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Adv."],"published-print":{"date-parts":[[2026,8,28]]},"abstract":"<jats:p>Extreme heat is an escalating public health concern. Although prior studies have examined heat-health associations, their reliance on restricted diagnoses and diagnostic categories may miss or misclassify heat-related illness. Here, we conducted a heat-wide association study to evaluate acute-care diagnoses associated with extreme heat in Chicago, Illinois. Using 916,904 acute-care visits\u2014including emergency department and urgent care encounters\u2014among 372,140 adults across four health care systems from 2011 to 2023, we applied a two-stage analytic approach: quasi-Poisson regression to screen diagnosis codes associated with heat, followed by distributed lag nonlinear models in a time-stratified case-crossover design to characterize exposure-response and lag patterns. Stage 1 retained 44 diagnosis codes, and 33 clinically reportable diagnoses were retained after stage 2. We observed elevated cumulative odds over lags 0 to 3 for multiple diagnoses, including fluid-balance and renal disorders, dermatologic and pressure-related conditions, multiple sclerosis, a cannabinoid-related mental and behavioral disorder, varicose veins of the lower extremities, and multiple injuries and external causes. 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