Purpose: Temperature changes unfavorably impact on cardiovascular disease. However, the association between temperature changes and coronary artery disease (CAD) is not well documented. This study aimed to explore the association between daily mean temperature and daily CAD hospital admissions on the southeast coast of China (Fuzhou City).
Methods: A total of 1883 CAD patients who underwent percutaneous coronary intervention between 2017 and 2019 were obtained. The severity of CAD was evaluated by the Gensini score. Distributed lag non-linear model (DLNM) combined with a quasi-Poisson regression model was used to examine the delayed effect between daily mean temperature and daily CAD hospital admissions. Stratified analyses were performed by Gensini score and severity of lesions. The relative risk (RR) with a 95% confidence interval (CI) was used to assess the relationship.
Results: Extreme cold (8°C) (RR=0.49, 95% CI: 0.25– 0.99) and moderate cold (10°C) (RR=0.56, 95% CI: 0.31– 0.99) daily mean temperature with a lag of 0– 20 days were correlated with lower risk of daily CAD hospital admissions. Moderate heat (30°C) (RR=1.80, 95% CI: 1.01– 3.20) and extreme heat (32°C) (RR=2.02, 95% CI: 1.01– 4.04) daily mean temperature with a lag of 0– 20 days related to a higher risk of daily CAD hospital admissions. Similar results were observed for daily mean temperature with a lag of 0– 25 days. Stratified analysis showed the lagged effect of daily mean temperature (lag 0, 0– 5, 0– 15, 0– 20, and 0– 25 days) on the daily CAD hospital admissions was observed only in patients with a Gensini score ≤ 39 (tertile 1).
Conclusion: Cold temperatures may have a protective effect on daily CAD hospital admissions in the Fuzhou area, whereas hot temperatures can have an adverse effect.

Keywords: temperature, coronary artery disease, gensini score, daily admissions, lag effect