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We have previously identified mitogen-activated protein kinase-activated protein kinase 2 (MK2) is required for caspase-3 nuclear translocation in the execution of apoptosis; however, little is known of the underlying mechanisms. Therefore, we sought to determine the role of kinase and nonkinase functions of MK2 in promoting nuclear translocation of caspase-3. We identified two non-small cell lung cancer cell lines for use in these experiments based on low MK2 expression. Wild-type, enzymatic and cellular localization mutant MK2 constructs were expressed using adenoviral infection. Cell death was evaluated by flow cytometry. In addition, cell lysates were harvested for protein analyses. Phosphorylation of caspase-3 was determined using two-dimensional gel electrophoresis followed by immunoblotting and in vitro kinase assay. Association between MK2 and caspase-3 was evaluated using proximity-based biotin ligation assays and co-immunoprecipitation. Overexpression of MK2 resulted in nuclear translocation of caspase-3 and caspase-3-mediated apoptosis. MK2 directly phosphorylates caspase-3; however, phosphorylation status of caspase-3 or MK2-dependent phosphorylation of caspase-3 did not alter caspase-3 activity. The enzymatic function of MK2 was dispensable in nuclear translocation of caspase-3. MK2 and caspase-3 associated together and a nonenzymatic function of MK2, chaperoned nuclear trafficking, is required for caspase-3-mediated apoptosis. Taken together, our results demonstrate a nonenzymatic role for MK2 in the nuclear translocation of caspase-3. Furthermore, MK2 may function as a molecular switch in regulating the transition between the cytosolic and nuclear functions of caspase-3.

MK2, known to promote caspase-3 nuclear translocation in the execution of apoptosis, is reduced in non-small cell lung cancer cells. In adenocarcinomas of patients, higher MK2 expression is associated with early-stage disease, better clinical response following chemotherapy and independently associated with improved survival.

Data on the prevalence of sleep-disordered breathing (SDB) in people with HIV are limited. Moreover, whether the associations between SDB and age or BMI differ by HIV status is unknown.Is SDB more prevalent in men with HIV than those without HIV, and do the predictors of SDB differ between the two groups?Home polysomnography was used in the Multicenter AIDS Cohort Study to assess SDB prevalence in men with (n = 466; 92% virologically suppressed) and without (n = 370) HIV. SDB was defined using the oxygen desaturation index (ODI) and the apnea-hypopnea index (AHI), using four definitions: ≥ 5 events/h based on an ODI with a 3% (ODISDB prevalence was similar in men with and without HIV using the ODISDB prevalence was high overall but greater in men with than without HIV using the ODI

Associations of mean glucose and time in range (70-180 mg/dL) from continuous glucose monitoring (CGM) with HbA1c in adults with type 2 diabetes are not well characterized. We conducted a secondary analysis of 186 participants from the Hyperglycemic Profiles in Obstructive Sleep Apnea (HYPNOS) trial. Participants simultaneously wore Dexcom G4 and Abbott Libre Pro CGM sensors up to 4 weeks. Mean HbA1c was 7.7% (SD, 1.3). There were strong negative Pearson's correlations of HbA1c with CGM time in range (-0.79, Abbott; -0.81, Dexcom) and strong positive correlations with CGM mean glucose (Dexcom, 0.84; Abbott, 0.82). However, there were large differences in CGM mean glucose (±20 mg/dL) and time in range (±14%) at any given HbA1c value. Mean glucose and HbA1c are strongly correlated in type 2 diabetes patients not taking insulin but discordance is evident at the individual level. Clinicians should expect discordance and use HbA1c and CGM in a complementary manner. ClinicalTrials.gov Identifier: NCT02454153.

Continuous glucose monitoring (CGM) provides temporal data on glycemic variability, a predictor of outcomes related to type 2 diabetes mellitus. The current study sought to determine whether CGM-derived metrics in patients with type 2 diabetes are different in moderate-to-severe versus mild obstructive sleep apnea (OSA).In adults with type 2 diabetes, home testing was used of assess the presence of OSA. CGM data were collected for at least 7 days in those with an oxygen desaturation index (ODI) ≥ 5 events/hr. The study sample was divided into mild (ODI: 5.0-14.9 events/hr) and moderate-to-severe OSA (ODI ≥15 events/hr). Actigraphy was used to distinguish the wake and sleep periods. CGM-derived metrics were compared between the two groups using multivariable regression models.Compared to mild OSA, patients with moderate-to-severe OSA had higher mean glucose levels during sleep (adjusted difference 8.4 mg/dL; p-value: 0.03) and wakefulness (adjusted difference 7.1 mg/dL; p-value: 0.06). Moderate-to-severe OSA patients also had lower odds for having their glucose values within the acceptable range during wakefulness than those with mild OSA (adjusted odds ratio of 0.63; p-value: 0.02). The mean amplitude of glycemic excursion and standard deviation of the rate of change in glucose values (SD-ROC) were higher in moderate-to-severe than mild OSA, but only during wakefulness. Sex modified the association between OSA severity and SD-ROC, but not the other CGM-derived metrics.In patients with type 2 diabetes, moderate-to-severe OSA is associated with greater abnormalities in CGM-derived metrics than mild OSA with notable differences between sleep and wakefulness.

