Impaired Vigilance in Patients with Narcolepsy Type 1: A Psychomotor Vigilance Task Study
Bibliographic record
Abstract
Purpose: The psychomotor vigilance task (PVT) is one of the main methods to measure sustained vigilance/attention in sleep research. Vigilance is the main factor affecting daytime function in patients with narcolepsy type 1 (NT1). We aimed to quantify the negative effects of sleep-wake disorders on vigilance and investigate potential neural mechanisms. Patients and Methods: We compared data from 42 patients and 31 healthy controls, including sociodemographics, nighttime sleep quality (Pittsburgh Sleep Quality Index, PSQI), sleepiness (Epworth Sleepiness Scale, ESS), cognitive abilities (Montreal Cognitive Assessment, MoCA), emotional control (Barratt Impulsiveness Scale-11, BIS-11), depressive symptoms (Patient Health Questionnaire-9, PHQ-9), and PVT performance. PVT outcomes analyzed included number of lapses, reaction time (RT), variability in RT, and the slowest and fastest 10% of RTs. All patients were diagnosed with NT1 based on The International Classification of Sleep Disorders-Third Edition. Results: Patients with NT1 had a significantly higher body mass index and longer duration of education than healthy controls. The patients also had a greater tendency for daytime sleepiness and poorer nighttime sleep quality, higher depression and impulsiveness scores, and more severe cognitive dysfunction. PVT performance was better in the healthy controls than in patients with NT1. We also noticed that emotional changes and the proportion of rapid eye movement sleep at night are related to PVT performance. Conclusion: More severe sleepiness and an increased emotional burden could underlie the arousal and vigilance deficits seen in patients with NT1. We speculate that impaired vigilance in patients with NT1 is associated with abnormal brain function caused by a resource allocation imbalance related to hypothalamic orexin neuron damage, sleep inertia may also have a slight impact on this. Future studies should delve into this topic more deeply.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".