Acute Kidney Injury after Coronary Artery Bypass Graft Surgery: The heterogeneity of the Available Real-World Data Through a Meta-analysis (Journal of Statistics on Health Decision, 2022)
Introduction:Meta-analysis is the method to pool data from studies that report the same event in a comparable sample and, thus, summarize information from different populations. However, data extraction is limited to the information provided in the included studies. Frequently, individual patient information is not available, hence, real world data access is limited.Individual patient data (IPD) meta-analysis in a research area like health sciences constitutes the ideal method to analyse real world data, assuming a high level of evidence. (1) This method is based on a collaboration network in which variables can be merged among datasets once a single definition is determined reducing methodological heterogeneity. The use of IPD for meta-analysis has advantages, (allows adjustment for confounding factors), and limitations (obtaining individual patient data knowing that data collection and management are often unclear). (1, 2) To tackle high heterogeneity in a study-level meta-analysis, sensitivity analyses are recommended. Leave-one-out analysis is an option that evaluates the cumulative effect of each study by excluding one at a time, portraying its influence in the overall result (3).Considering the lack of long-term data on postoperative acute kidney injury (AKI) in coronary artery bypass grafting surgery (CABG) patients, paired with the expected study heterogeneity, we intend to summarize evidence regarding its effect on early and long-term survival, evaluate heterogeneity and perform sensitivity analysis. Methods:Systematic searches were performed in MEDLINE and ISI Web of Science, restricted by date of publication (January 1960–April 2021). Inclusion criteria comprised observational studies reporting incidence of postoperative AKI in adult patients, submitted to isolated CABG with at least 1-year of follow-up and survival estimates.Analyses were performed using Review Manager 5.4. and R environment. Random effects models were used to compute pooled HR and OR (95% CI), through generic inverse variance method and Mantel-Haenszel method or generalized linear mixed-effects model and logit-transformed proportions of AKI were used for analysis of prevalence data. Heterogeneity was defined using I2 statistics and was considered low (75%) (4). Between-study heterogeneity was studied using sensitivity analyses, namely, leave-one-out evaluations (metagen (meta R package)). Early and late survival were evaluated through this sensitivity analysis and were present according to each study impact on both effect size estimates and observed I2. (5) Results:Thirteen retrospective observational studies comprising 63209 patients were included, (N AKI=11366, N non-AKI=51843). AKI incidence ranged 0.6%-54% with a pooled incidence of 16%.Postoperative AKI was associated with higher early mortality (OR (95%CI): 7.59 (3.18-18.15), p
Keywords: Acute kidney injury [Mesh]; Coronary artery bypass [Mesh]; Data Analysis [Mesh]; Heterogeneity; Mortality [Mesh]; Meta-analysis [Mesh]; Population Characteristics [Mesh]; Research Design [Mesh]