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Study objectivesSleep is an important dimension in the care of chronic obstructive pulmonary disease (COPD), but its relevance to exacerbations is unclear. We wanted to assess whether sleep quality as measured by the Pittsburgh Sleep Quality Index (PSQI) is associated with an increased risk of COPD exacerbations and does this differ by socio-environmental exposures.MethodsWe included 1647 current and former smokers with spirometrically confirmed COPD from the SPIROMICS cohort. We assessed incidence rate ratios for exacerbation using zero-inflated negative binomial regression adjusting for demographics, medical comorbidities, and multiple metrics of disease severity, including respiratory medications, airflow obstruction, and symptom burden. Our final model adjusted for socio-environmental exposures using the Area Deprivation Index, a composite measure of contemporary neighborhood quality, and Adversity-Opportunity Index, a composite measure of individual-level historic and current socioeconomic indicators. We used a pre-determined threshold of 20% missingness to undertake multiple imputation by chained equations. As sensitivity analyses, we repeated models in those with complete data and after controlling for prior exacerbations. As an exploratory analysis, we considered an interaction between socio-environmental condition and sleep quality.ResultsAfter adjustment for all co-variates, increasing PSQI scores (range 0-21) were associated with a 5% increased risk for exacerbation per point (p = .001) in the imputed dataset. Sensitivity analyses using complete cases and after controlling for prior exacerbation history were similar. Exploratory analysis suggested less effect among those who lived in poor-quality neighborhoods (p-for-interaction = .035).ConclusionsPoor sleep quality may contribute to future exacerbations among patients with COPD. This represents one target for improving disease control.Clinical trial registrationSubpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS). ClinicalTrials.gov Identifier# NCT01969344. Registry URL: https://clinicaltrials.gov/ct2/show/.

Rationale: Comorbidity is a significant driver of health status and healthcare utilization in chronic obstructive pulmonary disease (COPD). Obstructive sleep apnea (OSA) portends poorer outcomes, whereas obesity is protective. Objectives: We describe the prevalence and influence of these comorbidities on COPD readmissions. Methods: We collated discharge records for COPD exacerbations spanning 2010-2016 from the Nationwide Readmissions Database using Medicare's Hospital Readmissions Reduction Program criteria, with OSA-COPD overlap identified by concomitant diagnosis code for OSA. We used mixed-effects logistic regression to predict readmission odds. A cross-sectional mediation analysis was performed to evaluate the extent that OSA attenuated obesity's impact on readmission. Results: Of 1,662,983 qualifying COPD discharges, 19.1% carried a diagnosis of obesity and 12.9% had OSA, with both diagnoses present in 7.8%. In unadjusted analyses, obesity (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.03-1.05; P

Study objectivesTo evaluate the clinical utility of actigraphy as compared with sleep questionnaires prior to the Multiple Sleep Latency Test (MSLT) in a sleep disorders clinic population.MethodsTwenty-eight clinically referred participants (mean age: 42.3 ± 18.8 years) completed the study protocol. On day 1, participants completed the following questionnaires: Epworth Sleepiness Scale (ESS), Insomnia Severity Index, Pittsburgh Sleep Quality Index (PSQI), Visual Analog Scale (affect, vigor), Patient Health Questionnaire, and Multidimensional Fatigue Symptom Inventory-Short Form. On days 1-8, participants wore an actigraph and completed a sleep diary to assess mean nighttime and mean daytime total sleep time and sleep efficiency or sleep percentage. On day 9, participants repeated the ESS and completed an MSLT. Correlations assessed mean MSLT sleep-onset latency (MSLT-SOL) vs actigraphy, sleep diary, and questionnaires. Chi-square analyses assessed abnormal MSLT-SOL (≤ 8 minutes) or daytime sleepiness (ESS ≥ 10) and referral question (ie, sleep-disordered breathing vs hypersomnolence disorder).ResultsMean MSLT-SOL was correlated with nighttime total sleep time assessed via both actigraphy and diary, but not with questionnaires. Significant correlations emerged for ESS score on day 1 vs 9, actigraphy vs sleep diary mean nighttime total sleep time, and PSQI vs mean sleep diary sleep efficiency. There was no significant relationship between mean MSLT-SOL and referral question.ConclusionsOur finding that total sleep time measured by actigraphy was associated with MSLT-SOL suggests it is useful in informing the interpretation of MSLT findings; however, it does not appear to be a viable substitute for MSLT for the measurement of objective sleepiness in clinical settings.CitationKelly MR, Zeidler MR, DeCruz S, et al. Actigraphy prior to Multiple Sleep Latency Test: nighttime total sleep time predicts sleep-onset latency. J Clin Sleep Med. 2022;18(1):161-170.