Background The glucose management indicator (GMI) is an estimated measure of hemoglobin A1c (HbA1c) recommended for the management of persons with diabetes using continuous glucose monitoring (CGM). However, GMI was derived primarily in young adults with type 1 diabetes, and its performance in patients with type 2 diabetes is poorly characterized. Methods We conducted a prospective cohort study in 144 adults with obstructive sleep apnea and type 2 diabetes not using insulin (mean age: 59.4 years; 45.1% female). HbA1c was measured at the study screening visit. Participants simultaneously wore 2 CGM sensors (Dexcom G4 and Abbott Libre Pro) for up to 4 weeks (2 weeks at baseline and 2 weeks at the 3-month follow-up visit). GMI was calculated using all available CGM data for each sensor. Results Median wear time was 27 days (IQR: 23–29) for the Dexcom G4 and 28 days (IQR: 24–29) for the Libre Pro. The mean difference between HbA1c and GMI was small (0.12–0.14 percentage points) (approximately 2 mmol/mol). However, the 2 measures were only moderately correlated (r = 0.68–0.71), and there was substantial variability in GMI at any given value of HbA1c (root mean squared error: 0.66–0.69 percentage points [7 to 8 mmol/mol]). Between 36% and 43% of participants had an absolute difference between HbA1c and GMI ≥0.5 percentage points (≥5 mmol/mol), and 9% to 18% had an absolute difference >1 percentage points (>11 mmol/mol). Discordance was higher in the Libre Pro than the Dexcom G4. Conclusions GMI may be an unreliable measure of glycemic control for patients with type 2 diabetes and should be interpreted cautiously in clinical practice. Clinicaltrials.gov Registration Number: NCT02454153.

Racial disparities in guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) have not been fully documented in a community setting.In the ARIC Surveillance Study (2005-2014), we examined racial differences in GDMT at discharge, its temporal trends, and the prognostic impact among individuals with hospitalized HFrEF, using weighted regression models to account for sampling design. Optimal GDMT was defined as beta blockers (BB), mineralocorticoid receptor antagonist (MRA) and ACE inhibitors (ACEI) or angiotensin II receptor blockers (ARB). Acceptable GDMT included either one of BB, MRA, ACEI/ARB or hydralazine plus nitrates (H-N).Of 16,455 (unweighted n = 3,669) HFrEF cases, 47% were Black. Only ~ 10% were discharged with optimal GDMT with higher proportion in Black than White individuals (11.1% vs. 8.6%, p 0.001). BB use was 80% in both racial groups while Black individuals were more likely to receive ACEI/ARB (62.0% vs. 54.6%) and MRA (18.0% vs. 13.8%) than Whites, with a similar pattern for H-N (21.8% vs. 10.1%). There was a trend of decreasing use of optimal GDMT in both groups, with significant decline of ACEI/ARB use in Whites (- 2.8% p 0.01) but increasing H-N use in both groups (+ 6.5% and + 9.2%, p 0.01). Only ACEI/ARB and BB were associated with lower 1-year mortality.Optimal GDMT was prescribed in only ~ 10% of HFrEF patients at discharge but was more so in Black than White individuals. ACEI/ARB use declined in Whites while H-N use increased in both races. GDMT utilization, particularly ACEI/ARB, should be improved in Black and Whites individuals with HFrEF.

BACKGROUND: Sleep-disordered breathing (SDB) is associated with an increased risk of cardiac arrhythmias, sudden cardiac death, and all-cause mortality. This study investigates the mechanisms underlying this association by examining the effects of prevalent and incident SDB and intermittent hypoxia on ventricular repolarization lability. METHODS: Electrocardiographic recordings from three cohorts were used for this study: (1) a cross-sectional sample of 61 participants with severe SDB and a matched group without SDB; (2) a longitudinal sample of 26 participants without SDB at baseline who developed SDB after a 5-year follow-up, and a matched group without SDB; and (3) a cohort of 19 healthy adults exposed to intermittent hypoxia or ambient air. Mean heart rate, heart rate variability (SDNN), and QT variability index (QTVI), a measure of ventricular repolarization lability, were calculated from one-lead ECG recordings. RESULTS: In the cross-sectional sample, participants with severe SDB had larger QTVI ( P = 0.027), heart rate ( P = 0.028), SDNN ( P = 0.018), and hypoxemia burden as assessed by the total sleep time with oxygen saturation less than 90% (TST (90) ; P < 0.001) than those without SDB. TST (90) , but not the frequency of arousals, was an independent predictor of QTVI ( P = 0.017). Both heart rate and QTVI were predictive of all-cause mortality. In the longitudinal sample with incident SDB, QTVI increased from -1.23 ± 0.15 to -0.86 ± 0.14 ( P = 0.017) over the 5-year follow-up period. Finally, in the cohort of healthy adults, 4 hours of exposure to intermittent hypoxia increased heart rate ( P = 0.001) and QTVI ( P = 0.016). CONCLUSIONS: Prevalent and incident SDB are associated with increased ventricular repolarization instability which predisposes to ventricular arrhythmias and sudden cardiac death. Intermittent hypoxemia can destabilize ventricular repolarization and is a likely mediator of increased mortality in SDB. CLINICAL PERSPECTIVE: WHAT IS NEW? Sleep-disordered breathing, a prevalent condition in the general population, is associated with unstable ventricular repolarization. Incident sleep-disordered breathing destabilizes ventricular repolarization, likely due to the effects of intermittent hypoxemia. Acute exposure to intermittent hypoxia destabilizes ventricular repolarization in healthy adults indicating a causal effect of sleep-disordered breathing on ventricular repolarization and increased mortality risk. WHAT ARE THE CLINICAL IMPLICATIONS? Identifying and treating sleep-disordered breathing in patients at risk for sudden cardiac death, such as those with congestive heart failure, can improve clinical outcomes.

Methadone, a widely-prescribed medication for chronic pain and opioid addiction, is associated with respiratory depression and increased predisposition for torsades de pointes, a potentially fatal arrhythmia. Most methadone-related deaths occur during sleep. The objective of this study was to determine whether methadone’s arrhythmogenic effects increase during sleep, with a focus on cardiac repolarization instability using QT variability index (QTVI), a measure shown to predict arrhythmias and mortality. Sleep study data of 24 patients on chronic methadone therapy referred to a tertiary clinic for overnight polysomnography were compared with two matched groups not on methadone: 24 patients referred for overnight polysomnography to the same clinic (Clinic group), and 24 volunteers who had overnight polysomnography at home (Community group). Despite similar values for heart rate, heart rate variability, corrected QT interval, QTVI and oxygen saturation (SpO(2)) when awake, patients on methadone had larger QTVI (p=0.015 vs Clinic, p1000 premature beats per median sleep period), a precursor for torsades de pointes, was uncommon but more frequent in patients on methadone (p=0.039). This study demonstrates that chronic methadone use is associated with increased cardiac repolarization instability. Methadone’s pro-arrhythmic impact may be mediated by sleep-related hypoxemia which could explain the increased nocturnal mortality associated with this opioid.

