Diagnostic value of actigraphy in hypersomnolence disorders

The Swiss Primary Hypersomnolence and Narcolepsy Cohort Study: feasibility of long-term monitoring with Fitbit smartwatches in central disorders of hypersomnolence and extraction of digital biomarkers in narcolepsy

The Swiss Primary Hypersomnolence and Narcolepsy Cohort Study (SPHYNCS) is a multicenter research initiative to identify new biomarkers in central disorders of hypersomnolence (CDH). Whereas narcolepsy type 1 (NT1) is well characterized, other CDH disorders lack precise biomarkers. In SPHYNCS, we utilized Fitbit smartwatches to monitor physical activity, heart rate, and sleep parameters over 1 year. We examined the feasibility of long-term ambulatory monitoring using the wearable device. We then explored digital biomarkers differentiating patients with NT1 from healthy controls (HC). A total of 115 participants received a Fitbit smartwatch. Using a adherence metric to evaluate the usability of the wearable device, we found an overall adherence rate of 80% over 1 year. We calculated daily physical activity, heart rate, and sleep parameters from 2 weeks of greatest adherence to compare NT1 (n = 20) and HC (n = 9) participants. Compared to controls, NT1 patients demonstrated findings consistent with increased sleep fragmentation, including significantly greater wake-after-sleep onset (p = .007) and awakening index (p = .025), as well as standard deviation of time in bed (p = .044). Moreover, NT1 patients exhibited a significantly shorter REM latency (p = .019), and sleep latency (p = .001), as well as a lower peak heart rate (p = .008), heart rate standard deviation (p = .039) and high-intensity activity (p = .009) compared to HC. This ongoing study demonstrates the feasibility of long-term monitoring with wearable technology in patients with CDH and potentially identifies a digital biomarker profile for NT1. While further validation is needed in larger datasets, these data suggest that long-term wearable technology may play a future role in diagnosing and managing narcolepsy.

The actigraphic evaluation of daytime sleep in central disorders of hypersomnolence: comparison with polysomnography

STUDY OBJECTIVES

The role of actigraphy in central disorders of hypersomnolence (CDH) is expanding but evidence of reliability with polysomnography (PSG) is scarce and provided only during nighttime. We explored the agreement between actigraphy and continuous 24-hour PSG at CDH diagnosis.

METHODS

Forty-four consecutive drug-naïve patients (28 narcolepsy, 16 idiopathic hypersomnia) underwent actigraphy during 24 hours of free-running PSG, during multiple sleep latency test (MSLT) and 13 of them also during maintenance of wakefulness test (MWT). Daytime and nighttime sleep features and MSLT and MWT mean sleep latencies (mSL) were estimated with the actigraphic algorithms by Cole-Kripke (CK) Sadeh, and University of California San Diego (UCSD). Agreement to corresponding PSG measures was assessed with Bland Altman plots.

RESULTS

Nighttime-total sleep time (TST) in narcolepsy was significantly underestimated with CK (bias 27.8 min, 95%CI 13.7-41.9) and Sadeh (bias 56.7 min, 95%CI 38.8/74.5). Daytime-TST was overestimated in IH and narcolepsy with all algorithms (CK: bias -42.2, 95%CI -67/-17.4; Sadeh: bias -30.2 min, 95%CI -52.7/-7.7; UCSD bias -86.9 min, 95%CI -118.2/-55.6). 24-hour-TST was overestimated by CK and UCSD in IH (CK: bias -58.5 min, 95%CI -105.5/-11.5; UCSD: bias -118.8 min, 95% CI -172.5/-65), and by UCSD in narcolepsy (bias -68.8 min, 95%CI -109.3/-38.2). In the entire cohort, actigraphy overestimated MSLT mSL but not MWT mSL.

CONCLUSIONS

Conventional actigraphic algorithms overestimate 24-hour TST in IH and underestimate nighttime TST in narcolepsy. These discrepancies call for cautious application of actigraphy in the diagnostic process of CDH and the development of new quantitative signal analysis approaches.

Current Understanding of Narcolepsy 1 and its Comorbidities: What Clinicians Need to Know

Narcolepsy is a chronic neurologic disorder associated with the dysregulation of the sleep–wake cycle that often leads to a decreased quality of life and results in a considerable health burden. There is often a delay to diagnosis of narcolepsy, mainly due to the lack of recognition of this disorder. One of the main factors hindering the diagnosis of narcolepsy is the association of comorbidities, which include other sleep disorders, psychiatric disorders, cardiovascular disorders, and metabolic disorders. The signs and symptoms of these comorbidities often overlap with those of narcolepsy, and some of the medications used for their treatment may obscure the symptoms of narcolepsy, leading to a delay in diagnosis. This review is targeted to clinicians unaccustomed to working with sleep disorders and aims to increase recognition and improve the management of narcolepsy.