ArticleCureus2025
Predictors of Mortality in Acute Myocardial Infarction: Insights From the Healthcare Cost and Utilization Project (HCUP) Nationwide Readmission Database.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.