Bibliographic record
Abstract
Background ST-segment elevation myocardial infarction (STEMI) outcomes are influenced by the location of the culprit vessel with worse outcomes portended with a left anterior descending (LAD) culprit lesion. However, relatively little is known about the independent association of LAD involvement with clinical outcomes of patients with STEMI with and without out-of-hospital cardiac arrest (OHCA). Methods We identified 91 patients with and 929 without a preceding OHCA within the Vancouver Coastal Health Authority who presented with an acute STEMI and underwent primary percutaneous coronary intervention between 26 June 2007 and 31 March 2016. Results Patients with STEMI with OHCA had higher rates of in-hospital cardiac arrest (43.3% vs 8.3%, p<0.001), heart failure (50.5% vs 11.3%, p<0.001), cardiogenic shock (49.5% vs 5.7%, p<0.001), mortality (35.2% vs 3.3%, p<0.001) and reduced left ventricular ejection fraction (LVEF; 42.9% vs 47.3%, p<0.001) compared with those without OHCA. Among patients without OHCA, LAD involvement was associated with increased heart failure (18.1% vs 5.2%, p<0.001), in-hospital cardiac arrest (10.7% vs 6.2%, p<0.014), cardiogenic shock (8.4% vs 3.3%, p<0.001), reduced LVEF (43.0% vs 51.2%, p<0.001) and mortality (5.2% vs 1.3%, p=0.003) compared with patients without LAD involvement. With the exception of LVEF, these associations were not seen among patients with STEMI with OHCA and an LAD culprit. The presence of an LAD culprit was not independently associated with increased hospital mortality among patients with OHCA after adjusting for potential confounding factors. Conclusion Our study has demonstrated a differential impact of LAD involvement on clinical outcomes among patients with STEMI who present with and without OHCA. Our data highlight the complexity surrounding the prognostication following OHCA complicating STEMI and demonstrate that other mechanisms other than LAD involvement contribute to the high mortality associated with OHCA as a result of STEMI.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.082 | 0.021 |
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".