Early revascularization and ACC/AHA guideline-compliant medical management improve left ventricular function and short-term prognosis in patients presenting with acute myocardial infarction and severe left ventricular dysfunction.
Bibliographic record
Abstract
BACKGROUND: Myocardial infarction (MI) complicated by severe left ventricular (LV) dysfunction is associated with significant morbidity and mortality. The natural history of this population with contemporary revascularization and guideline-based medical therapies is poorly defined. We sought to determine the impact of contemporary treatment strategies on LV function and prognosis in patients with MI and severe LV dysfunction. METHODS: Consecutive MI patients were prospectively followed as part of an ongoing internal database. The current report comprises 75 patients with first MI and severe LV systolic dysfunction (EF less than or equal to 3%). Initial demographic and clinical data were collected during hospitalization and at 1-, 3- and 6-month follow up. RESULTS: Patients were 71% male, 36% diabetic and 51% had prior coronary disease with a mean (+/- SD) age of 65 +/- 14 years. The average hospital stay was 5.7 days for ST-elevation (CPK range 424 to 5,250) and 2.4 days for non-ST-elevation MI (CPK range 175 to 705). Revascularization in-hospital was performed in 87% of patients (62 percutaneous, 3 surgical). At hospital discharge, treatment included beta-blockers (84%), ACE-inhibitors (73%), statins (81%), aspirin (88%) and clopidogrel (84%). Mean (+/- SD) LVEF was 25.7 +/- 5.9% in hospital, 36.6 +/- 11.8% by 1 to 3 months (p < 0.01), and 37.6 +/- 9.3% at 6 months (p < 0.01). By 1 to 3 months, 63% had improved LVEF, 24% were unchanged and 14% were worse. One patient died in the hospital and 3 died by 6-month follow up (mortality 5.3%). CONCLUSION: A strategy of early revascularization combined with guideline-based medical management favorably impacts LV function and short-term prognosis in MI patients with severe LV systolic dysfunction. With contemporary treatment strategies, the majority (> 60%) of patients demonstrate improvement in LVEF and mortality is low (5.3%).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".