0.9647) andLeague Table while Silymarin was 3rd (0.7934) and lastrespectively and was included in one study.Ahmed et al. BMC Nephrology (2018) 19:323 Page 4 of 18Sensitivity analysisFlow chart for the main analyses and sub-analyses isincluded in Additional file 1. From the main analysis200 RCTs we run sub-analysis that includes 184RCTS in which we exclude all studies with zerovalues (n = 7). All figures and tables are included inAdditional file 3.The second analysis involved 173 RCTs after excludingstudies reporting any use of hyperosmolar contrastmedia, the sub-analysis without zero values RCTs in-clude 159 RCTS.Trials with high baseline renal profile were in analysis 3which includes 112 RCTs and sub-analysis for 105 RCTS.The 4th analysis includes 60 and 53 RCTs respectively.Analysis specifications, figures and tables provided inAdditional file 5, Additional file 6 and Additional file 7.When interpreting sub-analyses results in conventionaldirect pairwise comparisons the main effect results fromthe size of the excluded studies because there is no ex-clusion for interventions and they will always be presentat both sides of the forest plot. This impact the overalldiamond shape effect estimates size and confidenceFig. 2 Network Diagram: The size of each intervention node is proportional to the number of patients included in the trials, while the thicknessof interconnecting lines is proportional to the number of pairwise comparisons between any two interventionsAhmed et al. BMC Nephrology (2018) 19:323 Page 5 of 18interval will either shift towards one treatment or touch-ing the line of no effect indicating no superiority for anyintervention. This is different in Network Meta-analysisin which we can see changes in connections dynamic(Network Diagram) and interventions numbers repre-sented by node sizes and number of connections be-tween them both can be affected or totally removed bythe excluding studies. In the latter case the NetworkDiagram and characteristics of interventions and com-parisons provide detailed visualization to help comparethe main vs sub-analysis. In Additional file 3, Additionalfile 5, Additional file 6 and Additional file 7 we detailedall excluded studies, the affected interventions, NetworkDiagrams and the characteristics of the interventionsand comparisons.Assessment of consistencyAn ‘inconsistency plot’ (Fig. 5) was generated to assessinconsistency. Inconsistency in network meta-analysis issimilar to heterogeneity in conventional meta-analysis butconsistency concerns the relation between the treatmentswhereas heterogeneity concerns the variation betweentrials within a pairwise comparison between two treat-ments. Inconsistency is caused by imbalances in the distri-bution of effect modifiers in the direct and indirectevidence. Effects modifiers in this large sample includebut are not limited to patient factors, drug interactions,contrast media volume and type and renal function pre-intervention. Inevitably, some modifiers exist that cannotbe completely eliminated in large multi-treatment networkmeta-analysis, leading to some inconsistency, indicating aneed for careful interpretation of the results [301]. Theconsistency plot shows individual data points’ posteriormean deviance contributions for the consistency model(horizontal axis) and the unrelated mean effects model(vertical axis) along with the line of equality. In our analysis,the main limitation is excel inability to handle a largeamount of nodes. However, there should be a considerationTable 1 Interventions within Network DiagramNO Drug Abbreviation Patients1 I.V Hydration I.V 51362 Statins Sta 30403 Furosemide Fur 5544 NAC NAC 60955 Trimetazidine Tri 3526 NaHCO3 NaH 33937 PGE1 PGE 3048 MgSO4 MgS 629 Pentoxifylline Pen 43810 Placebo Pla 704411 Control Con 912012 Allopurinol All 20413 BNP BNP 74414 Probucol Pro 19815 α-tocopherol α-t 31216 γ-tocopherol γ-t 10217 Oxygen Oxy 34618 Amlodipine and Valsartan Aml 4519 K/Na citrate K/N 20320 Nicorandil Nic 29121 Ascorbic Acid Asc 55222 Alpha-Lipoic Acid Alp 13923 Oral Hydration Ora 25424 Nebivolol Neb 4025 Anisodamine Ani 19226 RIPC RIP 60827 Theophylline The 38428 Hypothermia Hyp 5829 Glutathione Glu 42130 MESNA MES 5131 ACEI AC 12932 Aminophylline Ami 4533 Iloprost Ilo 11834 Acetazolamide Ace 9435 ANP ANP 20236 Zinc Zin 1837 Dialysis Dia 29338 Fenoldopam Fe 33339 ERAs ER 7740 CCB CC 4241 Dopamine Do 4842 Mannitol Ma 3543 Cordyceps Co 8844 Silymarin Si 69ACEI Angiotensin Converting-Enzyme Inhibitor, ANP Atrial Natriuretic Peptide,BNP B-Type Natriuretic Peptide, CCB Calcium Channels Blockers, CI-AKI ContrastInduced Acute Kidney Injury, CIN Contrast Induced Nephropathy, ERAsEndothelin Receptor Antagonism, MESNA 2-Mercaptoethane Sulfonate Sodium,MgSo4 Magnesium Sulphate, NAC N-acetyl cysteine, NaHco3 SodiumBicarbonate, PGE1 Prostaglandin E1, RIPC Remote Ischemic PreconditioningTable 2 Network CharacteristicsCharacteristic NumberNumber of Interventions 44Number of Studies 200Total Number of Patients in Network 42,273Total Number of Events in Network 4602Total Possible Pairwise Comparisons 946Total Number Pairwise Comparisons with Direct Data 81Number of Two-arm Studies 179Number of Multi-Arms Studies 21Number of Studies with No Zero Events 184Number of Studies With At Least One Zero Event 16Number of Studies with All Zero Events 2Ahmed et al. BMC Nephrology (2018) 19:323 Page 6 of 18Fig. 3 Risk of Bias GraphFig. 