Neglected external validity in reports of randomized trials: The example of hip and knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To evaluate data reporting related to external validity from randomized controlled trials (RCTs) assessing pharmacologic and nonpharmacologic treatment for hip and knee osteoarthritis (OA). METHODS: All RCTs assessing pharmacologic treatments and nonpharmacologic treatments for hip and knee OA indexed between January 2002 and December 2006 were selected. A sample of 120 articles were randomly selected: 30 each assessing pharmacologic treatments, surgery or technical interventions, rehabilitation, and nonimplantable devices. RESULTS: The country was clearly reported in 25 (21%) reports, the setting described in 40 (33%) reports, and the number of centers in 54 (45%). Details about the centers (volume of care) were given in 24 (20%) reports. Rates were lower for surgical trials for the country (3%), the setting (3%), the number of centers (13%), and details about the centers (7%). The intervention was adequately described in all pharmacologic reports and in >80% of rehabilitation reports. The technical procedure was given in all surgical intervention trial reports, but the type of anesthesia was reported in 4 (13%), preoperative care in 2 (7%), and postoperative care in 15 (50%). The device was described in 93% of device trial reports, but the manufacturer was reported in only 33%. CONCLUSION: There is low reporting of data related to external validity in reports of RCTs assessing pharmacologic and nonpharmacologic treatments for hip and knee OA.
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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 | 0.840 | 0.957 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.003 | 0.025 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".