Computed tomography has low yield in the evaluation of idiopathic unilateral true vocal fold paresis
Bibliographic record
Abstract
OBJECTIVE/HYPOTHESIS: To determine the clinical yield of neck and chest computed tomography in the initial assessment of patients with idiopathic unilateral true vocal fold paresis. STUDY DESIGN: Retrospective chart review. METHODS: A retrospective chart review of consecutive adult patients with idiopathic unilateral true vocal fold paresis diagnosed by stroboscopy in a tertiary-care voice center from 2003 to 2010. RESULTS: There were 176 patients with unilateral vocal fold paresis of which 81 subjects had idiopathic unilateral true vocal fold paresis. Of these, 60 patients (74.1%) had a computed tomography workup. Fifty-nine patients (98.3%) had a normal computed tomography while one patient had a single mediastinal lymph node that was PET-CT negative. This demonstrates an initial 1.7% yield and ultimate 0% yield of the computed tomography workup. CONCLUSION: Our results suggest that computed tomography workup has a low yield for occult neck and mediastinal pathology in patients with idiopathic unilateral true vocal fold paresis. Chest and neck computed tomography may not be clinically beneficial provided the patient has good otolaryngologic and medical follow-up.
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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 | 0.001 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".