Better Outcomes for Patients Treated at Hospitals That Participate in Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Barriers to institutions participating in clinical trials include concerns about harms and costs. However, we hypothesized that patients treated at hospitals participating in trials would have better outcomes than patients treated at nonparticipating hospitals. We tested this hypothesis in 494 CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes With Early Implementation of the American College of Cardiology/American Heart Association Guidelines) hospitals treating 174 062 patients with non-ST-segment elevation acute coronary syndrome. METHODS: Hospitals were classified into tertiles by percentage of patients concurrently enrolled in non-ST-segment elevation acute coronary syndrome trials. Outcomes were use of composite guideline-indicated care and in-hospital mortality. Multivariate regression was used to examine the association between hospital trial participation and outcomes. RESULTS: Overall, 4590 patients (2.6%) were enrolled in trials, ranging from 0% (145 hospitals) to low-enrollment tertile (1.0%; interquartile range [IQR], 0.5%-1.4%; n=226) to high-enrollment tertile (4.9%; IQR, 3.5%-9.7%; n=123). The composite guideline adherence score increased with increasing tertiles of trial participation: 76.9% (IQR, 71.8%-81.3%) vs 78.3% (IQR, 73.2%-82.4%) vs 81.1% (IQR, 76.2%-84.1%) (adjusted P= .008). Hospitals that participated in trials had higher adjusted guideline adherence than nonparticipating hospitals (low enrollment, 0.8% greater [95% confidence interval {CI}, -0.9% to 2.6%]; and high enrollment, 2.5% greater [95% CI, 0.5%-4.5%]). In-hospital mortality decreased with increasing trial participation: 5.9% vs 4.4% vs 3.5% (adjusted P= .003). Patients treated at hospitals that participated in trials had significantly lower mortality than patients treated at nonparticipating hospitals (low enrollment adjusted odds, 0.9 [95% CI, 0.8-1.0]; and high enrollment adjusted odds, 0.8 [95% CI, 0.7-0.9]). CONCLUSIONS: The CRUSADE hospitals enrolled less than 3% of their patients with non-ST-segment elevation acute coronary syndrome into trials, and one-third never participated in trials. Compared with hospitals that do not participate in trials, those hospitals that do participate in trials seem to provide better care and to have lower mortality.
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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 | 0.009 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".