Scholarlink

Background <p>Glycemic variability (GV) reflects glucose fluctuations, and increased GV is associated with adverse cardiovascular outcomes. We systematically evaluated the association between GV, measured by the mean amplitude of glycemic excursions (MAGE) and standard deviation (SD), and cardiovascular risk in patients with pre-existing cardiovascular disease (CVD).</p> Materials and methods <p>We searched PubMed, Embase, Scopus, Web of Science, and CENTRAL through May 2025 for studies on GV and cardiovascular outcomes in patients with established cardiovascular disease. Random-effects models with Knapp-Hartung adjustment were used to pool the risk ratios (RRs) and 95% confidence intervals (CIs). Subgroup, sensitivity, and meta-regression analyses were used to explore heterogeneity. The risk of bias was assessed using the ROBINS-I tool.</p> Results <p>Seventeen studies comprising 6,096 patients were included. In the categorical analysis, higher MAGE (RR: 2.18; 95% CI: 1.70, 2.80; I² = 15.6%) and SD (RR: 1.94; 95% CI: 1.32, 2.87; I² = 55.9%) were associated with increased risk of major adverse cardiovascular events (MACE). Continuous MAGE was also associated with MACE (RR: 1.66; 95% CI: 1.28, 2.14; I² = 65.65%), while continuous SD showed a non-significant association. The adjusted analyses for MAGE reinforced these findings. The MAGE cut-off thresholds significantly moderated the effect sizes in the meta-regression analysis. Subgroup analyses showed between-group differences in SD according to diabetes status and in MAGE according to country and follow-up duration. The certainty of evidence (GRADE) was very low for all contrasts. In outcome-specific analyses, both MAGE and SD were associated with acute heart failure and myocardial infarction, but not cardiovascular mortality.</p> Conclusion <p>GV, particularly when assessed using MAGE, is a significant predictor of cardiovascular risk in patients with pre-existing CVD. While these findings support its prognostic utility, limitations such as the observational design and residual confounding warrant cautious interpretation. Further studies should establish standardized thresholds and dose-response relationships.</p> Registration <p>PROSPERO CRD420251002622.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The prognostic role of glycemic variability in predicting the risk of adverse cardiovascular events in patients with cardiovascular diseases: a meta-analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月27日

查看全文
  • Bahar Darouei,
  • Reza Amani-Beni,
  • Nasim Kakavand,
  • Arsham Seifnezhad,
  • Sadegh Mazaheri-Tehrani,
  • Arman Shekarian,
  • Reza Eshraghi,
  • Ashkan Bahrami,
  • Ehsan Amini-Salehi,
  • Seyyed Mohammad Hashemi,
  • Mohammad Reza Movahed,
  • Pam R. Taub,
  • Guillermo Umpierrez

摘要

Background

Glycemic variability (GV) reflects glucose fluctuations, and increased GV is associated with adverse cardiovascular outcomes. We systematically evaluated the association between GV, measured by the mean amplitude of glycemic excursions (MAGE) and standard deviation (SD), and cardiovascular risk in patients with pre-existing cardiovascular disease (CVD).

Materials and methods

We searched PubMed, Embase, Scopus, Web of Science, and CENTRAL through May 2025 for studies on GV and cardiovascular outcomes in patients with established cardiovascular disease. Random-effects models with Knapp-Hartung adjustment were used to pool the risk ratios (RRs) and 95% confidence intervals (CIs). Subgroup, sensitivity, and meta-regression analyses were used to explore heterogeneity. The risk of bias was assessed using the ROBINS-I tool.

Results

Seventeen studies comprising 6,096 patients were included. In the categorical analysis, higher MAGE (RR: 2.18; 95% CI: 1.70, 2.80; I² = 15.6%) and SD (RR: 1.94; 95% CI: 1.32, 2.87; I² = 55.9%) were associated with increased risk of major adverse cardiovascular events (MACE). Continuous MAGE was also associated with MACE (RR: 1.66; 95% CI: 1.28, 2.14; I² = 65.65%), while continuous SD showed a non-significant association. The adjusted analyses for MAGE reinforced these findings. The MAGE cut-off thresholds significantly moderated the effect sizes in the meta-regression analysis. Subgroup analyses showed between-group differences in SD according to diabetes status and in MAGE according to country and follow-up duration. The certainty of evidence (GRADE) was very low for all contrasts. In outcome-specific analyses, both MAGE and SD were associated with acute heart failure and myocardial infarction, but not cardiovascular mortality.

Conclusion

GV, particularly when assessed using MAGE, is a significant predictor of cardiovascular risk in patients with pre-existing CVD. While these findings support its prognostic utility, limitations such as the observational design and residual confounding warrant cautious interpretation. Further studies should establish standardized thresholds and dose-response relationships.

Registration

PROSPERO CRD420251002622.