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

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.