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Nonlinear Relation Between Cardiac Mortality and Excess Temperature in Heatwaves: Exposure Response in 2.39 Million Patients.

Journal of the American College of Cardiology2025-03-25PubMed
Total: 81.5Innovation: 8Impact: 8Rigor: 8Citation: 9

Summary

Using a novel excess cumulative temperature metric, compound heatwaves showed near-linear increases in cardiac mortality risk, far exceeding estimates based on traditional binary heatwave definitions. The study quantified substantial excess deaths and identified disease subtypes most sensitive to heat stress.

Key Findings

  • Compound heatwaves showed a near-linear increase in cardiac mortality risk across the entire ECT-HW range (OR 1.86), exceeding nighttime-only (OR 1.16) and daytime-only (OR 1.19).
  • Estimated excess cardiac deaths were 41,869 (compound), 9,092 (nighttime-only), and 9,809 (daytime-only), surpassing traditional binary-heatwave estimates.
  • Sudden cardiac arrest, acute myocardial infarction, and heart failure were most sensitive to compound heatwaves; pulmonary heart disease was least sensitive.

Clinical Implications

Health systems should incorporate compound heatwave alerts, deploy disease-specific heat health action plans (e.g., for heart failure and post-MI patients), and integrate environmental risk into cardiac triage and telemonitoring during heat events.

Why It Matters

It reframes heatwave risk assessment for cardiac mortality with an exposure–response metric that avoids underestimation, directly informing climate-health policy and disease-specific preparedness.

Limitations

  • Observational design with potential residual confounding and exposure misclassification.
  • Generalizability limited to Mainland China; relies on death certificate coding accuracy.

Future Directions

Validate ECT-HW models across regions, integrate real-time environmental feeds into clinical risk tools, and test targeted heat-health interventions for high-risk cardiac populations.

Study Information

Study Type
Case-control
Research Domain
Prognosis
Evidence Level
III - Large nationwide observational case-crossover analysis with advanced time-series modeling
Study Design
OTHER