Abstract 9193: Variation in Quality of Care Among Patients Hospitalized With Acute Heart Failure in an International Trial: Findings From ASCEND-HF
Bibliographic record
Abstract
BACKGROUND: Translation of evidence-based heart failure (HF) therapies to clinical practice is incomplete and may be subject to international variation. We compared key HF quality indicators in acute HF (AHF) patients enrolled in the international Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure (ASCEND-HF) trial. METHODS: Patients were admitted to hospital for AHF and comprised 5 regions (North America n=3149, Latin America n=658, Asia- Pacific n=1744, Central Europe n=966 and Western Europe n=490). Quality indicators assessed at hospital discharge from the US-based Get With The Guidelines program were used, including: medications (ACEI/ARB, beta blockers, aldosterone inhibitors, hydralazine-nitrates, statin therapy and warfarin) for eligible patients, use (or planned use) of implantable intracardiac devices (ICD, CRT) for eligible patients and blood pressure control (<140/90 mmHg). RESULTS: 7007 intent-to-treat AHF patients in 398 centres were enrolled. There was significant variation in conformity between different quality indicators, ranging from 0% to 89% (See Table). Of all potential performance opportunities, 24,807 of 39874 (62%) were met, with Central Europe highest at 68%, followed by North America (65%), Western Europe (63%), Latin America (59%) and Asia-Pacific (56%), P<0.0001. CONCLUSION: Quality of care for patients hospitalized with AHF remains suboptimal even within a randomized clinical trial. Moreover, significant unexplained inter-regional variability in quality of care exists. Further study is required to understand and overcome the global barriers to delivery of optimal evidence-based care.
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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 | 0.027 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".