Objectives Postprandial hyperglycemia is common in type 2 diabetes even in those with acceptable glycemic control and conveys an increased risk of cardiovascular morbidity and mortality. Although obstructive sleep apnea (OSA) has been associated with altered glucose metabolism, data regarding its association with postprandial hyperglycemia in type 2 diabetes are limited. Thus, the current study sought to characterize the association between OSA and postprandial hyperglycemia in adults with type 2 diabetes. Methods A cross-sectional study of adults with type 2 diabetes was conducted. Home sleep testing was used to assess OSA severity as determined by the oxygen desaturation index (ODI). Self-monitoring of blood glucose (SMBG) was performed before and 2-h after breakfast, lunch, and dinner for three days. The association between OSA and glucose levels before and after each meal was examined using multivariable logistic regression. Results The study sample consisted of 195 adults with 52% being men. OSA severity, as assessed by ODI quartiles, was associated with higher postprandial glucose values after dinner but not after breakfast or lunch. The adjusted odds ratios (95% confidence intervals) for a higher post-dinner glucose level for four ODI quartiles were 1.00 (Reference), 2.16 (0.96, 4.87), 2.23 (1.03, 4.83), and 2.58 (1.18, 5.94). Stratified analyses showed that this association was present in men but not women. Conclusions Increasing OSA severity is associated with postprandial hyperglycemia in type 2 diabetes and may contribute to impaired glycemic control. Future studies examining the impact of OSA treatment on glucose metabolism should consider meal-related glycemic excursions as a potential outcome.

Background The within-person and between-sensor variability of metrics from different interstitial continuous glucose monitoring (CGM) sensors in adults with type 2 diabetes not taking insulin is unclear. Methods Secondary analysis of data from 172 participants from the Hyperglycemic Profiles in Obstructive Sleep Apnea randomized clinical trial. Participants simultaneously wore Dexcom G4 and Abbott Libre Pro CGM sensors for up to 2 weeks at baseline and again at the 3-month follow-up visit. Results At baseline (up to 2 weeks of CGM), mean glucose for both the Abbott and Dexcom sensors was approximately 150 mg/dL (8.3 mmol/L) and time in range (70180 mg/dL [3.910.0 mmol/L]) was just below 80. When comparing the same sensor at 2 different time points (two 2-week periods, 3 months apart), the within-person coefficient of variation (CVw) in mean glucose was 17.4 (Abbott) and 14.2 (Dexcom). CVw for percent time in range: 20.1 (Abbott) and 18.6 (Dexcom). At baseline, the Pearson correlation of mean glucose from the 2 sensors worn simultaneously was r 0.86, root mean squared error (RMSE), 13 mg/dL (0.7 mmol/L); for time in range, r 0.88, RMSE, 8 percentage points. Conclusions Substantial variation was observed within sensors over time and across 2 different sensors worn simultaneously on the same individuals. Clinicians should be aware of this variability when using CGM technology to make clinical decisions. ClinicalTrials.gov Identifier: NCT02454153.

Arsenic exposure has been linked to poor pulmonary function, and inefficient arsenic metabolizers may be at increased risk. Dietary rice has recently been identified as a possible substantial route of exposure to arsenic, and it remains unknown whether it can provide a sufficient level of exposure to affect pulmonary function in inefficient metabolizers. Within 12,609 participants of HCHS/SOL, asthma diagnoses and spirometry-based measures of pulmonary function were assessed, and rice consumption was inferred from grain intake via a food frequency questionnaire. After stratifying by smoking history, the relationship between arsenic metabolism efficiency [percentages of inorganic arsenic (%iAs), monomethylarsenate (%MMA), and dimethylarsinate (%DMA) species in urine] and the measures of pulmonary function were estimated in a two-sample Mendelian randomization approach (genotype information from an Illumina HumanOmni2.5-8v1-1 array), focusing on participants with high inferred rice consumption. Among never-smoking high inferred consumers of rice (n = 1395), inefficient metabolism was associated with past asthma diagnosis and forced vital capacity below the lower limit of normal (LLN) (OR 1.40, p = 0.0212 and OR 1.42, p = 0.0072, respectively, for each percentage-point increase in %iAs; OR 1.26, p = 0.0240 and OR 1.24, p = 0.0193 for %MMA; OR 0.87, p = 0.0209 and OR 0.87, p = 0.0123 for the marker of efficient metabolism, %DMA). Among ever-smoking high inferred consumers of rice (n = 1127), inefficient metabolism was associated with peak expiratory flow below LLN (OR 1.54, p = 0.0108/percentage-point increase in %iAs, OR 1.37, p = 0.0097 for %MMA, and OR 0.83, p = 0.0093 for %DMA). Less efficient arsenic metabolism was associated with indicators of pulmonary dysfunction among those with high inferred rice consumption, suggesting that reductions in dietary arsenic could improve respiratory health.

