Auto-adjusting and advanced positive airway pressure therapeutic modalities.

Continuous positive airway pressure (CPAP) therapy is the first-line treatment for obstructive sleep apnea (OSA). Although the gold standard for the treatment of OSA, CPAP may not be the optimal modality to treat more complex sleep disordered breathing such as Cheyne-Stokes respirations, opioid-induced central apnea, and complex sleep disordered breathing related to chronic hypoventilation syndromes (obesity-hypoventilation syndrome, restrictive thoracic disease due to neuromuscular or thoracic cage disease, chronic obstructive pulmonary disease). Newer generation auto-adjusting PAP devices are increasingly being used to treat OSA. Advanced positive airway pressure modalities have been developed in an effort to improve treatment of the more complex sleep disordered breathing syndromes including automated servo ventilation and volume-targeted pressure-limited ventilation. This article is intended to provide the clinician reader with a description of newer PAP modalities, a review of evidence-supported indications for use, as well as to provide a framework for managing patients with advanced positive airway pressure therapy.

Hypoglossal nerve stimulation over-titration.

This case report reviews worsening obstructive sleep apnea (OSA) events in a patient over-titrated with a hypoglossal nerve stimulator. A healthy 57-year-old man underwent hypoglossal nerve stimulator implantation for moderate OSA. During an in-laboratory hypoglossal nerve stimulator titration the patient had improvement of his OSA at 2.1 V. However, a further increase of voltage resulted in worsening of obstructive events. The pathophysiology behind this finding is unknown but may result from unfavorable changes in the upper anatomy due to higher energy delivered to the hypoglossal nerve and surrounding structures. This high energy may also lead to genioglossus muscle fatigue. This finding highlights the importance of hypoglossal nerve stimulation titration with a dedicated sleep study. CITATION: Chang M, Moore V, Eng K, Ryden A, Zeidler M. Hypoglossal nerve stimulation over-titration. J Clin Sleep Med. 2024;20(6):999-1001.

The effectiveness of cognitive behavioral therapy for insomnia on sleep outcomes in the context of pain among older adult veterans.

BACKGROUND: Cognitive behavioral therapy for insomnia (CBT-I) is the gold-standard treatment for insomnia disorder in adults. Compared to young adults, older adults have increased risk for the development of conditions associated with chronic pain, which may impact the efficacy of CBT-I in improving insomnia symptoms in older adults. This study evaluated the effect of participant-rated pain on sleep-related outcomes of a supervised, non-clinician administered CBT-I program in older adult patients with chronic insomnia disorder. METHODS: Secondary analysis was conducted using data from a randomized controlled trial among 106 community-dwelling older adult veterans (N = 106; mean age 72.1 years, 96% male, 78.3% White, 6.6% Hispanic, 5.7% African American) with chronic (≥3 months) insomnia disorder. Participants engaged in five sessions of manual-based CBT-I in individual or group format within one Department of Veterans Affairs healthcare system, provided by non-clinician "sleep coaches" who had weekly telephone supervision by behavioral sleep medicine specialists. Insomnia symptoms (Insomnia Severity Index), perceived sleep quality (Pittsburgh Sleep Quality Index), fatigue (Flinder's Fatigue Scale), daytime sleepiness (Epworth Sleepiness Scale), and perceived pain severity (items from the Geriatric Pain Measure) were assessed at 4 time points: baseline, one-week posttreatment, 6-month follow-up, and 12-month follow-up. Mixed effects models with time invariant and time varying predictors were employed for analyses. RESULTS: CBT-I improved insomnia symptoms, perceived sleep quality, fatigue, and daytime sleepiness among older veterans with chronic insomnia. Participant-reported pain was associated with greater improvements in insomnia symptoms following CBT-I. Pain did not affect improvements in other sleep-related outcomes (-0.38 ≤ b ≤ 0.07, p > 0.05). Between-subjects differences in pain, but not within-subject changes in pain over time, appeared to play a central role in insomnia symptom improvement at posttreatment, with individuals with higher-than-average pain showing greater insomnia symptom improvement (ISI score reduction; -0.32 ≤ b ≤ -0.28, p ≤ 0.005). CONCLUSIONS: Pain did not meaningfully hinder the effects of CBT-I on sleep outcomes. Among older veterans with chronic insomnia disorder, individuals with higher pain exhibited slightly greater improvement in insomnia than those with lower levels of pain. These findings suggest that experiencing pain does not impair treatment response and should not preclude older adults with insomnia from being offered CBT-I.

Racial disparities in positive airway pressure therapy adherence among veterans with obstructive sleep apnea.

STUDY OBJECTIVES: Black individuals are disproportionately affected by diabetes, cardiovascular disease, obesity, and OSA. Adherence to PAP therapy has been reported to be lower among black individuals. This study seeks to examine associations between black race and PAP adherence among veterans with OSA. METHODS: This was a retrospective study. Veterans newly diagnosed with OSA at a single Department of Veterans Affairs sleep center who were prescribed a modem-enabled PAP device between January 2015 and November 2017 were enrolled. PAP adherence was defined as ≥ 4 hours nightly usage for at least 70% of nights measured at 30 days from PAP setup. We examined the relationship between race and adherence, controlling for sex, marital status, age, socioeconomic status, residual apnea-hypopnea index), and mask leak. RESULTS: Of 3013 patients identified with OSA, 2571 (85%) were newly started on PAP therapy (95% male, aged 59 years ± 14 years, 45% married, 8% with neighborhood socioeconomic disadvantage). Twenty-five percent of participants were black, and 57% were white. PAP adherence at 30 days was 50% overall (42% among blacks, 53% among nonblacks). Black race was associated with reduced 30-day PAP adherence in unadjusted (P < .001) and adjusted logistic regression models (odds ratio = 0.64; 95% CI, 0.53 - 0.78; P < .001). CONCLUSIONS: Among veterans with OSA, black race was associated with reduced PAP adherence. These findings suggest health inequality among black individuals in the treatment of OSA.

