Standard admission orders can improve the management of acute myocardial infarction
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether the use of standard admission orders for patients admitted with acute myocardial infarction (AMI) is associated with better hospital quality of care. DESIGN: Secondary analysis of a population-based database derived from a large cluster randomized AMI quality improvement trial. SETTING: Seventy-eight acute care hospital corporations located in Ontario, Canada. PARTICIPANTS: A total of 5338 patients with AMI admitted directly to the coronary care/intensive care units of participating hospitals in 2004/2005. Main outcome measure(s) Hospital performance on seven process-of-care measures and a combined composite process-of-care measure. Secondary outcomes were 30-day and 1-year mortality rates. RESULTS: Most patients (81%) were treated with standard admission orders. These patients were more likely to receive four of seven identified process-of-care measures (P< 0.05), including fibrinolytics ≤ 30 min or primary percutaneous coronary intervention ≤ 90 min of arrival, fibrinolytics administration decided by emergency department physician, aspirin ≤ 6 h of arrival and lipid test ≤ 24 h. After propensity-score matching (for risk adjustment), use of standard admission orders was not associated with significantly lower 30-day or 1-year mortality. However, patients who met the composite process-of-care measure had lower 30-day and 1-year mortality (relative risk= 0.51 (95% confidence interval (CI): 0.40-0.67) and 0.70 (95% CI: 0.58-0.84), respectively). CONCLUSION: In AMI, the use of standard admission orders was associated with improved hospital performance on several but not all acute process-of-care quality indicators. The utilization of standard admission orders should be considered as a strategy for improving hospital care in patients admitted with AMI.
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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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".