Levels of Evidence in Rhinology and Skull Base Surgery Research
Bibliographic record
Abstract
Objective The purpose of this study was to evaluate the quality of evidence of rhinology and rhinologic skull base surgery (RSBS) research and its evolution over the past decade. Study Design Review article. Setting We reviewed articles from 2007 to 2019 in 4 leading peer‐reviewed otolaryngology journals and 3 rhinology‐specific journals. Methods The articles were reviewed and levels of evidence were assigned using the Oxford Centre for Evidence‐Based Medicine 2011 guidelines. High quality was defined as level of evidence 1 or 2. Results In total, 1835 articles were reviewed in this study spanning a 13‐year period. Overall, the absolute number of RSBS publications increased significantly 22.6% per year, from 108 articles in 2007 to 481 in 2019 ( P <. 001; 95% CI, 7.9‐37.2). In 2007, only 13 articles, or 15%, were high quality, and this grew to 146 articles, or 39%, in 2019. A 14.0% per year exponential increase in the number of high‐quality publications was found to be statistically significant ( P <. 001; 95% CI, 7.2, 20.7). Overall, high‐quality publications represented just 25.8% of RSBS articles overall. There was no significant difference in quality between rhinology‐specific journals and general otolaryngology journals (χ 2 = 3.1, P =. 077). Conclusion The number of overall publications and of high‐quality RSBS publications has significantly increased over the past decade. However, the proportion of high‐quality studies continues to represent a minority of total RSBS research.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, not a consensus.
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".