Reporting of Clinical Trial Interventions Published in Leading Otolaryngology–Head and Neck Surgery Journals
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Randomized controlled trials (RCTs) play a crucial role in advancing patient care within otolaryngology-head and neck surgery (OTL-HNS), yet studies have shown the reporting of these trials needs improvement. Here, we evaluate the completeness of intervention reporting of RCTs in OTL-HNS and evaluate whether the publication of the Template for Intervention Description and Replication (TIDieR) checklist has influenced intervention reporting. STUDY DESIGN: Retrospective Cross-Sectional Analysis. METHODS: We searched PubMed for RCTs published in top OTL-HNS journals in two cohorts, one before the release of the TIDieR and one afterward. A sample of 300 RCTs was randomly selected and screened for inclusion. Once the dataset was finalized, we extracted trial characteristics and assessed each trial's adherence to the TIDieR checklist. We then used descriptive characteristics, a generalized estimated equation, time-series analysis, and a two-sample t test to analyze our data. RESULTS: After screening was completed, 173 RCTs were included in our analysis. Of these RCTs, 103 (59.5%) showed <60% adherence to the TIDieR checklist. We found a slight increase in adherence to TIDieR items after the checklist was released, although this was not statistically significant (P = .91). In addition, we found that trials with a crossover study design or multiple interventions and those that provided a Consolidated Standards for Reporting Trials statement were associated with greater adherence to the TIDieR checklist. CONCLUSIONS: The majority of OTL-HNS RCTs included in our analysis showed suboptimal reporting factors related to the TIDieR checklist. Requiring a TIDieR statement and automating the journal requirements process for all OTL-HNS clinical trials would be a worthwhile, efficient approach to improving research quality and ultimately patient care within OTL-HNS. LEVEL OF EVIDENCE: NA Laryngoscope, 130:E507-E514, 2020.
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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 | 0.720 | 0.920 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.040 | 0.034 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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, 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".