Comparative efficacy and acceptability of different exercise patterns for reducing cardiovascular events in pre-diabetes: protocol for a systematic review and network meta-analysis of randomised controlled trials

Abstract

Introduction Exercise has been used to reverse dysglycaemic states in patients with pre-diabetes. Systematic reviews show that exercise is an effective way to reduce the incidence of diabetes, but there is conflicting evidence for reducing the occurrence of cardiovascular events. Therefore, we present a systematic review and network meta-analysis protocol designed to compare the effectiveness of different forms of exercise in reducing cardiovascular events and their tolerability in different populations.Methods and analysis We will include all randomised controlled trials and compare one exercise intervention to another. We will compare the following exercise patterns: standard endurance training, strength training, high-intensity interval training, mind-body exercise, and mixed strength and aerobic training. The primary outcomes are the occurrence of major cardiovascular events and the rate of patient attrition during the intervention. We will search major English and Chinese databases as well as trial registry websites for published and unpublished studies. All reference selection and data extraction will be conducted by at least two independent reviewers. We will conduct a random effects model to combine effect sizes and use the surface under the cumulative ranking curve and the mean ranks to rank the effectiveness of interventions. All data will be fitted at WinBUGS in a Bayesian framework and correlation graphs will be plotted using StataSE 14. We will also use the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework to evaluate the quality of evidence for the study results.Ethics and dissemination This study does not involve a population-based intervention, and therefore, does not require ethical approval. We will publish the findings of this systematic review in a peer-reviewed scientific journal, and the dataset will be made available free of charge. The completed review will be disseminated electronically in print and on social media, where appropriate.PROSPERO registration number CRD42023422737.