Abstract 16600: Unraveling Outcomes in Medically Managed Patient With Acute Coronary Syndromes (ACS): The Alberta COntemporary Acute coronary syndrome Patients invasive Treatment Strategies (COAPT) Study
Bibliographic record
Abstract
Objectives: Limited “real world” data exists on characteristics and outcomes of ACS patients managed without revascularization (REVASC). Accordingly, we assessed an inclusive cohort of ACS patients grouped by catheterization and REVASC status. Methods: ACS pts in Alberta, Canada (n=3.7M) were assessed using population health database linkages (April 2010 - March 2013) and categorized into 3 groups: no CATH, CATH no REVASC and CATH REVASC (excluding pts with previous CATH - 6 m or ACS - 3 m). Baseline characteristics, in-hospital death, one year death and readmission were compared (logistic regression modelling). Results: Of 14, 661 ACS pts, 20.6% were not referred for CATH, 17.7% had CATH no REVASC and 61.7% had CATH REVASC (table). The pts not referred for CATH pts were older had more comorbidities, less frequent STEMI and were more likely admitted to a non-CATH hospital. They had prolonged hospital stay and 11.9% in-hospital death; 4-fold higher comparing no CATH vs. REVASC (adjusted OR 4.37, 95% CI 3.4-5.6). After excluding pts with in-hospital death within 2 days from admission and/or non-obstructive CAD (n=712), pts not referred for CATH had a 3-fold risk of in-hospital death (OR 3.28, 95% CI 2.5-4.4). Compared to REVASC, CATH no REVASC did not have increased in-hospital death (OR 1.2, 95% CI 0.86 - 1.1), however if pts without obstructive CAD were excluded, CATH no REVASC had a trend for increased in-hospital death (OR 1.4, 95% CI 0.99 - 1.96). Cath no REVASC was associated with increased 1 yr death (adjusted OR 1.97 (1.54-2.5)). Conclusion: Patients with ACS managed medically represent a diverse patient population. Once receiving CATH, pts managed medically have similar risk of death as those receiving REVASC. However those not referred for CATH have multiple comorbidities, are more likely managed in non-cardiac CATH hospitals and have a marked increase in both of in-hospital and 1 year death and rehospitalizaiton.This substantial cohort deserves further investigation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".