Feasibility of a Practical Clinical Trial for Asthma Conducted in Primary Care
Bibliographic record
Abstract
BACKGROUND: Practical clinical trials (PCTs) are essential to generate relevant evidence-based information to improve patient health. Primary care physicians' experience performing randomized controlled trials (RCTs) on representative patient populations is limited. We implemented a pilot practice-based asthma PCT to answer the following feasibility questions: (1) Was clinician interest initiated and maintained? (2) Did clinicians enroll patients into an RCT and complete follow-up? (3) Was an interactive voice-response (IVR) telephone system useful to collect patient-reported data? METHODS: The protocol included (1) broadly representative adult asthma eligibility criteria, (2) self-reported patient-oriented outcomes, and (3) use of IVR to collect these data. Physicians in practice-based research networks, managed care organizations, and academic networks volunteered to participate. RESULTS: Of 13 physician volunteers, 10 (8 single-person office practices, 1 emergency department physician, 1 clinical researcher) from 4 states and 1 Canadian province enrolled 58 subjects and randomized 45 meeting final eligibility criteria; 39 (87%) attended the follow-up visit. However, only 34 (76%) provided adequate follow-up IVR self-report data, and subjects with less than a high school education provided significantly (P <.001) less data than other groups. CONCLUSIONS: Physician recruiting, randomizing, and completing a representative sample of adult asthma patients was feasible. The utility of IVR in primary care research requires further study.
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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 | 0.340 | 0.318 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".