Blinding of Outcomes in Trials of Orthopaedic Trauma: An Opportunity to Enhance the Validity of Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Blinding personnel in randomized controlled trials is an important strategy to minimize bias and increase the validity of the results. Trials of surgical interventions present blinding challenges not seen in drug trials. How often orthopaedic trauma investigators undertake blinding, and the frequency with which they could potentially utilize blinding, remains uncertain. METHODS: We conducted a systematic review of all randomized controlled trials of orthopaedic trauma published from 1995 to 2004. Two reviewers assessed each trial for eligibility and extracted data regarding its characteristics, outcomes, reporting of blinding, and feasibility of blinding. RESULTS: We included 171 unique randomized controlled trials spanning a variety of body regions and interventions. The most commonly reported outcomes were clinical (e.g., mortality or wound infection; 91% of trials), radiographic (83%), patient-reported (66%), and physiological results (e.g., range of motion; 56%). Less than 10% of the trials in each category reported the use of blinded outcome assessors. This contrasted with blinding that investigators could have accomplished: blinding was feasible with use of simple methods such as independent assessors, concealed incisions, and masked radiographs for 89% of clinical assessors, 89% of radiographic assessors, 96% of physiological assessors, and 35% of patient-reported assessors. CONCLUSIONS: Trials in orthopaedic trauma typically measure many outcomes requiring judgment, but the individuals assessing those outcomes are seldom blinded. Investigators have the opportunity to enhance the validity of future clinical trials by incorporating simple blinding techniques.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
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 | 0.898 | 0.948 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.024 | 0.017 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.019 | 0.029 |
| Open science | 0.008 | 0.014 |
| Research integrity | 0.022 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".