Reporting quality of randomized controlled trials in otolaryngology: Review of adherence to the CONSORT statement
Bibliographic record
Abstract
BACKGROUND: Randomized controlled trials are the gold standard in medical and surgical research to assess the efficacy of therapeutic interventions. The reporting of these trials should be of high quality to allow readers' appropriate interpretation and application. METHODS: The objectives of our study were to assess the extent to which the recent Otolaryngology - Head and Neck Surgery (ORL-HNS) randomized control trials in the top nine journals and in the top Canadian journal comply with the Consolidated Standards of Reporting Trials (CONSORT) statement, and to identify the CONSORT items most in need of improvement. Based on the impact factor and circulation number of 2014, the top nine Otolaryngology journals and the top Canadian Otolaryngology journal were selected and were searched to identify RCTs published in English and between 2010 and 2014. Two authors independently reviewed and extracted data using a standardized data extraction form constructed with the help of a medical librarian. Our outcome was to assess the adherence of articles reporting to the CONSORT items. Descriptive statistics were used. RESULTS: One hundred and eighty-two Otolaryngologic RCTs were identified in the top nine international journals and in the top Canadian journal. The inter-rater reliability between two raters was 0.32. The extent of adherence to CONSORT Statement ranged from 25 to 93.5% with a mean of 59.0% and a median of 59.4%. Only 6.5% of RCTs described the individual responsible for enrolling and assigning subjects and method of randomization; 32.4% reported the estimated effect size and precision; 40.6% reported a sample size calculation and 32.4% mentioned external validity or implications of the findings. CONCLUSION: Findings revealed that the reporting of RCTs in the top nine ORL-HNS journals and in the top Canadian ORL-HNS journal is suboptimal. The quality of reporting can be improved by addressing the three CONSORT items found most deficient in this study namely, sample size calculations, estimated effect size and precision, and external validity.
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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 | 0.693 | 0.873 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.018 | 0.026 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".