Abstract 19018: Variation in Treatment and Outcomes in ACS: Insights from the Alberta Contemporary Acute Coronary Syndrome Patients Invasive Treatment Strategy (COAPT) Study
Bibliographic record
Abstract
Background: In a universal health care system, we examined variations in treatment strategies and clinical outcomes in a contemporary cohort of acute coronary syndrome (ACS) patients. Methods: Hospitalization claims of 15,264 patients with ACS between April 1, 2010 and March 2012 were deterministically linked to the Alberta Provincial Project for Outcomes Assessment in Coronary Heart Disease (APPROACH) angiographic database. We compared baseline characteristics and use of diagnostic and therapeutic procedures across 3 invasive sites. For patients who underwent an invasive strategy, we examined 1-year rates of death and repeat revascularization. Results: Of the study cohort, 14.3% were medically treated at 91 non-invasive hospitals without transfer to an invasive site and had a 9.3% rate of in-hospital death. The remaining patients were admitted or transferred to one of the three invasive sites (A 5935 pts [40.4% transfer]; B 3910 pts [47.1% transfer]; C 3243 pts [57.4% transfer]). The majority were treated with an invasive strategy: A 87.4%, B 88.9%, C 90.1%, p<0.001). Patient characteristics according to invasive site are reported below (Table). Most notable are the dissimilar rates of coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) along with the different use of drug-eluting stents (DES). Mortality rates were similar (in-hospital and 1-year). However, significant differences in one-year repeat revascularization were observed. Conclusion: Results from this large contemporary Canadian study suggest variation in revascularization strategies exist resulting in differences in clinical outcome at one year. Further investigations are warranted to allow alignment of best practice and patient outcomes for patients with ACS.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".