BACKGROUND: Healthy sleep is an important component of childhood development. Changes in sleep architecture, including sleep stage composition, quantity, and quality from infancy to adolescence are a reflection of neurologic maturation. Hospital admission for acute illness introduces modifiable risk factors for sleep disruption that may negatively affect active brain development during a period of illness and recovery. Thus, it is important to examine non‐pharmacologic interventions for sleep promotion in the pediatric inpatient setting. OBJECTIVES: To evaluate the effect of non‐pharmacological sleep promotion interventions in hospitalized children and adolescents on sleep quality and sleep duration, child or parent satisfaction, cost‐effectiveness, delirium incidence, length of mechanical ventilation, length of stay, and mortality. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, CINAHL, three other databases, and three trials registers to December 2021. We searched Google Scholar, and two websites, handsearched conference abstracts, and checked reference lists of included studies. SELECTION CRITERIA: Randomized controlled trials (RCTs) or quasi‐RCTs, including cross‐over trials, investigating the effects of any non‐pharmacological sleep promotion intervention on the sleep quality or sleep duration (or both) of children aged 1 month to 18 years in the pediatric inpatient setting (intensive care unit [ICU] or general ward setting). DATA COLLECTION AND ANALYSIS: Two review authors independently assessed trial eligibility, evaluated risk of bias, extracted and synthesized data, and used the GRADE approach to assess certainty of evidence. The primary outcomes were changes in both objective and subjective validated measures of sleep in children; secondary outcomes were child and parent satisfaction, cost‐effectiveness ratios, delirium incidence or delirium‐free days at time of hospital discharge, duration of mechanical ventilation, length of hospital stay, and mortality. MAIN RESULTS: We included 10 trials (528 participants; aged 3 to 22 years) in inpatient pediatric settings. Seven studies were conducted in the USA, two in Canada, and one in Brazil. Eight studies were funded by government, charity, or foundation grants. Two provided no information on funding. Eight studies investigated behavioral interventions (massage, touch therapy, and bedtime stories); two investigated physical activity interventions. Duration and timing of interventions varied widely. All studies were at high risk of performance bias due to the nature of the intervention, as participants, parents, and staff could not be masked to group assignment. We were unable to perform a quantitative synthesis due to substantial clinical heterogeneity. Behavioral interventions versus usual care Five studies (145 participants) provided low‐certainty evidence of no clear difference between multicomponent relaxation interventions and usual care on objective sleep measures. Overall, evidence from single studies found no clear differences in daytime or nighttime sleep measures (33 participants); any sleep parameter (48 participants); or daytime or nighttime sleep or nighttime arousals (20 participants). One study (34 participants) reported no effect of massage on nighttime sleep, sleep efficiency (SE), wake after sleep onset (WASO), or total sleep time (TST) in adolescents with cancer. Evidence from a cross‐over study in 10 children with burns suggested touch therapy may increase TST (391 minutes, interquartile range [IQR] 251 to 467 versus 331 minutes, IQR 268 to 373; P = 0.02); SE (76, IQR 53 to 90 versus 66, IQR 55 to 78; P = 0.04); and the number of rapid eye movement (REM) periods (4.5, IQR 2 to 5 versus 3.5, IQR 2 to 4; P = 0.03); but not WASO, sleep latency (SL), total duration of REM, or per cent of slow wave sleep. Four studies (232 participants) provided very low‐certainty evidence on subjective measures of sleep. Evidence from single studies found that sleep efficiency may increase, and the percentage of nighttime wakefulness may decrease more over a five‐day period following a massage than usual care (72 participants). One study (48 participants) reported an improvement in Children's Sleep Habits Questionnaire scores after discharge in children who received a multicomponent relaxation intervention compared to usual care. In another study, mean sleep duration per sleep episode was longer (23 minutes versus 15 minutes), and time to fall asleep was shorter (22 minutes versus 27 minutes) following a bedtime story versus no story (18 participants); and children listening to a parent‐recorded story had longer SL than when a parent was present (mean 57.5 versus 43.5 minutes); both groups reported longer SL than groups who had a stranger‐recorded story, and those who had no story and absent parents (94 participants; P < 0.001). In one study (34 participants), 87% (13/15) of participants felt they slept better following massage, with most parents (92%; 11/12) reporting they wanted their child to receive a massage again. Another study (20 participants) reported that parents thought the music, touch, and reading components of the intervention were acceptable, feasible, and had positive effects on their children (very low‐certainty evidence). Physical activity interventions versus usual care One study (29 participants) found that an enhanced physical activity intervention may result in little or no improvement in TST or SE compared to usual care (low‐certainty evidence). Another study (139 participants), comparing play versus no play found inconsistent results on subjective measures of sleep across different ages (TST was 49% higher for the no play groups in 4‐ to 7‐year olds, 10% higher in 7‐ to 11‐year olds, and 22% higher in 11‐ to 14‐year olds). This study also found inconsistent results between boys and girls (girls in the first two age groups in the play group slept more than the no play group). No study evaluated child or parent satisfaction for behavioral interventions, or cost‐effectiveness, delirium incidence or delirium‐free days at hospital discharge, length of mechanical ventilation, length of hospital stay, or mortality for either behavioral or physical activity intervention. AUTHORS' CONCLUSIONS: The included studies were heterogeneous, so we could not quantitatively synthesize the results. Our narrative summary found inconsistent, low to very low‐certainty evidence. Therefore, we are unable to determine how non‐pharmacologic sleep promotion interventions affect sleep quality or sleep duration compared with usual care or other interventions. The evidence base should be strengthened through design and conduct of randomized trials, which use validated and highly reliable sleep assessment tools, including objective measures, such as polysomnography and actigraphy.

