Stable Patients With STEMI Rarely Require Intensive-Care-Level Therapy After Primary PCI
Bibliographic record
Abstract
Background The disposition of patients presenting with ST-elevation myocardial infarction (STEMI) is commonly the coronary care unit. Recent studies have suggested that low-risk STEMI patients could be managed in a lower-acuity setting immediately after percutaneous coronary intervention (PCI). We sought to determine the frequency of downstream intensive-care therapy used in our "stable" STEMI patients post-PCI. Methods A single-centre, retrospective review was completed of consecutive patients who underwent primary PCI for STEMI between 2013 and 2016. Post-PCI, patients were defined as being stable if they had not required intensive-care therapy or suffered significant complications. Intensive-care therapies and complications were defined as invasive/noninvasive ventilation, pacing, cardiac arrest, use of vasopressors/inotropes, dialysis, stroke, or major bleeding. This group of stable patients had their course followed to discharge. Results A total of 731 patients presented with STEMI for primary PCI. Of these, 132 patients (18%) required intensive-care therapies and/or had complications prior to PCI and were excluded. After PCI, 599 STEMI patients (82%) were defined as stable, according to the above definition. Of these, 11 patients (1.8%) required intensive-care therapies during their hospitalization. Zwolle scores were significantly higher in patients with complications (6.3 ± 4.4 vs 2.0 ± 1.5, P < 0.0001). The most frequent intensive-care complications and therapies were cardiac arrest (7 patients, 1%) and vasopressor use (4 patients, 0.7%). These complications most frequently occurred on the first admission day (6 patients, 1%). Conclusions Patients who are stable at the completion of their primary PCI rarely develop complications that require intensive care. These patients are easily identified for triage to a lower-acuity setting, alleviating congestion in cardiac care units and reducing hospitalization costs.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".