Long-term Effect of Lifestyle Interventions on the Cardiovascular and All-Cause Mortality of Subjects With Prediabetes and Type 2 Diabetes: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Lifestyle interventions improve the metabolic control of individuals with hyperglycemia. PURPOSE: We aimed to determine the effect of lifestyle interventions on cardiovascular and all-cause mortality in this population. DATA SOURCES: Searches were made through MEDLINE, Cochrane CENTRAL, Embase, and Web of Science (no date/language restriction, until 15 May 2022). STUDY SELECTION: We included randomized clinical trials (RCTs) of subjects with prediabetes and type 2 diabetes, comparing intensive lifestyle interventions with usual care, with a minimum of 2 years of active intervention. DATA EXTRACTION: Data from the 11 RCTs selected were extracted in duplicate. A frequentist and arm-based meta-analysis was performed with random-effects models to estimate relative risk (RR) for mortality, and heterogeneity was assessed through I2 metrics. A generalized linear mixed model (GLMM) was used to confirm the findings. DATA SYNTHESIS: Lifestyle interventions were not superior to usual care in reducing cardiovascular (RR 0.99; 95% CI 0.79-1.23) or all-cause (RR 0.93; 95% CI 0.85-1.03) mortality. Subgroup, sensitivity, and meta-regression analyses showed no influence of type of intervention, mean follow-up, age, glycemic status, geographical location, risk of bias, or weight change. All of these results were confirmed with the GLMM. Most studies had a low risk of bias according to the RoB 2.0 tool and the certainty of evidence was moderate for both outcomes. LIMITATIONS: Most studies had a low risk of bias according to the RoB 2.0 tool, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach resulted in moderate certainty of evidence for both outcomes. Differences in lifestyle programs and in usual care between the studies should be considered in the interpretation of our results. CONCLUSIONS: Intensive lifestyle interventions implemented so far did not show superiority to usual care in reducing cardiovascular or all-cause mortality for subjects with prediabetes and type 2 diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.008 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".