Fine wine or sour grapes? A systematic review and meta-analysis of the impact of red wine polyphenols on vascular health

Fig. 1. PRISMA flow diagram showing the search, screening and selection process, including eligible study numbers for both qualitative and quantitative synthesis

Fig. 2. Forest plot showing mean difference and 95% confidence intervals for the impact of chronic red wine polyphenol supplementation compared to placebo-controls on systolic blood pressure in humans, with subgroup analysis based on the health status of the included cohort. Horizontal lines indicate the 95% confidence interval. Shaded diamond shows the calculated subgroup and overall mean difference alongside the results of the random effect model for each group

Fig. 3. Forest plot showing mean difference and 95% confidence intervals for the impact of chronic red wine polyphenol supplementation compared to placebo-controls on systolic blood pressure in humans, with subgroup analysis comparing studies administering resveratrol compared to all other red wine polyphenols. Horizontal lines indicate the 95% confidence interval. Shaded diamond shows the calculated subgroup and overall mean difference alongside the results of the random effect model for each group

Fig. 4. Forest plot showing mean difference and 95% confidence intervals for the impact of chronic red wine polyphenol supplementation compared to placebo-controls on diastolic blood pressure in humans, with subgroup analysis based on the health status of the included cohort. Horizontal lines indicate the 95% confidence interval; shaded diamond shows the calculated subgroup and overall mean difference alongside the results of the random effect model for each group

Fig. 5. Sensitivity and influence analysis computed using the Metafor meta-analysis package for human studies included in meta-analysis for systolic blood pressure, showing the externally standardised residuals (rstudent), standard deviation fits (DFFIT), Cook’s distances (cook.d), covariance ratios (cov.r), leave-on-out estimates of the amount heterogeneity (tau2.del), leave-one-out values of the test statistics for heterogeneity (QE.del), hat values (hat) and weight weight). Studies presented in red are considered influential and should be inspected on a case-by-case ratio to determine whether they may be considered an outlier

Fig. 6. Sensitivity and influence analysis computed using the Metafor meta-analysis package for human studies included in meta-analysis for diastolic blood pressure, showing the externally standardised residuals (rstudent), standard deviation fits (DFFIT), Cook’s distances (cook.d), covariance ratios (cov.r), leave-on-out estimates of the amount heterogeneity (tau2.del), leave-one-out values of the test statistics for heterogeneity (QE.del), hat values (hat) and weight (weight). Studies presented in red are considered influential and should be inspected on a case-by-case ratio to determine whether they may be considered an outlier