Gender Differences in Food Insecurity, Anxiety, and Nutrition in Israel: A Cross-Sectional Study.

Stable angina is a common disorder worldwide with a continuously increasing prevalence (, ). Minimizing or eradicating symptoms of angina is the key aim of stable angina pectoris treatment (). Angina occurs when myocardial oxygen supply does not meet myocardial demand, typically triggered by exertion or emotional stress (). Emerging evidence suggests environmental thermal stress may constitute an underrecognized trigger (–). While cold-induced coronary vasoconstriction has been well documented, recent studies reveal high temperatures may exacerbate angina through multiple mechanisms, such as hemodynamic overload, dehydration-thrombosis cascade and electrolyte-mediated instability. Thermoregulated cutaneous vasodilation redistributes large amounts of cardiac output to the peripheral circulation, forcing compensatory increases in heart rate and myocardial oxygen consumption (). This creates a “double burden” scenario in which coronary perfusion pressure decreases while myocardial oxygen demand simultaneously increases, thereby exacerbating the supply–demand mismatch (). Profuse sweating induces plasma volume depletion, elevating hematocrit within 2 h (). This hemoconcentration increases blood viscosity and promotes platelet aggregation via shear stress activation (). When the temperature rises, the body sweats more to cool down, leading to the loss of electrolytes such as potassium and sodium. Sodium-potassium ATPase dysfunction during thermal stress causes intracellular K + depletion (). Electrolyte imbalance can affect the normal functioning of the heart, causing arrhythmias and other cardiac problems that may worsen angina. Furthermore, thermal stress has been linked to an augmented risk of cardiovascular dysfunction (), encompassing conditions such as hypertension and acute myocardial infarction. The vasodilation of peripheral blood vessels, while attempting to dissipate heat, may concurrently reduce systolic blood pressure, diminishing coronary blood flow and elevating the risk of sudden cardiac arrest (). Additionally, Patients who use diuretics may have severe hypovolemia and consequently angina attacks or even heat shock (). The risk of heat-related illness results from a combination of individual susceptibility, environmental heat exposure, and other contributing factors (). Much of the prior literature on temperature-related cardiovascular risk has focused on the effects of heat exposure on the overall patient population, with fewer studies focused on individual susceptibility and identify relevant influencing factors, like gender, ethnicity and latitude (–). Under a warming climate, hot weather can have an increasing impact on patients with heat-sensitive angina (HSA) pectoris, which means angina attacks will be more frequent for them in the future. More precise identification tools, preventions and interventions for patients with HSA are still lacking. Machine learning (ML) is a new type of artificial intelligence that is beginning to be widely applied to clinical data sets for the purpose of developing robust risk models and redefining patient classes (). In environmental epidemiology, machine learning has found numerous applications, encompassing studies on high temperature-related epidemiology, among others. For instance, Boudreault et al. developed several machine and deep learning models to predict heat-related mortality in Canada (), while Kim et al. built a random forest (RF) model to predict CVD mortality in South Korea (). In clinical settings, Hirano et al. built 4 ML models for heatstroke mortality predictions in Japan (), while Fujiwara et al. used ML for heart illness detection (). While these studies are important, none has yet used ML to predict heat-related angina attacks. The purpose of this study is to predict the risk of angina attacks in high temperature environment for patients with stable angina pectoris based on ML models.