Clinical outcomes of patients undergoing primary percutaneous coronary intervention for acute myocardial infarction requiring the intensive care unit
Bibliographic record
Abstract
Background: Outcomes for patients with ST-segment elevation myocardial infarction continue to improve, largely due to timely provision of reperfusion by primary percutaneous coronary intervention (PPCI). However, despite prompt and successful PPCI, a small proportion of patients require ventilatory and hemodynamic support in an intensive care unit (ICU). The outcome of these patients remains poorly defined. Methods: A retrospective review of all consecutive admissions post-PPCI pathway to a single ICU between January 2009 and May 2014 was performed. Patients were analysed based on survival and indication for admission. Preadmission characteristics and ICU course were reviewed. Univariate and multivariable regression analysis was performed to determine predictors of outcome. Results: During the study period 2902 PPCI were performed and 101 patients were admitted to ICU following PPCI (incidence 3.5%). ICU mortality post-PPCI was 33.7%. Pre-ICU admission factors in a multivariable logistic regression analysis associated with increased mortality included requirement for an intra-aortic balloon pump and a high SOFA score. Conclusions: ICU admission post PPCI is associated with significant mortality. Mortality was related to high presenting SOFA score and need for IABP. These results provide important prognostic information and an acceptable method for risk-stratifying patients with acute myocardial infarction requiring intensive care.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".