Data Synthesis and Analysis
For each study outcome that was reported by more than one study, the results from individual studies were combined statistically using the random-effects meta-analysis model, stratified by the level of exposure (ACEIs/ARBs, ACEIs, ARBs); whereas for outcomes which were reported by only one study, narrative synthesis was used. For studies which did not report the summary statistics and measure of effects, we firstly used the reported primary statistics (number of patients with/without the outcomes in both exposed/unexposed group) to calculate the corresponding measure of effects (Odds ratios) and their 95% confidence interval (35), and subsequently used these measure of effects in the random-effects meta-analysis. Several sub-group analyses were also undertaken to explore the effect of potential confounders on the robustness and sensitivity of combined pooled estimates and included sub-group analyses based on whether the reported measure of effects was crude or adjusted, the study was peer-reviewed or not, the study’s methodological quality as per the risk of bias assessment was performed as well as the continent where the study was conducted. Meta-analyses pooled estimated were presented as odds ratios and 95%CI and graphically as forest plots. Heterogeneity between the studies was evaluated using I2 statistic (36), indicating whether variability is more likely due to study heterogeneity or chance. Negative I2 values were set to zero, hence I2 values ranged between 0%-100% with 0% indicating lack of heterogeneity, whereas 25%, 50%, and 75% indicating low, moderate and high heterogeneity, respectively (36). Data were analysed using STATA 12.

Role of the Funding Source

None