Real-world management and outcomes of 7 million patients with acute coronary syndrome according to clinical research trial enrolment status: a propensity matched analysis
Bibliographic record
Abstract
AIMS: We aimed to determine whether clinical outcomes and invasive care of acute coronary syndrome (ACS) patients participating in trials differed from those of non-participants, particularly including those who were trial eligible. METHODS AND RESULTS: We included all hospitalizations with a principal diagnosis of ACS in the US National Inpatient Sample between January 2004 and September 2015, stratified by trial enrolment and eligibility using the International Classification of Diseases, ninth revision. We conducted propensity score matching to investigate the following outcomes: all-cause mortality; major bleeding; stroke; composite of mortality, stroke, and cardiac complications [major adverse cardiovascular and cerebrovascular events (MACCEs)]; coronary angiography (CA); and percutaneous coronary intervention (PCI). A total of 7 091 179 weighted ACS hospitalizations were analysed, including 19 684 (0.3%) trial participants and 7 071 495 non-participants (3 485 514 of whom were trial eligible). Trial participants were more likely to receive CA [Δ% 28.73%, 95% confidence interval (CI) 27.22-30.24, P < 0.001] and PCI (Δ% 27.13%, 95% CI 24.86-29.41, P < 0.001), with decreased mortality (Δ% -3.51%, 95% CI -4.72 to -2.31, P < 0.001), MACCEs (Δ% -3.04%, 95% CI -4.55 to -1.53, P < 0.001), and bleeding (Δ% -0.89%, 95% CI -1.59 to -0.19, P = 0.013) compared with non-participants. After accounting for eligibility, trial participants were more likely to undergo CA (Δ% 22.78%, 95% CI 21.58-23.99, P < 0.001) and PCI (Δ% 23.95%, 95% CI 21.77-26.13, P < 0.001), and had no difference in mortality (Δ% -0.21%, 95% CI -0.65 to 0.24, P = 0.362). CONCLUSION: Among ACS patients, trial enrolment was associated with significantly greater invasive care and lower mortality than among matched non-participants. Trial participants were more likely to be invasively managed even when compared with eligible non-participants, even though there was no difference in mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".