Reporting of Outcomes in Orthopaedic Randomized Trials
Bibliographic record
Abstract
BACKGROUND: Randomization, concealment of treatment allocation, and blinding are all known to limit bias in clinical research. Nonsurgical studies that fail to meet these standards have been reported to inflate the differences between treatment and control groups. While surgical trials can rarely blind surgeons or patients, they can often blind outcome assessors. The aim of this systematic review was threefold: (1) to examine the reporting of outcome measures in orthopaedic trials, (2) to determine the feasibility of blinding in published orthopaedic trials, and (3) to examine the association between the magnitude of treatment differences and the blinding of outcome assessors. METHODS: We identified and reviewed thirty-two randomized, controlled trials published in The Journal of Bone and Joint Surgery (American Volume) in 2003 and 2004 for the appropriate use of outcome measures. These trials represented 3.4% of all 938 studies published during that time-period. All thirty-two trials were reviewed by two authors for (1) the outcome measures used and (2) the blinding of outcomes assessors. We calculated the magnitude of the treatment effect of the use of blinded compared with unblinded outcome assessors. RESULTS: Ten (31%) of the thirty-two randomized controlled trials used a modified outcome instrument. Of the ten trials, four failed to describe how the outcome instrument was modified. Nine of the ten articles did not describe how the modified instrument was validated and retested. Sixteen of the thirty-two randomized controlled trials did not report blinding of outcome assessors when blinding would have been possible. Among the studies with continuous outcome measure, unblinded outcomes assessment was associated with significantly larger treatment effects than blinded outcomes assessment (standardized mean difference, 0.76 compared with 0.25; p = 0.01). Similarly, in the studies with dichotomous outcomes, unblinded outcomes assessments were associated with significantly greater treatment effects than blinded outcomes assessments (odds ratio, 0.13 compared with 0.42; p < 0.001). The ratio of odds ratios (unblinded to blinded outcomes assessment) was 0.31, suggesting that unblinded outcomes assessment was associated with a potential for exaggeration of the benefit of the effectiveness of a treatment in our cohort of studies. CONCLUSIONS: In future orthopaedic randomized controlled trials, emphasis should be placed on detailed reporting of outcome measures to facilitate generalization and the outcome assessors should be blinded, when possible, to limit bias.
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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 | 0.901 | 0.817 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.134 | 0.049 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".