Management and outcomes of acute myocardial infarction in patients with preexisting heart failure: an analysis of 2 million patients from the national inpatient sample
Bibliographic record
Abstract
Background Inpatient management and outcomes of patients presenting with acute myocardial infarction (AMI) with a history of heart failure (HF) have not been well characterized.Methods Hospitalizations for AMI from the Nationwide Inpatient Sample (2015–2018) were categorized according to a preexisting diagnosis of HF with preserved ejection fraction (HFpEF), reduced ejection fraction (HFrEF), or absence of HF. Utilization of invasive management and in-hospital outcomes were analyzed.Results Among 2,434,639 hospitalizations with an AMI, 19.8% had a history of HFrEF and 11.9% had a history of HFpEF. Coronary angiography and PCI respectively were performed significantly less among patients with HF (36.6% and 17.4% in HFpEF, 51.1% and 24.6% in HFrEF, and 64.4% and 42.3% among patients without HF, all p < 0.0001). Mortality was more common among patients with HFrEF (10.3%) and HFpEF (8.3%) when compared to patients without a history of HF (6.4%), p < 0.0001. Conclusion HF is a common preexisting comorbidity among patients presenting with AMI and is associated with lower utilization of invasive procedures and higher complications including mortality, particularly among those with HFrEF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".