4 Rankogram: ranking the interventions for the probability of being the best, the interventions are colour coded; the first column representsthe chance of being first best and 2nd column is the chance of being 2nd best and so on. i.e. the first column represent the chance of being firstbest cmparing all interventions out of100% and the second represent the chance of being second best out of 100% up to last column in thiscase number 44 (nuber of interventions); the overall ranking for each treatment is the sum of scores through out the 44 compasrisons. Theoverall numerical value is presented in Table 3Ahmed et al. BMC Nephrology (2018) 19:323 Page 7 of 18of individual pairwise comparisons effect estimates gener-ated within the forest plot.In GeMTC R analyses I2 statistics and DIC was muchsmaller for Random effect indicating less heterogeneitycompared with a fixed effect which is expected to pro-vide the nature of the network. Detailed scores are pre-sented in Additional file 1 while Gelman and Rubin’sconvergence diagnostics were added to correspondedanalyses in Additional file 3, Additional file 5, Additionalfile 6 and Additional file 7.In general, the main analysis reviled some interesting re-sults with Allopurinol, Prostaglandin E1 (PGE1) & Oxygenwere ranked high with good both statistical and clinicaloutcomes in relatively fewer number of studies comparingwith other interventions studied in larger number of RCTse.g. NAC, Statins, Hydration, NaHco3 and RIPC. The re-sults were stable throughout different sub analysis consid-ering the changes in network diagram being affected byexcluded studies in all 7 networks. The model fitting andthe consistency within the network was good consideringthe large size and it is understandable that it was better fit-ted in the 7 sub-groups analysis specially after excludingzero values studies. It is very important here to rememberin network ranking is the probability of being the bestwithin the interventions and we need to look at the forestplot for each comparison.DiscussionSummary of evidenceThis is a systematic review and network meta-analysis(multi-treatment comparison) of studies investigatingmethods for the prevention of contrast-induced nephrop-athy. We identified 200 eligible trials, of which 3 had 2different arms and thus analysed separately. Data from atotal of 42,273 patients undergoing 44 different interven-tions were included. Intravenous hydration (Nacl) wasused as the reference treatment as there is a consensussupported by evidence accepting it as a method of preven-tion with no clear superiority for other I.V fluids [81]. inour network it was also included in many multiple armsTable 3 Interventions ranking the treatments names columnfollow the league table (which arranges the presentation ofsummary estimates by ranking the treatments in order of mostpronounced impact on the outcome under consideration) thenumerical values represents the cumulative results of theprobability of being best in which the highest score is 1 or100% (see Rankogram)Treatment SUCRA Treatment SUCRAAllopurinol 0.9647 NaHCO3 0.3419MESNA 0.9427 Pentoxifylline 0.3391PGE1 0.7809 I.V Hydration 0.3124α-tocopherol 0.7614 Placebo 0.2694Oxygen 0.7527 Oral Hydration 0.2517K/Na citrate 0.7469 Hypothermia 0.2021Trimetazidine 0.7151 Control 0.1658Probucol 0.7042 Amlodipine and Valsartan 0.05485γ-tocopherol 0.689 ACEI 0.5783BNP 0.6767 Aminophylline 0.6593Anisodamine 0.6594 Iloprost 0.7481Nicorandil 0.6442 Acetazolamide 0.6242Theophylline 0.629 ANP 0.3291RIPC 0.5692 Zinc 0.198Statins 0.5497 Dialysis 0.4319MgSO4 0.5177 Fenoldopam 0.2296NAC 0.4592 ERAs 0.06734Nebivolol 0.4543 CCB 0.7249Ascorbic Acid 0.4433 Dopamine 0.1916Alpha-Lipoic Acid 0.4322 Mannitol 0.1905Furosemide 0.4027 Cordyceps 0.4459Glutathione 0.3554 Silymarin 0.7934Analysis Random Effects (Vague)Fig. 5 Inconsistency Plot: Inconsistency is similar to heterogeneity in conventional meta-analysis, but consistency concerns the relation betweenthe direct and indirect evidence. The consistency plot shows