Clinical practice patterns and ascertainment bias for cardiovascular events in a randomized trial: A survey of investigators in the BEST-CLI trial
Why this work is in the frame
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Bibliographic record
Abstract
Ascertainment bias is a well-recognized source of bias in research, but few studies have systematically analyzed sources of ascertainment bias in randomized trials in which blinding is not possible and endpoint assessment is not protocolized. In the current study, we sought to evaluate differences in the clinical practice patterns of trial investigators with respect to bias in the ascertainment of pre-revascularization patient risk and the incidence of secondary endpoints post-revascularization. We conducted a cross-sectional survey of active investigators ( n = 936) from the Best Endovascular Versus Best Surgical Therapy for Patients with Critical Limb Ischemia (BEST-CLI) trial. The total survey response rate was 19.6% (183/936). Vascular surgeons were more likely than nonsurgical interventionalists to order tests for cardiac complications after both surgical bypass ( p < 0.001) and endovascular revascularization ( p = 0.038). Post-procedure, investigators were more likely to order additional testing for cardiac complications in open surgery versus endovascular cases (7% vs 16% never, 41% vs 65% rarely, 43% vs 17% sometimes, 9% vs 2% always, respectively; p < 0.0001). Significant variation in practice patterns exist in the pre- and post-procedure assessment of cardiac risk and events for patients with CLI undergoing revascularization. Variation in the ascertainment of risk and outcomes according to the type of revascularization procedure and physician specialty should be considered when interpreting the results of clinical studies, such as the BEST-CLI trial. ClinicalTrials.gov Identifier: NCT02060630
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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 | 0.046 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it