Perceptions of pain of laryngeal electromyography
Bibliographic record
Abstract
OBJECTIVE: To evaluate pain associated with laryngeal electromyography (LEMG). STUDY DESIGN: A prospective case series. METHODS: Adult patients scheduled for LEMG in a tertiary care laryngology practice were recruited between July 20, 2016, and March 1, 2017. Demographic and clinical data were extracted from the charts. Study participants reported their anticipated pain level using a visual analog scale (VAS) prior to the procedure. VAS was administered again within 10 minutes after the procedure, along with the validated McGill Pain Questionnaire, to gauge patient's pain perception after undergoing LEMG. RESULTS: Results were reviewed for 80 patients (mean age 48.2 ± 16.6 years, 37.5% male). Preprocedure VAS pain scores (4.59 ± 2.3 out of 10) were not significantly different than postprocedure VAS pain scores (4.61 ± 2.4) (P = 0.95). The McGill Pain Questionnaire reported a moderate pain level (32.1 ± 12.7 out of 78). Females anticipated a higher preprocedure VAS pain score (5.04 ± 2.3) than males (3.85 ± 2.2) (P = 0.02); however, postprocedure scores were not significantly different between genders. The following factors did not influence the pain scores: age, professional voice use, history of previous EMG, chronic pain diagnosis, psychiatric diagnosis, or current treatment with pain/psychiatric medications. All LEMGs were completed without any complications. CONCLUSION: Patients appropriately anticipated their pain levels for the LEMG, which may be attributed to proper patient education and counselling before the procedure. Overall pain levels were mild to moderate, and all LEMGs were completed; thus, LEMG was well tolerated. LEVEL OF EVIDENCE: 4. Laryngoscope, 128:896-900, 2018.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".