Cognitive behavioral therapy for insomnia (CBTI) for comorbid insomnia and obstructive sleep apnea (OSA) has had mixed results. We integrated CBTI with a positive airway pressure (PAP) adherence program and tested effects on sleep and PAP use. 125 veterans (mean age 63.2, 96% men, 39% non-Hispanic white, 26% black/African American, 18% Hispanic/Latino) with comorbid insomnia and newly-diagnosed OSA (apnea-hypopnea index ≥ 15) were randomized to 5-weekly sessions integrating CBTI with a PAP adherence program provided by a "sleep coach" (with behavioral sleep medicine supervision), or 5-weekly sleep education control sessions. Participants and assessment staff were blinded to group assignment. Outcomes (baseline, 3 and 6 months) included Pittsburgh Sleep Quality Index (PSQI), 7-day sleep diary (sleep onset latency [SOL-D], wake after sleep onset [WASO-D], sleep efficiency [SE-D]), 7-day actigraphy (SE-A), and objective PAP use (hours/night and nights ≥ 4 h). Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), and Functional Outcomes of Sleep Questionnaire-10 (FOSQ-10) were also collected. Compared to controls, intervention participants showed greater improvement (baseline to 3 and 6 months, respectively) in PSQI (-3.2 and -1.7), SOL-D (-16.2 and -15.5 minutes), SE-D (10.5% and 8.5%), SE-A (4.4% and 2.6%) and more 90-day PAP use (1.3 and 0.9 more hours/night, 17.4 and 11.3 more nights PAP ≥ 4 h). 90-day PAP use at 3 months was 3.2 and 1.9 h/night in intervention versus controls. Intervention participants also had greater improvements in ISI, ESS, and FOSQ-10 (all p < 0.05). An intervention integrating CBTI with a PAP adherence program delivered by a supervised sleep coach improved sleep and PAP use in adults with comorbid insomnia and OSA. ClinicalTrials.govStudy name: Novel Treatment of Comorbid Insomnia and Sleep Apnea in Older VeteransURL: https://clinicaltrials.gov/ct2/results?cond=&term=NCT02027558&cntry=&state=&city=&dist=Registration: NCT02027558.

Study objectivesThe goals of this study were to estimate rates of undiagnosed, diagnosed, and treated sleep apnea in women veterans and to identify factors associated with diagnosis and treatment of sleep apnea in this population.MethodsA large nationwide postal survey was sent to a random sample of 4,000 women veterans who had received health care at a Veterans Health Administration (VA) facility in the previous 6 months. A total of 1,498 surveys were completed. Survey items used for the current analyses included: demographics; sleep apnea risk, diagnostic status, and treatment; symptoms of other sleep disorders (eg, insomnia); mental health symptoms; and comorbidities.ResultsAmong responders, 13% of women reported a prior sleep apnea diagnosis. Among women who reported a diagnosis of sleep apnea, 65% reported using positive airway pressure therapy. A sleep apnea diagnosis was associated with older age, higher BMI, non-Hispanic African American/Black racial/ethnic identity, being unemployed, other sleep disorder symptoms (eg, insomnia), depression and post-traumatic stress disorder symptoms, and multimorbidity. Among women without a sleep apnea diagnosis, 43% scored as "high risk" on the STOP (snoring, tiredness, observed apneas, blood pressure) questionnaire. High risk scores were associated with older age, higher BMI, African American/Black identity, other sleep disorder symptoms (eg, insomnia), mental health symptoms, and multimorbidity. Only BMI differed between women using vs not using positive airway pressure therapy.ConclusionsWomen veterans with diagnosed sleep apnea were commonly treated with positive airway pressure therapy, which is standard first-line treatment; however, many undiagnosed women were at high risk. Efforts to increase screening, diagnosis, and treatment of sleep apnea in women with comorbid mental and physical health conditions are needed.

Case presentationA 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.

Study objectivesHome 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.MethodsHSAT 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.ResultsModels 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.ConclusionsCompared 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.

BackgroundObstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD) are common conditions; the co-occurrence of these diseases, called the overlap syndrome (OVS), has been associated with poor health outcomes.PurposeThe purpose of this Official American Thoracic Society Research Statement is to describe pathophysiology, epidemiology, outcomes, diagnostic metrics, and treatment of OVS, as well as to identify important gaps in knowledge and make recommendations for future research.MethodsClinicians and researchers with expertise in sleep medicine, pulmonary medicine, or both were invited to participate. Topics were divided among the participants according to their interest and expertise. A literature search was conducted; the search was not a formal systematic review. Evidence was considered and supplemented with the panelists' nonsystematic clinical observations. Important knowledge gaps were identified.ResultsRecommendations for research to fill existing knowledge gaps were made. The recommendations were formulated by discussion and consensus.ConclusionsMany important questions about OVS exist. This American Thoracic Society Research Statement highlights the types of research that leading clinicians and researchers believe will have the greatest impact on better understanding the spectrum of disease, improving diagnosis, and optimizing therapy.

One of the main issues with radiofrequency (RF) ablation of the subpleural lung malignancy is pain management during and after RF ablation. In this article, we present a case that utilized a technique to decrease the pain associated with RF ablation of a malignancy located within the subpleural lung. Under CT guidance, we created an artificial pneumothorax prior to the RF ablation, which resulted in minimizing the pain usually experienced during and after the procedure. It also decreased the amount of pain medications usually used in patients undergoing RF ablation of a subpleural lung lesion.