Background Sleep-disordered breathing (SDB) is independently associated with insulin resistance, glucose intolerance, and type 2 diabetes mellitus. However, data on whether SDB alters the metabolism of free fatty acids (FFAs) are lacking. Research Question The primary objective of the current study was to characterize alterations in FFA metabolism across the spectrum of SDB severity. Study Design and Methods The study sample included 118 participants with and without SDB who underwent full-montage polysomnography, the frequently sampled IV glucose tolerance test (FSIGTT), and body composition measurements including determination of percent body fat. Parameters of lipolysis suppression, time to FFA nadir, and FFA rebound after an IV glucose challenge were derived using a mathematical model. Multivariable regression analyses were used to characterize the independent associations between SDB severity and parameters of FFA metabolism. Results SDB severity, as assessed by the apnea-hypopnea index, was associated with adipocyte insulin resistance, a decrease in the glucose- and insulin-mediated suppression of lipolysis, a longer duration to reach a nadir in FFA levels during the FSIGTT, and a sluggish rebound in FFA levels after suppression. Severity of SDB-related hypoxemia was independently associated with adipocyte insulin resistance and the time to reach the FFA nadir during the FSIGTT. Finally, a higher percentage of stage N3 sleep was positively associated with greater suppression of lipolysis and a faster rebound in the FFA levels during the FSIGTT. Interpretation Independent of adiposity, SDB is associated with impairments in FFA metabolism, which may contribute to the development of glucose intolerance and type 2 diabetes in SDB.

Background Lung to finger circulation time (LFCT) measured from sleep studies may represent a novel physiologic marker for cardiovascular risk in patients with sleep disordered breathing (SDB). We hypothesized that sleep study-derived LFCT would improve risk classification of markers of subclinical cardiovascular disease. Methods We included participants in the Multi-Ethnic Study of Atherosclerosis (MESA) Sleep cohort with moderate-severe SDB (apnea hypopnea index [AHI] ≥ 15/hr) (N = 598). Results Those with average LFCT above the median (19.4 s) (vs. shorter LFCT) tended to be older, more obese and male. In multivariable analysis, no significant associations were found between average LFCT and subclinical cardiovascular markers including coronary artery calcium, carotid intima-media thickness or left ventricular hypertrophy. However, there was modest improvement in risk classification of coronary artery calcification as compared with AHI alone when average LFCT was added to AHI (C statistics 0.53 vs. 0.62, p = 0.0066). Conclusions In conclusion, LFCT may be a useful addition to conventional SDB metrics to improve cardiovascular risk assessment.

Background: Noninvasive ventilation (NIV) is used for patients with chronic obstructive pulmonary disease (COPD) and chronic hypercapnia. However, evidence for clinical efficacy and optimal management of therapy is limited. Target Audience: Patients with COPD, clinicians who care for them, and policy makers. Methods: We summarized evidence addressing five PICO (patients, intervention, comparator, and outcome) questions. The GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach was used to evaluate the certainty in evidence and generate actionable recommendations. Recommendations were formulated by a panel of pulmonary and sleep physicians, respiratory therapists, and methodologists using the Evidence-to-Decision framework. Recommendations: 1) We suggest the use of nocturnal NIV in addition to usual care for patients with chronic stable hypercapnic COPD (conditional recommendation, moderate certainty); 2) we suggest that patients with chronic stable hypercapnic COPD undergo screening for obstructive sleep apnea before initiation of long-term NIV (conditional recommendation, very low certainty); 3) we suggest not initiating long-term NIV during an admission for acute-on-chronic hypercapnic respiratory failure, favoring instead reassessment for NIV at 2–4 weeks after resolution (conditional recommendation, low certainty); 4) we suggest not using an in-laboratory overnight polysomnogram to titrate NIV in patients with chronic stable hypercapnic COPD who are initiating NIV (conditional recommendation, very low certainty); and 5) we suggest NIV with targeted normalization of PaCO2 in patients with hypercapnic COPD on long-term NIV (conditional recommendation, low certainty). Conclusions: This expert panel provides evidence-based recommendations addressing the use of NIV in patients with COPD and chronic stable hypercapnic respiratory failure.

Summary We introduce a multilevel functional Beta model to quantify the blood glucose levels measured by continuous glucose monitors for multiple days in study participants with type 2 diabetes mellitus. The model estimates the subject-specific marginal quantiles, quantifies the within- and between-subject variability, and produces interpretable parameters of blood glucose dynamics as a function of time from the actigraphy-estimated sleep onset. Results are validated via simulations and by studying the association between the estimated model parameters and hemoglobin A1c, the gold standard for assessing glucose control in diabetes.

Rationale: Sleep-disordered breathing (SDB) occurring primarily during rapid eye movement (REM) sleep is a common clinical problem. The natural history of REM-related SDB and the associated cardiovascular sequelae of disease progression remain to be determined. Objectives: The objective of the current study was to describe the natural history of REM-related SDB, ascertain predictors of progression, and determine whether the evolution of REM-related SDB into non-REM (NREM) sleep is associated with incident cardiovascular events. Methods: Participants from the Sleep Heart Health Study with a baseline NREM apnea–hypopnea index (NREM-AHI) of

Physical inactivity is a leading determinant of noncommunicable diseases. Yet, many adults remain physically inactive. Physical activity guidelines do not account for the multidimensionality of physical activity, such as the type or variety of physical activity behaviors. This study identified patterns of physical activity across multiple dimensions (e.g., frequency, duration, and variety) using a nationally representative sample of adults. Sociodemographic characteristics, health behaviors, and clinical characteristics associated with each physical activity pattern were defined. Multivariate finite mixture modeling was used to identify patterns of physical activity among 2003–2004 and 2005–2006 adult National Health and Nutrition Examination Survey participants. Chi-square tests were used to identify sociodemographic differences within each physical activity cluster and test associations between the physical activity clusters with health behaviors and clinical characteristics. Five clusters of physical activity patterns were identified: (a) low frequency, short duration (n = 730, 13%); (b) low frequency, long duration (n = 392, 7%); (c) daily frequency, short duration (n = 3,011, 55%); (d) daily frequency, long duration (n = 373, 7%); and (e) high frequency, average duration (n = 964, 18%). Walking was the most common form of activity; highly active adults engaged in more varied types of activity. High-activity clusters were comprised of a greater proportion of younger, White, nonsmoking adult men reporting moderate alcohol use without mobility problems or chronic health conditions. Active females engaged in frequent short bouts of activity. Data-driven approaches are useful for identifying clusters of physical activity that encompass multiple dimensions of activity. These activity clusters vary across sociodemographic and clinical subgroups.

