Laryngoscopic findings of age‐related vocal fold atrophy are reliable but not specific
Bibliographic record
Abstract
OBJECTIVES: We aimed to evaluate the reliability of laryngoscopic features of vocal fold atrophy as assessed by novice otolaryngology trainees and expert laryngologists. DESIGN: Two expert fellowship-trained laryngologists and three non-expert otolaryngology resident trainees were recruited to view 50 anonymised laryngo-stroboscopic examinations of patients presenting with dysphonia and non-voice, laryngeal complaints. Reviewers were asked to stratify the patient's age, provide an opinion about the presence of age-related vocal fold atrophy and specify which laryngoscopy features were present to make the diagnosis. SETTING: Tertiary care laryngology practice. PARTICIPANTS: Two fellowship-trained laryngologists and three trainee otolaryngologists. MAIN OUTCOME MEASURES: Accuracy of age categorisation was determined and Kappa analysis was performed to assess inter-rater agreement. RESULTS: The mean age of patients was 54.9 years old with near equal male to female distribution. The overall accuracy of age category determination by raters was only 30.8%. Kappa analysis demonstrated fair agreement regarding the presence of vocal fold atrophy in non-expert reviewers, and moderate agreement amongst expert reviewers. Features of glottic gap, muscular atrophy of vocal folds and prominent vocal processes were all identified with high agreement (>80.0%). CONCLUSION: Our study illustrates that while raters can agree on the presence of age-related vocal fold atrophy, the findings may be non-specific and do not necessarily correlate with age.
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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 | 0.013 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".