An actigraphy-based algorithm to assess daytime napping in people with narcolepsy type 1

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ID: 325614
2026
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Abstract
STUDY OBJECTIVES: Excessive daytime sleepiness is a defining symptom of narcolepsy, affecting daily functioning and quality of life. We developed and evaluated an actigraphy-based nap detection algorithm to objectively estimate daytime naps, a key manifestation of excessive daytime sleepiness. METHODS: The nap detection algorithm was developed using data from the Multi-Ethnic Study of Atherosclerosis. This dataset included manually annotated naps from 2237 participants with 7 days of wrist-worn actigraphy. The nap detection algorithm was then applied in studies of participants with narcolepsy type 1 (NT1). RESULTS: Our final nap detection algorithm yielded high specificity (Tau B: 93.2%) and accuracy (F1 Area: 83.9%). Applying our algorithm in an observational study (NCT04445129), participants with NT1 experienced 12.8 fewer nap-free days (p < .001) over 28 days and slept 34 min more (p < .001) during the day than controls. In a randomized clinical trial (NCT05687903), our algorithm demonstrated that participants with NT1 treated with an orexin receptor 2- selective agonist, oveporexton (TAK-861), experienced 6.1-11.9 additional nap-free days and slept 12-33 min fewer versus baseline. CONCLUSIONS: Overall, our nap detection algorithm retained sensitivity while minimizing false positives. It reliably identified nap-based phenotypes that differentiate individuals with NT1 from age and sex-matched healthy controls, and it demonstrated that an orexin receptor 2-selective agonist reduces napping in participants with NT1 to normative levels near those of healthy controls.
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openalex_W7203707451 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Raul Torres, Rahul Ghosal, Melissa Naylor, Simerpal K. Gill, Yelena Pyatkevich, Sarah Bermingham, Derek L. Buhl, Brian Tracey, Marta Karas, Francesco Onorati, Vadim Zipunnikov, Dmitri Volfson
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Journal Sleep & breathing = Schlaf & Atmung
Year 2026
DOI
10.1093/sleep/zsag219
URL
https://doi.org/10.1093/sleep/zsag219
Keywords Keywords not found

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