1364 An Unexpected Diagnosis for Persistent Hypersomnia with a Wearable Consumer Health Tracker

Abstract Introduction An increasing number of wearable consumer health trackers (CHTs) for sleep are being used by patients. Validation studies comparing CHTs to gold standard polysomnography (PSG) are variable and inconsistent. In 2025, the World Sleep Society recommended pragmatic use of CHTs for sleep monitoring while understanding the limitations of the devices. We present a case of an unexpected diagnosis for hypersomnia found with a CHT. Report of case(s) A 61-year-old male with a history of type 1 narcolepsy, severe obstructive sleep apnea (OSA) on bilevel positive airway pressure (BiPAP), restless leg syndrome, hypertension, and right hemidiaphragm paralysis presented with persistent hypersomnia. Despite being 100% compliant with BiPAP and on a sodium oxybate for narcolepsy and gabapentin for RLS control, he continued to have excessive daytime fatigue causing an inability to remain employed and multiple motor vehicle accidents. He had trialed multiple wake-promoting agents, but each led to significant side effects requiring discontinuation. A two-week sleep diary (Figure 1) was consistent with an irregular sleep-wake cycle rhythm disorder. While adjusting his medications and optimizing his sleep schedule, he began to wear a CHT. He was able to makeshift the battery so he could track his sleep-wake cycle continuously. Data from his CHT was consistent with a non-24 circadian rhythm disorder (Figure 2). He was started on tasimelteon, a melatonin MT1 and MT2 receptor agonist, daily. Subsequent CHT data showed resolution of his non-24 circadian rhythm disorder (Figure 3) with improvement of his daytime hypersomnia symptoms. Conclusion Wearable CHTs can provide informative data on sleep-wake cycle and sleep architecture. However, accuracy of this data can vary from device to device. Often data from CHTs are incidentally presented to providers; providers should be aware of limitations of these devices when utilizing the data clinically. Limitations of CHTs include detecting exact wake-sleep transition, accuracy of sleep staging, limited regulation of devices, and limited understanding of underlying proprietary algorithms interpreting raw data. Despite these limitations, data from CHTs can be clinically useful, as in this patient. Providers are recommended to focus on trends and patterns from CHTs and remain up to date in evolving best practice recommendations for use. Support (if any)