A 38-Year-Old Man With Well Treated OSA on CPAP With Persistent Nocturnal Hypoxemia.

CASE PRESENTATION: A 38-year-old male with a prior diagnosis of severe OSA (apnea-hypopnea index [AHI] 99/h) presented for transfer of care. He was successfully titrated to CPAP of 10 cm H2O at an outside laboratory and was compliant with therapy with residual AHI 1.9/h. On presentation, he was polycythemic, with negative evaluation for primary polycythemia, and evaluation for hypoxemia was initiated.

Insomnia Disorder Among Older Veterans: Results of a Postal Survey.

STUDY OBJECTIVES: To estimate the prevalence of insomnia disorder among older veterans and to study relationships among age and self-rated health, with insomnia disorder, self-reported sleep duration and sleep efficiency. METHODS: A cross-sectional postal survey of community-dwelling older veterans (older than 60 years) seen at one VA Healthcare System in the prior 18 months was performed, which was constructed to align with the general diagnostic criteria for insomnia disorder (International Classification of Sleep Disorders, Second Edition [ICSD-2]). The survey also queried self-reported sleep duration, bedtime, and wake time, which were used to calculate sleep efficiency. The survey also asked about race/ethnicity and self-rated health (using the general health item from the Short Form-36). RESULTS: A completed survey was returned by 4,717 individuals (51.9% response rate; mean age 74.1 years). Of those, 2,249 (47.7%) met ICSD-2 diagnostic criteria for insomnia disorder. In logistic regression analyses, insomnia disorder was more likely among younger age categories (odds ratios [OR] 1.4-2.5) and in those with worse self-rated health (OR 2.1-14.4). Both total nocturnal sleep time and time in bed increased with older age (all P < .001), whereas sleep efficiency did not differ. Worse self-rated health was associated with shorter total nocturnal sleep time, more time in bed, and lower (worse) sleep efficiency. CONCLUSIONS: Results of the postal survey suggest that almost half of community-dwelling older veterans have insomnia disorder, which was more common in young-old and among those with worse self-rated health. Additional work is needed to address the high burden of insomnia among older adults, including those with poor health.

Predicting Nondiagnostic Home Sleep Apnea Tests Using Machine Learning.

STUDY OBJECTIVES: Home sleep apnea testing (HSAT) is an efficient and cost-effective method of diagnosing obstructive sleep apnea (OSA). However, nondiagnostic HSAT necessitates additional tests that erode these benefits, delaying diagnoses and increasing costs. Our objective was to optimize this diagnostic pathway by using predictive modeling to identify patients who should be referred directly to polysomnography (PSG) due to their high probability of nondiagnostic HSAT. METHODS: HSAT performed as the initial test for suspected OSA within the Veterans Administration Greater Los Angeles Healthcare System was analyzed retrospectively. Data were extracted from pre-HSAT questionnaires and the medical record. Tests were diagnostic if there was a respiratory event index (REI) ≥ 5 events/h. Tests with REI < 5 events/h or technical inadequacy-two outcomes requiring additional testing with PSG-were considered nondiagnostic. Standard logistic regression models were compared with models trained using machine learning techniques. RESULTS: Models were trained using 80% of available data and validated on the remaining 20%. Performance was evaluated using partial area under the precision-recall curve (pAUPRC). Machine learning techniques consistently yielded higher pAUPRC than standard logistic regression, which had pAUPRC of 0.574. The random forest model outperformed all other models (pAUPRC 0.862). Preferred calibration of this model yielded the following: sensitivity 0.46, specificity 0.95, positive predictive value 0.81, negative predictive value 0.80. CONCLUSIONS: Compared with standard logistic regression models, machine learning models improve prediction of patients requiring in-laboratory PSG. These models could be implemented into a clinical decision support tool to help clinicians select the optimal test to diagnose OSA.

Role of sleep duration and quality in the risk and severity of type 2 diabetes mellitus.

BACKGROUND: Evidence from laboratory and epidemiologic studies suggests that decreased sleep duration or quality may increase diabetes risk. We examined whether short or poor sleep is associated with glycemic control in African Americans with type 2 diabetes mellitus. METHODS: We conducted a cross-sectional study of volunteers with type 2 diabetes interviewed at the University of Chicago Hospitals, Chicago, Ill. The final analysis included 161 participants. Glycemic control was assessed by hemoglobin A1c (HbA1c) level obtained from medical charts. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Perceived sleep debt was calculated as the difference between preferred and actual weekday sleep duration. RESULTS: The mean +/- SD sleep duration was 6.0 +/- 1.6 hours, and 71% of the participants were classified as having poor quality sleep (PSQI score >5). We excluded patients with sleep frequently disrupted by pain (n = 39). In patients without diabetic complications, glycemic control was associated with perceived sleep debt but not PSQI score. The predicted increase in HbA1c level for a perceived sleep debt of 3 hours per night was 1.1% above the median. In patients with at least 1 complication, HbA1c level was associated with PSQI score but not perceived sleep debt. The predicted increase in HbA1c level for a 5-point increase in PSQI was 1.9% above the median. CONCLUSIONS: In our sample, sleep duration and quality were significant predictors of HbA1c, a key marker of glycemic control. Combined with existing evidence linking sleep loss to increased diabetes risk, these data suggest that optimizing sleep duration and quality should be tested as an intervention to improve glucose control in patients with type 2 diabetes.