individual data points’ posterior mean deviance contributions for the consistencymodel (horizontal axis) and the unrelated mean effects model (vertical axis) along with the line of equalityAhmed et al. BMC Nephrology (2018) 19:323 Page 8 of 18RCTs which make it statistically a very good comparator.While only randomized control trials were included, de-fining the outcome and inclusion criteria, help tominimize the number of effect modifiers at play in differ-ent studies, thus minimising inconsistency. However, theassumption of homogeneity should be accepted with cau-tion in light of the large numbers of trials and patientsincluded.It is very important for readers more familiar withgeneral probability measure in which the value one isassigned to the entire probability space to recognizethat SUCRA use posterior probabilities for each treat-ment to be among the n - best options (cumulativeprobabilities) thus the sum add to > 1. The word bestreferred to the number of times that an interventionranks first out of the total number of random sam-ples [14] In Rankogram the first column representthe chance of being first best out of100% and the sec-ond represent the chance of being second best up tolast column; the overall ranking for each treatment isthe sum and that the reason each treatment probabil-ity is calculated out of 100%.We can generally categorize the 44 ranked interven-tions in groups. The first group is high ranked interven-tions with relatively fewer number of studies and thisgroup is mainly for further research consideration des-pite good design RCTs, good clinical outcomes, and ourconscious effort to eliminate the effect of small node ef-fect on the network and the fact we accommodate andaccounted for the different in interventions size whencalculating the probability but we cannot ignore that thismay still play in favour of small studies and we thinkthey deserve another look with larger well-designed tri-als, this group includes mainly Allopurinol, Prostaglan-din E1 (PGE1) & Oxygen; Allopurinol a xanthineoxidase Inhibitor used for treatment of gout and man-agement of hyperuricemia associated with chemotherapyand was assessed in 4 trials with 204 patients with recentpublished evidence suggesting some benefits [302] whilePGE1 in 4 trails with total 304 patients. InterestinglyOxygen was highly ranked before and after exclusion ofzero events studies and the total number of patients was346 in 2 studies.The scorned group is the middle group which includedin decent number of studies and the interventions in thisgroup with safe and or well tested profile can be used inpatient care at the same time continuously evaluatedand this group can include RIPC, Statins (which usuallyin use specially by cardiac and vascular patients), NAC,NaHco3, I.V hydration, Oral hydration and hypothermia.This group needed the physician to consult his localguidelines after evaluating each patient individually andsome interventions like hypothermia is not applicablefor all patients.The sub-analyses in our network for was performedafter excluding studies with zero events to eliminate favor-able effect profile. It produced better statistical results andhelped compare the results without the interventions in-volved in a small number of trials.Research & Clinical impactFor health care providers, the results of this meta-analysisdo not suggest changes to current clinical practice. Theprevention methods assessed in large studies should beevaluated on a case-by-case basis, bearing in mind the co-morbidities, clinical needs and prior risk factors of the in-dividual patient with special consideration to national andlocal guidelines. Interventions with safe profile and sup-portive evidence from direct pair-wise meta-analysis canbe considered as additional or second-line therapies forCA-AKI prevention. For clinical researchers, the highly-ranked treatments with relatively small number of trialsmerit further examonation in larger RCTs.LimitationsOne limitation of this meta-analysis is the exclusion ofnon-English language studies (n = 12). The inclusion ofthese studies may add to the supportive evidence for theuse of some interventions, although the effect size ofthese trials is likely to be minimal in light of the samplesizes in question. Another limitation is the difference incontrast media used which may affect the outcomes; weexcluded studies that used hyperosmolar contrast mediato minimise this effect with some evidence suggestingsimilar CIN incidence for iso and low-osmolar CM incoronary angiography patients [303]. In large Network,another consideration is our inability to account forother possible effect modifiers, and our assumptions re-garding homogeneity and similarity across