Background and Aims: Although non-optimum ambient temperature is a major non-traditional risk factor for acute myocardial infarction, there is no prior knowledge on whether non-optimum ambient temperature could differentially affect myocardial infarction with obstructive coronary artery disease (MI-CAD) and myocardial infarction with non-obstructive coronary arteries (MINOCA). Methods: Using the Chinese Cardiovascular Association database-Chest Pain Center Registry, a nationwide, time-stratified, case-crossover investigation was conducted from 2015 to 2021. Meteorological data were obtained from an established satellite-based model, and daily exposures were assigned according to the onset of myocardial infarction in each patient. A conditional logistic regression model combined with distributed lag non-linear models (10 days) was used to estimate the exposure–response relationships. Results: A total of 83 784 MINOCA patients and 918 730 MI-CAD patients were included. The risk of MINOCA and MI-CAD associated with low temperature occurred at lag 2 day and lasted to 1 week. Extremely low temperature was associated with a substantially greater odds ratio (OR) of MINOCA [OR 1.58, 95% confidence interval (CI) 1.31–1.90] than MI-CAD (unmatched: OR 1.32, 95% CI 1.23–1.43; equally matched by age and sex: OR 1.25, 95% CI 1.04–1.50), compared with the corresponding reference temperatures (30°C, 35°C, and 30°C). Stronger associations were observed for patients who were aged ≥65 years, female, or resided in the south. There was no significant difference for the impacts of high temperature on MINOCA and MI-CAD. Conclusions: This nationwide study highlights the particular susceptibility of MINOCA patients to ambient low temperature compared with that of MI-CAD patients.

Background: Acute myocardial infarction comprises two distinct entities, myocardial infarction with obstructive coronary artery disease (MI-CAD) and myocardial infarction with nonobstructive coronary arteries (MINOCA), characterized by divergent pathogenesis and potential links to particulate air pollution. This study aimed to investigate the differential impacts of such pollution on the onset of MI-CAD and MINOCA to inform precise prevention and control of myocardial infarction. Methods: Based on the Chinese Cardiovascular Association Database—Chest Pain Center Registry, we performed a nationwide, time-stratified, case-crossover study from 2015 to 2021. Hourly concentrations of fine particulate matter (PM _2.5 ) and inhalable particulate matter (PM ₁₀ ) were acquired through nearby fixed-site monitoring. We combined a conditional logistic regression model with polynomial distributed lag nonlinear models to differentiate the exposure–response relationships of the hourly concentrations of PM _2.5 and PM ₁₀ with the onset of MI-CAD and MINOCA over 72 hours. We further calculated the attributable fractions (AFs) due to particulate air pollution accordingly. Results: A total of 918,730 patients with MI-CAD and 83,802 patients with MINOCA were included. The risks of MINOCA and MI-CAD onset were highest at the concurrent exposure hour and diminished within 30 hours. Exposure to PM2.5 and PM10 was associated with a 1–2-fold higher risk of MINOCA compared with MI-CAD. Each interquartile range increase in the concentrations of PM _2.5 and PM ₁₀ resulted in a 2.17% (95% CI: 0.82–3.53%) and 1.57% (95% CI: 0.23–2.94%) increased risk of MINOCA onset, respectively. The corresponding effect estimates for MI-CAD were 1.14% (95% CI: 0.74–1.55%) and 0.47% (95% CI: 0.13–0.81%), respectively. There were no apparent thresholds for these associations. The AFs of MINOCA attributable to PM _2.5 and PM ₁₀ were 2.43% and 1.72%, respectively, which were almost one to two times greater than those of MI-CAD (1.27% and 0.54%, respectively). Conclusions: This nationwide study provides robust evidence that, compared with MI-CAD, MINOCA is more sensitive to particulate air pollution. This effect could occur during concurrent hours and under health-based air quality guidelines.

Background: Cardiac computed tomography angiography (CCTA), the premier coronary artery disease (CAD) rule-out test, is less available in rural areas (vs urban) in the US. To address this gap, we previously developed a test using non-invasive signals and a machine-learned algorithm, usable anywhere with internet. We trained the algorithm using US populations: (1) subjects enrolled before CCTA for specificity and (2) subjects undergoing invasive coronary angiography (ICA), for both sensitivity and specificity. US validation used separate, identically constructed, blinded populations (N = 1816). In US validation, sensitivity was 88% (95% CI 85–91%) and specificity was 51% (48–55%). Although China is urbanizing rapidly, 510 million (36% of the population) still reside in rural areas. Thus, China might benefit from the test, but given the demographic differences, the efficacy of the test in the Chinese population is unknown. The aim of the present study was to assess test performance within a cohort of Chinese ICA subjects. Methods: Subjects were enrolled at Zhongshan Hospital, Fudan University (China), using the same inclusion and exclusion criteria as in the US study. The same device as in the US captured signals pre-ICA. We applied the unchanged algorithm from US validation to the signals, then matched with the ICA results. Results: 558 subjects had both ICA results and a signal, 458 passed signal quality and outlier checks, and 348 had significant CAD. Compared to the US sensitivity cohort, the Chinese cohort was significantly younger, had a lower BMI, a higher proportion of males, and lower rates of tobacco use, hypertension, and diabetes. Race was Asian only in China, while the US was primarily White/Caucasian. Chinese cohort sensitivity was 89% (86–93%), p = 0.46 vs the US. Discussion: Our study was limited by the lack of a Chinese CCTA specificity cohort. However, sensitivity was high, and thus robust to the significant demographic shifts. Therefore, we anticipate similar behavior in specificity; to explore that, we combined the Chinese ICA negatives (N = 110) with the US CCTA negatives from the previous work, in the same proportion as used in US validation, which models the population of patients under assessment for cardiac symptoms. The resultant specificity was 51% (48–55%). With the Chinese ICA positives, the area under the receiver operator characteristic curve was 0.79 (0.77–0.81). These results suggest the test’s potential effectiveness in the Chinese population. Trial registration: NCT04034537.