Stable Patients With STEMI Rarely Require Intensive-Care-Level Therapy After Primary PCI
Bibliographic record
Abstract
BackgroundThe 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.MethodsA 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.ResultsA 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%).ConclusionsPatients 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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".