Abstract 8397: Action Registry Guideline Adherences Differ Between ST-Elevation and Non-ST Elevation Myocardial Infarction Patients
Bibliographic record
Abstract
Background: Based on the ACC/AHA 2008 Performance Measures for Adults with Acute Myocardial Infarction, the ACTION Registry-GWTG (Get with the Guidelines) Outcomes Report examines a given site's performance on acute and discharge guideline metrics used in treating heart attacks. We reviewed our data from the Outcomes Report to compare guideline adherences between ST Elevation myocardial infarction (STEMI) and non-ST Elevation myocardial infarction (NSTEMI) patients. Methods: There were 76,493 STEMI and 117,440 NSTEMI ACTION Registry participants between the 4 th quarter of 2007 through the 3 rd quarter of 2010 (i.e., 2008-2010). Acute guideline metrics included aspirin (ASA) on arrival and evaluation of left ventricular systolic function (LVSF). Discharge guideline metrics included aspirin (ASA), beta-blocker (BB), angiotensin-converting enzyme inhibitor (ACE) or angiotensin-receptor blocker (ARB) if ejection fraction <40%, statin, adult smoking cessation advice (ASCA), and cardiac rehabilitation referral (CRR). We analyzed adherences to guidelines in STEMI and NSTEMI patients over three years - nationally (NAT), at our center (MMH), and at the nation's top 10% centers (TOP). Chi square and Fischer's exact test were used to compare the two groups. Results: Conclusions: We found statistically significant discrepancies in metric guideline adherences between STEMI and NSTEMI patients over three years. Adherences were higher in the STEMI compared with NSTEMI groups in nearly all metrics measured. This may reflect the presence of timely and comprehensive “Code STEMI” guidelines in place. Perhaps “Code NSTEMI” guidelines or diagnosis-based (eg, NSTEMI-based) medication reconciliation forms could further improve NSTEMI guideline adherences.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".