Abstract 12401: Multidimensional Representativeness of Older Adults With Atrial Fibrillation in Randomized Controlled Trials: Comparing Participants of 12 Oral Anticoagulant RCTs to a Nationally Representative US Cohort
Bibliographic record
Abstract
Background: Anticoagulant RCTs are thought to have enrolled younger and less comorbid patients with atrial fibrillation (AF) compared to the general population. We developed a representation score summarizing patient characteristics to describe how well RCT participants with AF reflect a nationally representative cohort. Methods: We studied adults >=65 years old with AF by harmonizing two data sources: (1) patient-level data from 12 landmark RCTs testing anticoagulants vs. placebo or antiplatelets from the Atrial Fibrillation Investigators (AFI) consortium and (2) the Health and Retirement Study AF cohort (HRS-AF), a representative cohort of older adults with AF in the U.S. We fit a logistic regression model to estimate the probability of inclusion in the HRS-AF cohort in the pooled sample using age, height, weight, gender, heart failure, hypertension, diabetes, prior stroke, and prior myocardial infarction. This estimate, the Trial Benchmark Score, reflected the probability of belonging to the HRS-AF cohort and ranged from 0 to 1, with higher scores reflecting a greater likelihood of belonging to the HRS-AF cohort. We plotted the distribution of scores for HRS-AF and AFI participants and compared the mean scores using a t-test. Results: Compared to the HRS-AF cohort (n=3542), AFI participants (n=7933) were younger (72 vs. 76yrs, standardized mean difference [SMD] -0.7), more frequently male (64% vs. 46%, SMD 0.3), and had a lower likelihood of prior stroke (19% vs. 23%, SMD -0.4). The mean Trial Benchmark Score differed significantly between the two cohorts (HRS-AF mean 0.47 vs. AFI mean 0.23, p<0.001) ( Figure ). 52% of HRS-AF participants and 12% of AFI participants had a score >0.47 (the HRS-AF mean score). Conclusion: Differences in the Trial Benchmark Scores distributions indicate a substantial difference in the distribution of observable characteristics and that RCT participants were not fully representative of the benchmark population.
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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 | 0.251 | 0.318 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.012 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".