From guidelines to clinical practice: the impact of hospital and geographical characteristics on temporal trends in the management of acute coronary syndromes The Global Registry of Acute Coronary Events (GRACE)
Bibliographic record
Abstract
AIMS: The extent to which hospital and geographic characteristics influence the time course of uptake of evidence from key clinical trials and practice guidelines is unknown. The gap between evidence and practice is well recognized but the factors influencing this disjunction, and the extent to which such factors are modifiable, remain uncertain. METHODS AND RESULTS: Using chronological data from the GRACE registry (n=12666, July 1999 to December 2001), we test the hypothesis that hospital and geographic characteristics influence the time course of uptake of evidence-based guideline recommendations for acute coronary syndromes (ACS) with and without ST elevation. Certain therapies were widely adopted in both ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) patients (aspirin >94% of all patients; beta-blockers 85-95%) and changed only modestly over time. Significant increases in the use of low-molecular-weight heparins and glycoprotein IIb/IIIa inhibitors occurred in STEMI and NSTEMI patients in advance of published practice guidelines (September/November 2000) with marked geographical differences. The highest use of LMWH was in Europe in NSTEMI (86.8%) and the lowest in the USA (24.0%). Contrasting geographical variations were seen in the use of percutaneous coronary intervention (PCI) in NSTEMI: 39.5% USA, 34.6% Europe, 33.5% Argentina/Brazil, 25.0% Australia/New Zealand/Canada (July-December 2001). Theuse of PCI was more than five times greater in hospitals with an on-site catheterization laboratory compared to centres without these facilities, and geographic differences remained after correction for available facilities. CONCLUSIONS: Hospital and geographical factors appear to have a marked influence on the uptake of evidence-based therapies in ACS management. The presentation and publication of major international guidelines was not associated with a measurable change in the temporal pattern of practice. In contrast, antithrombotic and interventional therapies changed markedly over time and were profoundly influenced by hospital and geographic characteristics.
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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 | 0.020 | 0.131 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".