Practicing outcome-based medical care using pragmatic care trials
Bibliographic record
Abstract
The current separation between medical research and care is an obstacle to essential aspects of good medical practice: the verification that care interventions actually deliver the good outcomes they promise, and the use of scientific methods to optimize care under uncertainty. Pragmatic care trials have been designed to address these problems. Care trials are all-inclusive randomized trials integrated into care. Every item of trial design is selected in the best medical interest of participating patients. Care trials can eventually show what constitutes good medical practice based on patient outcomes. In the meantime, care trials give clinicians and patients the scientific methods necessary for optimization of medical care when no one really knows what to do.We report the progress of 9 randomized care trials that were used to guide the endovascular or surgical management of 1212 patients with acute stroke, intracranial aneurysms, and arteriovenous malformations in a single center in an elective or acute care context. Care trials were used to address long-standing dilemmas regarding rival medical, surgical, or endovascular management options or to offer innovative instead of standard treatments. The trial methodology, by replacing unrepeatable treatment decisions by 1:1 randomized allocation whenever reliable knowledge was not available, had an immediate impact, transforming unverifiable dogmatic medical practice into verifiable outcome-based medical care. We believe the approach is applicable to all medical or surgical domains, but widespread adoption may require the revision of many currently prevalent views regarding the role of research in clinical practice.
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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 | 0.007 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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; both teacher heads 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".