Background:People living with human immunodeficiency virus (HIV+) have greater risk for sudden arrhythmic death than HIV-uninfected (HIV–) individuals. HIV-associated abnormal cardiac repolarization may contribute to this risk. We investigated whether HIV serostatus is associated with ventricular repolarization lability by using the QT variability index (QTVI), defined as a log measure of QT-interval variance indexed to heart rate variance.Methods:We studied 1123 men (589 HIV+ and 534 HIV–) from MACS (Multicenter AIDS Cohort Study), using the ZioXT ambulatory electrocardiography patch. Beat-to-beat analysis of up to 4 full days of electrocardiographic data per participant was performed using an automated algorithm (median analyzed duration [quartile 1–quartile 3]: 78.3 [66.3–83.0] hours/person). QTVI was modeled using linear mixed-effects models adjusted for demographics, cardiac risk factors, and HIV-related and inflammatory biomarkers.Results:Mean (SD) age was 60.1 (11.9) years among HIV– and 54.2 (11.2) years among HIV+ participants (PConclusions:HIV+ men have greater beat-to-beat variability in QT interval (QTVI) than HIV– men, especially in the setting of HIV viremia and heightened inflammation. Among HIV+ men, higher QTVI suggests ventricular repolarization lability, which can increase susceptibility to arrhythmias, whereas lower heart rate variability signals a component of autonomic dysfunction.

Study Objectives To quantify the amount of sleep stage ambiguity across expert scorers and to validate a new auto-scoring platform against sleep staging performed by multiple scorers. Methods We applied a new auto-scoring system to three datasets containing 95 PSGs scored by 6–12 scorers, to compare sleep stage probabilities (hypnodensity; i.e. the probability of each sleep stage being assigned to a given epoch) as the primary output, as well as a single sleep stage per epoch assigned by hierarchical majority rule. Results The percentage of epochs with 100% agreement across scorers was 46 ± 9%, 38 ± 10% and 32 ± 9% for the datasets with 6, 9, and 12 scorers, respectively. The mean intra-class correlation coefficient between sleep stage probabilities from auto- and manual-scoring was 0.91, representing excellent reliability. Within each dataset, agreement between auto-scoring and consensus manual-scoring was significantly higher than agreement between manual-scoring and consensus manual-scoring (0.78 vs. 0.69; 0.74 vs. 0.67; and 0.75 vs. 0.67; all p < 0.01). Conclusions Analysis of scoring performed by multiple scorers reveals that sleep stage ambiguity is the rule rather than the exception. Probabilities of the sleep stages determined by artificial intelligence auto-scoring provide an excellent estimate of this ambiguity. Compared to consensus manual-scoring, sleep staging derived from auto-scoring is for each individual PSG noninferior to manual-scoring meaning that auto-scoring output is ready for interpretation without the need for manual adjustment.

Introduction: Evidence is mixed on short sleep duration and heart failure (HF) risk. Notably, no studies have investigated objectively-assessed sleep duration or controlled for comorbid sleep apnea in this context. Objective: To examine the independent associations of objective short sleep duration with incident HF, accounting for sleep apnea. Methods: We studied ARIC-SHHS study participants free of HF at visit 4 (1996-98). Sleep duration was measured by at-home polysomnography (PSG) and defined as: 7 to Results: We included 1,056 participants (mean age 62 years, 50% female, 99% White). During a median follow-up of 22 years, there were 211 HF events. Participants with sleep duration CI : 1.40-4.26) and 1.88 (95% CI : 1.07-3.29) ( Table ). However, further adjustment for clinical factors attenuated the results. The associations for sleep duration appeared more evident when we restricted our analysis to participants without prevalent cardiovascular disease ( Table ). The AHI was not a significant predictor of incident HF in the presence of sleep duration. Conclusions: Objectively-assessed short sleep duration

Study Objectives Along with multiple chronic comorbidities, sleep disorders are prevalent in people living with human immunodeficiency virus (HIV) infection. The goal of this study was to establish methods for assessing sleep quality and breathing-related disorders using self-applied home polysomnography in people with and without HIV. Methods Self-applied polysomnography was conducted on 960 participants in the Multicenter AIDS Cohort Study (MACS) using the Nox A1 recorder to collect data on the frontal electroencephalogram (EEG), bilateral electrooculograms, and a frontalis electromyogram during sleep. Breathing patterns were characterized using respiratory inductance plethysmography bands and pulse oximetry. Continuous recordings of the electrocardiogram were also obtained. All studies were scored centrally for sleep stages and disordered breathing events. Results Successful home polysomnography was obtained in 807 of 960 participants on the first attempt and 44 participants on the second. Thus, a successful polysomnogram was obtained in 851 (88.6%) of the participants. Reasons for an unsuccessful study included less than 3 h of data on oximetry (34.6%), EEG (28.4%), respiratory inductance plethysmography (21.0%), or two or more of these combined (16.0%). Of the successful studies (N = 851), signal quality was rated as good, very good, or excellent in 810 (95.2%). No temporal trends in study quality were noted. Independent correlates of an unsuccessful study included black race, current smoking, and cocaine use. Conclusions Home polysomnography was successfully completed in the MACS demonstrating its feasibility in a community cohort. Given the burden of in-lab polysomnography, the methods described herein provide a cost-effective alternative for collecting sleep data in the home.

