Junna, Mithri R.

Abstract Introduction Hypoglossal nerve stimulation (HGNS) is an effective therapy for moderate-to-severe obstructive sleep apnea (OSA) in patients intolerant of positive airway pressure. Comorbid insomnia (COMISA) is common and may shape their engagement. Despite reports of improved insomnia symptoms, real-world data suggest reduced adherence and increased support needs. This study evaluated the impact of COMISA on HGNS therapy patterns and outcomes. Methods We conducted a retrospective cohort study of 46 adults with OSA who underwent HGNS implantation at Mayo Clinic Rochester between July 2020 and August 2025. Patients were categorized as OSA alone or COMISA based on pre-implantation data, including documented insomnia diagnosis, insomnia severity index score ≥15, sleep initiation or maintenance complaints, hypnotic or melatonin use, participation in cognitive behavioral therapy for insomnia, or an insomnia care plan within one year prior to activation. We collected HGNS adherence metrics (30-day average nightly use, nightly pauses, percent nights used) at 1, 3, 6, and 12 months; non-visit HGNS-related clinical encounters at 6 and 12 months; and pre- and post-activation AHI from polysomnography or home sleep apnea testing. Longitudinal outcomes were analyzed using mixed-effects models with fixed effects for time and COMISA status and a random intercept for patient. Results The cohort was 54% male and 98% White, with median age 66 years and BMI 31 kg/m2 (24–34). Median pre-implant AHI was 27 (19–40), and 30 patients (65%) had COMISA. Median nightly HGNS use declined from 7.8 to 6.6 hours from 1 to 12 months; mixed-effects modeling confirmed significant decreases over time (p≤0.03). Median nightly therapy pauses increased from 0.1 to 0.5, and median non-visit clinical encounters increased cumulatively from 2.5 at 6 months to 3.0 by 12 months (both p≤0.01). Median AHI reduction was 18.5 (2–27) (p=0.047). There were no statistically significant differences between OSA-alone and COMISA groups in HGNS adherence trajectories, therapy pauses, support needs, or AHI improvement (all p>0.05). Conclusion Although HGNS use declined modestly over time, COMISA was not statistically associated with differences in adherence, clinical support needs, or treatment response. Directional trends suggest greater adaptation challenges among patients with COMISA, warranting evaluation in larger prospective studies. Support (if any)

Abstract Introduction Isolated REM sleep behavior disorder (iRBD) is characterized by loss of normal REM sleep atonia and dream enactment behavior. iRBD is strongly associated with α-synucleinopathies and risk for developing Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA), yet phenoconversion risk for long-term outcomes of younger women and men remains undefined. We aimed to ascertain longitudinal outcomes and phenoconversion risk in the Mayo Clinic iRBD cohort. Methods Eighty-nine of 165 registry participants with at least one-year follow-up were included. Retrospective chart review attained baseline demographics, age at presentation, baseline Timed Up and Go (TUG) and Montreal Cognitive Assessment (MoCA) scores, and phenoconversion status (iRBD, PD, DLB, mild cognitive impairment [MCI], MSA, or other). Kaplan–Meier survival analysis and Cox proportional hazards modeling were analyzed with alpha at p < 0.05. Results 68 men and 21 women had a mean age of 63 years at polysomnographic diagnosis. At follow-up, 64 (71.9%) remained iRBD; 7 (7.9%) developed PD, 11 (12.4%) developed DLB, 3 (3.4%) developed MCI, 1 (1.1%) developed MSA, and 3 (3.4%) developed another dementia. Abnormal TUG (>12 seconds) occurred in 5.9% and abnormal MoCA (< 24) in 23.3%. Phenoconversion rates were similar in women and men (p = 0.44). Older age at PSG predicted phenoconversion, corresponding to a two-fold increase in risk with each 10-year increase (HR 2.00, 95% CI 1.15–3.52). Neither abnormal TUG nor MoCA predicted conversion. Cumulative phenoconversion was approximately 1% at 1 year, 7% at 3 years, 10% at 5 years, 30% at 10 years, 34% at 12 years, and 49% at 15 years. Mean and median time to phenoconversion was 7 years (range, 1-18 years). Conclusion We found that iRBD phenoconversion rates were lower than historically reported. Only age at presentation predicted phenoconversion, with risk doubling per decade. At 12 years, cumulative phenoconversion rate was approximately 34%. Support (if any)

Background: The COVID-19 pandemic brought profound changes to health care systems worldwide. This study examines the adaptive responses of a sleep medicine practice that successfully pivoted to telemedicine, remote diagnostics, and agile operations, resulting in sustained growth and improved patient accessibility. Methods: We analyzed organizational and cultural elements enabling responsiveness, including telemedicine infrastructure, adaptive leadership, quality-focused processes, and effective communication. Objective outcomes were assessed by analyzing patient demographics, telemedicine visits, and sleep testing patterns during three phases: pre-pandemic (June 1, 2018 to March 8, 2020), acute COVID-19 (March 9, 2020 to April 19, 2020), and post-acute COVID-19 (April 20, 2020 to December 31, 2021). Results: Across 105,199 encounters, monthly sleep medicine visits and testing declined ∼50% during acute COVID-19, but rebounded to surpass baseline in the post-acute phase. Virtual visits increased significantly, replacing many face-to-face encounters. Home sleep apnea test use rose sharply, driven by disposable WatchPAT tests, while polysomnography use decreased. Testing volumes increased overall post-acute compared with pre-pandemic. Patients served during acute and post-acute phases were younger, more often female, non-White, and postgraduate-educated (all p < 0.001). Nonlocal patients increased during the post-acute phase, reflecting telemedicine expansion. Conclusions: Proactive telemedicine investments, adaptive leadership, quality-focused processes, and effective communication enabled this practice to adapt successfully during the pandemic. These resilience strategies provide a model for navigating future health care challenges, underscoring telemedicine and e-health’s critical roles in maintaining care delivery during crises.