Benefit of Repeat Multiple Sleep Latency Testing in Confirming a Possible Narcolepsy Diagnosis
Bibliographic record
Abstract
PURPOSE: The clinical diagnosis of narcolepsy is usually uncomplicated in the presence of cataplexy. Objective testing is more important in ambiguous disease. The gold-standard objective test in these cases is the multiple sleep latency test (MSLT). Repeat testing can be burdensome but is reasonable when faced with a diagnostic dilemma. However, there is limited evidence to support this approach. In this study, we assessed the diagnostic utility of a repeat MSLT in patients suspected of narcolepsy whose first MSLT result was nonconfirmatory. METHODS: Of 125 patients who underwent an MSLT between 2004 and 2009, we identified 10 (9.6%) who had undergone repeat studies. We analyzed changes in MSLT parameters while taking account of other relevant differences between testing. RESULTS: Two patients (20%) met narcolepsy criteria during the second MSLT. Nine patients (90%) met sleepiness criteria (mean sleep latency <8 minutes) during the second MSLT while only 5 did during the first (P = 0.05). CONCLUSIONS: We demonstrate that a repeat MSLT confirmed the diagnosis of narcolepsy in 20% of patients whose results had been nonconfirmatory on a first MSLT. This study provides support for a repeat MSLT in cases where clinical suspicion for narcolepsy is high despite an ambiguous first test.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".