Introduction: Early diagnosis of atrial fibrillation (AF) leading to early therapy can improve clinical outcomes (e.g., stroke). Current approaches for AF risk stratification are limited. Dynamic ECG analysis during sleep is an alternate, underexplored approach for AF risk stratification. Hypothesis: Dynamic ECG analysis during sleep predicts AF incidence in community adults, and adds major independent prognostic value to conventional AF risk factors and scores. Methods: In the multi-center prospective Sleep Heart Health Study, we studied consecutive, asymptomatic, ostensibly healthy, middle-aged and older community adults without a history of AF who were in sinus rhythm during home polysomnography. We performed comprehensive and systematic univariate and multivariate analyses of all available clinical, ECG and polysomnography parameters for association with AF incidence over follow-up. Results: Over 5.3±0.29 years, 315 (11.2%) of 2,807 people had new onset AF. We identified the major independent significant AF predictors, including established risk factors and ECG dynamics, and derived a multivariate prediction model entitled, the Cincinnati AF score (CAFS) ( FIGURE 1 ). Addition of CAFS to a multivariate model with (1) CHA 2 DS 2 -VASc score increased ROC curve area by 9% and yielded net reclassification improvement (NRI) of 90% [43+47% for cases and non-cases, respectively]; or with (2) CHARGE-AF score increased ROC curve area by 3.5% and yielded NRI of 54% [23+31%]. These improvements were driven primarily by the ECG dynamics, independent of sleep apnea and other risk factors. Conclusion: Dynamic ECG analysis during sleep adds major independent prognostic value to established AF risk factors and scores. The ability to better identify individuals who will and will not develop AF has potential for broad clinical impact. We are currently validating CAFS in another multi-center cohort of asymptomatic ambulatory adults with a diverse demographic profile.

Electrical cell‐substrate impedance sensing (ECIS) is an in vitro methodology for measuring the barrier integrity of a variety of cell types, including pulmonary endothelial cells. These experiments are frequently used for in vitro assessment of lung injury. The data derived from ECIS experiments consists of repeated measures of resistance across an endothelial monolayer. As such, these data reflect the dynamic changes in electrical resistance that occur over time. Currently methodologies for assessing ECIS data rely on single point assessments of barrier function, such as the maximal drop in trans‐endothelial electrical resistance (TERMax). However, this approach ignores the myriad of changes in resistance that occur before and after the TERMax data point. Herein, we utilize polynomial curve fitting on experimentally generated ECIS data, thus allowing for comparing ECIS experiments by examining the mean polynomial coefficients between groups. We show that polynomial curves accurately fit a variety of ECIS data, and that concordance between TERMax and coefficient analysis varies by type of stimulus, suggesting that TERMax differences may not always correlate with a significant difference in the overall shape of the ECIS profile. Lastly, we identify factors that impact coefficient values obtained in our analyses, including the length of time devoted to baseline measurements before addition of stimuli. Polynomial coefficient analysis is another tool that can be used for more comprehensive interrogation of ECIS data to better understand the biological underpinnings that lead to changes in barrier dysfunction in vitro., Electrical cell‐substrate impedance sensing (ECIS) is a common method for assessing cell permeability. Herein, we use polynomial fitting to improve fitting and quantification of resistance measurements generated by ECIS experiments.

BackgroundMechanisms underlying blood pressure (BP) changes in obstructive sleep apnoea (OSA) are incompletely understood. We assessed the associations between BP and selected polysomnography (PSG) traits: sleep depth, airflow limitation measurements and OSA-specific hypoxic burden.MethodsThis cross-sectional analysis included 2055 participants from the Multi-Ethnic Study of Atherosclerosis who underwent PSG and BP measurements in 2010–2013. Sleep depth was assessed using the ‘OR product’, a continuous measure of arousability. Airflow limitation was assessed by duty cycle (Ti/Tt) and % of breaths with flow limitation, and hypoxia by ‘hypoxic burden’. Primary outcomes were medication-adjusted systolic BP (SBP) and diastolic BP (DBP). We used generalised linear models adjusted for age, sex, race/ethnicity, smoking, education, body mass index, alcohol use, periodic limb movements and alternative physiological disturbances.ResultsThe sample had a mean age of 68.4 years and apnoea–hypopnoea index of 14.8 events/hour. Sleep depth was not significantly associated with BP. Every 1 SD increment in log-transformed non-rapid eye movement duty cycle was associated with 0.9% decrease in SBP (95% CI: 0.1% to 1.6%), even after adjusting for sleep depth and hypoxic burden. Every 1 SD increment in log-transformed hypoxic burden was associated with a 1.1% increase in SBP (95% CI: 0.1% to 2.1%) and 1.9% increase in DBP (95% CI: 1.0% to 2.8%) among those not using hypertension medications.ConclusionsHigher duty cycle was associated with lower SBP overall and hypoxic burden with higher SBP and DBP among non-BP medication users. These findings suggest changes in both respiratory effort and oxygenation during sleep influence BP.

The accelerating trend towards personalized “pre-cision medicine” and tele-healthcare is revolutionizing the practice of medicine and giving the individual unprecedented access to their own health data. At the same time, a widening gap between wakeful health (ex. physical activity) and nocturnal health (sleep) has revealed the need for accurate, reliable and automated methods to measure sleep in the home. Here we describe a small-footprint sensor array, using electrode stickers that can be self-applied to the forehead, in conjunction with an automated scoring algorithm that achieves accuracies on par with trained human experts (77% agreement using a five-class taxonomy). Compared to alternatives, this approach avoids the low signal-to-noise ratios of dry-contact scalp electrodes while also circumventing the need to measure through hair. Critically, it does not require a trained human expert, either to apply the electrodes or to translate the signals into a useful description of sleep patterns. Taken together, this represents an exciting step forward towards affordable, reliable, and accurate in-the-home sleep assessment.

