Predictors of Mortality in Acute Myocardial Infarction: Insights From the Healthcare Cost and Utilization Project (HCUP) Nationwide Readmission Database

Background Acute myocardial infarction (AMI) remains a significant concern for morbidity and mortality globally. Understanding AMI-related mortality predictors can help mitigate risks and improve patient outcomes. This study was conducted to evaluate demographic, clinical, and institutional factors associated with in-hospital mortality among patients admitted for AMI. Methods A retrospective analysis was conducted using the 2020 Nationwide Readmission Database (NRD). Adult patients (≥18 years) with a primary diagnosis of AMI were included. COVID-19 co-infection was identified via secondary diagnoses. Exclusion criteria comprised missing mortality data. Patient demographics, comorbidities, and hospital characteristics were analyzed. A survey-weighted multivariable logistic regression, incorporating discharge weights, stratification, and clustering, was used to estimate odds ratios (OR) for 30-day all-cause mortality (death during index admission or within 30-day unplanned readmission), adjusting for the above covariates, including COVID-19 status. Results Of 1,193,046 AMI admissions, 127,128 (10.7%) died within 30 days. Median age was 75 (65-83) years among non-survivors compared to 69 (59-79) years in survivors. Key multivariable predictors of higher mortality included All Patients Refined Diagnosis-Related Group (APR-DRG) "extreme" severity (OR 3.82, p < 0.001), cardiac arrest (OR 7.03, p < 0.001), cardiogenic shock (OR 1.52, p < 0.001), acute kidney injury (OR 1.82, p < 0.001), and COVID-19 co-infection (OR 2.51, p < 0.001). Institutional factors such as treatment at micropolitan hospitals (OR 1.72, p < 0.001) and self-pay status (OR 1.24, p < 0.001) also increased risk, with additional categories for Medicare, Medicaid, and private payers examined. Conclusion In conclusion, predictors of mortality in AMI patients include baseline characteristics such as age and gender, comorbidities like heart failure and cardiac arrest, socioeconomic factors, and the impact of COVID-19. Future studies should explore patient-level race/ethnicity and education data, assess vaccination effects, and develop targeted interventions to reduce these disparities.