a large num-ber of studies thus it is important to look at eachintervention ranking through the multiple analyses pro-vided in the supplemnts.While preparing this network meta-analysis a pairwisemeta-analysis was published .comparing N-acetylcysteine,sodium bicarbonate, statins and ascorbic acid for CA-AKIreduction [304]. The data was obtained from controlledtrials that used intravenous (IV) or intra-arterial contrast.The results of statins plus I.V saline vs I.V saline showclinically but not statistically significant difference. Whencomparing Sodium bicarbonate to I.V saline it was clinic-ally better, but again the difference was not statistically sig-nificant. However Ascorbic acid was better both clinicallyand statistically vs I.V saline and show no such differencewhen compared with NAC. A similar result can be ob-served in our ranking table with 0.5497, 0.4433, 0.3419and 0.3124 probability of being rank for statins, ascorbicacid, Sodium bicarbonate and I.V saline consequently. Al-though direct comparisons results were provided withinAhmed et al. BMC Nephrology (2018) 19:323 Page 9 of 18forest plot in our network, we think the results from pair-wise reviews is important; the nature of conventionalmeta-analysis prevent utilization of multiple arms trialsand creating indirect comparison but it can be used tolook at sections of more comprehensive network-meta-analysis in addition to the fact that It is more flexible interms of subgroup analysis and thus assessment of effectsmodifiers e.g. type of contrast media in this case.ConclusionThis systematic review and network meta-analysis pro-vide a comprehensive analysis of currently utilized CA-AKI prevention interventions. Results arising from thisnetwork identified some highly-ranked interventionsthroughout analyses and sub-analyses (e.g., Allopurinol,PGE1 & Oxygen) which were included in small numberof trials and merit further examination on a larger scalein the context of a well-designed RCTs.Additional filesAdditional file 1: Analysis flow chart and statistical approach. (DOCX 125 kb)Additional file 2: Studies characteristics. (DOCX 889 kb)Additional file 3: Main Analysis 200–184 RCTs. (DOCX 46108 kb)Additional file 4: Risk of Bias Table. (DOCX 1056 kb)Additional file 5: Excluding hyperosmolar 173–159 RCTs. (DOCX 41962 kb)Additional file 6: High Baseline Renal Profile 112–105 RCTs. (DOCX 32278 kb)Additional file 7: Normal Baseline Renal Profile 60–53 RCTs. (DOCX 16081 kb)AbbreviationsACEI: Angiotensin Converting-Enzyme Inhibitor; ANP: Atrial NatriureticPeptide; BNP: B-Type Natriuretic Peptide; CCB: Calcium Channels Blockers; CI-AKI: Contrast Induced Acute Kidney Injury; CIN: Contrast InducedNephropathy; CM: Contrast Media; ERAs: Endothelin Receptor Antagonism;MESNA: 2-Mercaptoethane Sulfonate Sodium; MgSo4: Magnesium Sulphate;NAC: N-acetyl cysteine; NaHco3: Sodium Bicarbonate; PGE1: Prostaglandin E1;RCT: Randomise Control Trails; RIPC: Remote Ischemic PreconditioningAcknowledgementsWe acknowledge Ms. Geraldine Curtin and the staff in the James Hardimanlibrary, NUI Galway, for their kind assistance in acquiring relevant papers andInformation.FundingThis research was funded by the National University of Ireland Galway.Availability of data and materialsN/A (2ndry data from published studies).Authors’ contributionsKA: Study design, Literature search, figures, data collection, data Analysis, datainterpretation and writing. TM: Critical appraisal, review and edit. RC FiguresEditing: SM Figures Editing. MT Critical appraisal, review and edit. MKMethodology, statistical data analysis, data interpretation, review and edit.Professor SW: Methodology, literature search, data interpretation Criticalappraisal, review, and edit. All authors read and approved the final manuscript.Ethics approval and consent to participateN/A.Consent for publicationN/A.Competing interestsThe authors declare that they have no competing interests.Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in publishedmaps and institutional affiliations.Author details1Lambe Institute for Translational Research, Discipline of Surgery NationalUniversity of Ireland, Galway, Republic of Ireland. 2Department of Vascularsurgery, Galway University Hospital, Galway, Republic of Ireland. 3School ofPopulation and Public Health, University of British Columbia, Scientist /Biostatistician, Centre for Health Evaluation and Outcome Sciences (CHEOS),St. Paul’s Hospital, Vancouver, Canada. 4HRB Clinical Research Facility Galway,Galway, Republic of Ireland.Received: 13 November 2017 Accepted: 22 October 2018References1. Mohammed NM, Mahfouz A, Achkar K, Rafie IM, Hajar R. Contrast-inducednephropathy. 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