Repetitive nerve stimulation cutoff values for the diagnosis of myasthenia gravis
Bibliographic record
Abstract
INTRODUCTION: Repetitive nerve stimulation (RNS) showing ≥ 10% decrement is considered the cutoff for myasthenia gravis (MG), but this has never been validated. The objective of this study was to find an optimal validated cutoff value for decrement on RNS. METHODS: We performed retrospective chart review of patients who had electrophysiological assessment for possible MG from 2013 to 2015. RESULTS: A total of 122 patients with MG and 182 controls were identified. RNS sensitivities for generalized and ocular MG using the traditional ≥10% cutoff value were 46% and 15%, respectively, for frontalis recordings, and 35% and 19%, respectively, for nasalis recordings. Using a decrement cutoff value of 7% for frontalis and 8% for nasalis increased the sensitivities by 6-11%, with specificities of 95-96%. CONCLUSIONS: For RNS in facial muscles, we suggest a cutoff value of 7-8%, which increases test sensitivity by 6-11%, while preserving high specificity for the diagnosis of MG. Muscle Nerve, 2016 Muscle Nerve 55: 166-170, 2017.
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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 | 0.002 | 0.007 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".