Quality Assessment
Quality assessment was conducted independently using the AMSTAR 2 tool (11). Studies were categorised as having high, moderate, low and critically low confidence in the results based on the number of ‘critical domains’. Critical domains related to each review containing: an explicit statement that the methods were established a priori within a protocol; if a satisfactory technique for assessing the risk of bias was conducted and sufficiently discussed; if the meta-analysis used appropriate methods; and if publication bias (small study bias) was conducted.
Data analysis and synthesis
The random-effects meta-analysis model was used to statistically combine the measure of effects for those outcomes that were reported by more than one study, stratified by the three level of exposure (ACEIs/ARBs, ACEIs, ARBs). We conducted several sub-group analyses based on numerous variables including: whether the reported measure of effects was crude or adjusted, the study was peer-reviewed or not, and the study’s methodological quality as per the quality assessment. Furthermore, to assess the impact of ACEIs/ARBs among patients with hypertension (the most common indication for ACEIs/ARBs), we also conducted sub-group analysis based on whether the studies had included either patients with hypertension only or at least had hypertension as one of the comorbidities versus those studies which did not recorded the hypertension status of their study population. The combined pooled estimates were presented as odds ratios and 95%CI and graphically as forest plots. I2 statistic (12) was used to assess heterogeneity between the studies with I2 of 0% indicating lack of heterogeneity, whereas 25%, 50%, and 75% indicating low, moderate and high heterogeneity, respectively (12). Publication bias was assessed using funnel plots and Egger’s asymmetry test (13) only for those outcomes where >10 studies were included in the analysis as recommended by Cochrane guidelines (14). Furthermore, we evaluated the influence of individual reviews on the summary pooled estimate for each outcome by conducting influential analyses (15) whereby the pooled meta-analysis estimates for each outcome were computed by omitting one study at a time. Data were analysed using STATA 12.

Role of the Funding Source

None