Obstructive sleep apnea (OSA) is thought to affect almost 1 billion people worldwide. OSA has well established cardiovascular and neurocognitive sequelae, although the optimal metric to assess its severity and/or potential response to therapy remains unclear. The apnea-hypopnea index (AHI) is well established; thus, we review its history and predictive value in various different clinical contexts. Although the AHI is often criticized for its limitations, it remains the best studied metric of OSA severity, albeit imperfect. We further review the potential value of alternative metrics including hypoxic burden, arousal intensity, odds ratio product, and cardiopulmonary coupling. We conclude with possible future directions to capture clinically meaningful OSA endophenotypes including the use of genetics, blood biomarkers, machine/deep learning and wearable technologies. Further research in OSA should be directed towards providing diagnostic and prognostic information to make the OSA diagnosis more accessible and to improving prognostic information regarding OSA consequences, in order to guide patient care and to help in the design of future clinical trials.

Large-scale randomized trials of positive airway pressure (PAP) efficacy have been largely negative but PAP adherence was notably suboptimal across the trials. To address this limitation, evidence-based PAP adherence protocols embedded within the larger trial protocol are recommended. The complexity of such protocols depends on adequacy of resources, including funding and inclusion of behavioral scientist experts on the scientific team, and trial-specific considerations (eg, target population) and methods. Recommendations for optimizing PAP adherence in large-scale trials are set forth that address rigor and reproducibility.

Background Data on the prevalence and correlates of restless legs syndrome (RLS) in people with HIV are limited. This study sought to determine the prevalence of RLS, associated clinical correlates, and characterize sleep-related differences in men with and without HIV. Methods Sleep-related data were collected in men who have sex with men participating in the Multicenter AIDS Cohort Study (MACS). Demographic, health behaviors, HIV status, comorbidities, and serological data were obtained from the MACS visit coinciding with sleep assessments. Participants completed questionnaires, home polysomnography, and wrist actigraphy. RLS status was determined with the Cambridge-Hopkins RLS questionnaire. RLS prevalence was compared in men with and without HIV. Multinomial logistic regression was used to examine correlates of RLS among all participants and men with HIV alone. Sleep-related differences were examined in men with and without HIV by RLS status. Results The sample consisted of 942 men (56% HIV+; mean age 57 years; 69% white). The prevalence of definite RLS was comparable in men with and without HIV (9.1% vs 8.7%). In multinomial regression, HIV status was not associated with RLS prevalence. However, white race, anemia, depression, and antidepressant use were each independently associated with RLS. HIV disease duration was also associated with RLS. Men with HIV and RLS reported poorer sleep quality, greater sleepiness, and had worse objective sleep efficiency/fragmentation than men without HIV/RLS. Conclusions The prevalence of RLS in men with and without HIV was similar. Screening for RLS may be considered among people with HIV with insomnia and with long-standing disease.

Glucose and free fatty acids (FFA) are essential nutrients that are both partly regulated by insulin. Impaired insulin secretion and insulin resistance are hallmarks of aberrant glucose disposal, and type 2 diabetes (T2DM). In the current study, a novel model of FFA kinetics is proposed to estimate the role insulin action on FFA lipolysis and oxidation allowing estimation of adipose tissue insulin sensitivity (SIFFA). Twenty-five normal volunteers were recruited for the current study. To participate, volunteers had to be less than 40 years of age and have a body mass index (BMI) < 30 kg/m2, and be free of medical comorbidity. The proposed model of FFA kinetics was used to analyze the data derived from the insulin-modified FSIGT. Mean fractional standard deviations of the parameter estimates were all less than 20%. Standardized residuals of the fit of the model to the FFA temporal data were randomly distributed, with only one estimated point lying outside the 2-standard deviation range, suggesting an acceptable fit of the model to the FFA data. The current study describes a novel one-compartment non-linear model of FFA kinetics during an FSIGT that provides an FFA metabolism insulin sensitivity parameter (SIFFA). Furthermore, the models suggest a new role of glucose as the modulator of FFA disposal. Estimates of SIFFA confirmed previous findings that FFA metabolism is more sensitive to changes in insulin than glucose metabolism. Novel derived indices of insulin sensitivity of FFA (SIFFA) were correlated with minimal model indices. These associations suggest a cooperative rather than competitive interplay between the two primary nutrients (glucose and FFA) and allude to the FFA acting as the buffer, such that glucose homeostasis is maintained.

Continuous Glucose Monitoring (CGM) data play an increasing role in clinical practice as they provide detailed quantification of blood glucose levels during the entire 24-hour period. The R package iglu implements a wide range of CGM-derived metrics for measuring glucose control and glucose variability. The package also allows one to visualize CGM data using time-series and lasagna plots. A distinct advantage of iglu is that it comes with a point-and-click graphical user interface (GUI) which makes the package widely accessible to users regardless of their programming experience. Thus, the open-source and easy to use iglu package will help advance CGM research and CGM data analyses. R package iglu is publicly available on CRAN and at https://github.com/irinagain/iglu.

Background Portable monitoring is a convenient means for diagnosing sleep apnea. However, data on whether one night of monitoring is sufficiently precise for the diagnosis of sleep apnea are limited. Research Question The current study sought to determine the variability and misclassification in disease severity over three consecutive nights in a large sample of patients referred for sleep apnea. Methods A sample of 10,340 adults referred for sleep apnea testing was assessed. A self-applied type III monitor was used for three consecutive nights. The apnea-hypopnea index (AHI) was determined for each night, and a reference AHI was computed by using data from all 3 nights. Pairwise correlations and the proportion misclassified regarding disease severity were computed for each of the three AHI values against the reference AHI. Results Strong correlations were observed between the AHI from each of the 3 nights (r = 0.87-0.89). However, substantial within-patient variability in the AHI and significant misclassification in sleep apnea severity were observed based on any 1 night of monitoring. Approximately 93% of the patients with a normal study on the first night and 87% of those with severe sleep apnea on the first night were correctly classified compared with the reference derived from all three nights. However, approximately 20% of the patients with mild and moderate sleep apnea on the first night were misdiagnosed either as not having sleep apnea or as having mild disease, respectively. Conclusions In patients with mild to moderate sleep apnea, one night of portable testing can lead to misclassification of disease severity given the substantial night-to-night variability in the AHI.