Technical Challenges for Laryngeal Electromyography
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Laryngeal electromyography (LEMG) is a useful diagnostic test in the evaluation of vocal fold paralysis (VFP). This study investigates factors that can make LEMG challenging to perform. METHODS: Patients with subacute unilateral VFP presented for LEMG were prospectively enrolled. Demographic data including BMI, previous neck surgery, and anatomic factors were collected. Patient-reported pain related to the procedure was recorded on a visual analogue scale (VAS). Electromyographer and otolaryngologist recorded a consensus rating of the perceived difficulty in performing the test and confidence in using the results for clinical decision-making. RESULTS: A total of 111 patients (56.8% female) were enrolled between August 2015 and August 2018. The mean age was 55 ± 14 years, and the average body mass index (BMI) was 28.5 ± 6.4. The mean patient-reported VAS score for pain was 35 ± 24. Notably, 31.2% of the tests were considered "very easy," 32.1% were considered "mildly challenging" and 23.9% and 12.8% were considered "moderately challenging" and "extremely challenging," respectively, by the clinicians. Common factors affecting LEMG difficulty included poorly palpable surface anatomy (50.5%) and patient intolerance (15.6%). Clinicians felt confident in 76.1% of the test findings. Bivariate analyses showed that prior neck surgery is associated with elevated VAS (p = 0.02), but clinician-perceived difficulty of performing the test is not associated with elevated VAS scores (p = 0.55). CONCLUSIONS: Majority of LEMG tests are well tolerated by patients. Physicians reported more confidence using LEMG for clinical decision-making when the test was easier to perform. Difficult surface anatomy and patient intolerance affects clinician confidence in integrating the test results with clinical care. LEVEL OF EVIDENCE: 3 Laryngoscope, 134:831-834, 2024.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".