Adenotonsillectomy for Snoring and Mild Sleep Apnea in Children: A Randomized Clinical Trial.

Importance: The utility of adenotonsillectomy in children who have habitual snoring without frequent obstructive breathing events (mild sleep-disordered breathing [SDB]) is unknown. Objectives: To evaluate early adenotonsillectomy compared with watchful waiting and supportive care (watchful waiting) on neurodevelopmental, behavioral, health, and polysomnographic outcomes in children with mild SDB. Design, Setting, and Participants: Randomized clinical trial enrolling 459 children aged 3 to 12.9 years with snoring and an obstructive apnea-hypopnea index (AHI) less than 3 enrolled at 7 US academic sleep centers from June 29, 2016, to February 1, 2021, and followed up for 12 months. Intervention: Participants were randomized 1:1 to either early adenotonsillectomy (n = 231) or watchful waiting (n = 228). Main Outcomes and Measures: The 2 primary outcomes were changes from baseline to 12 months for caregiver-reported Behavior Rating Inventory of Executive Function (BRIEF) Global Executive Composite (GEC) T score, a measure of executive function; and a computerized test of attention, the Go/No-go (GNG) test d-prime signal detection score, reflecting the probability of response to target vs nontarget stimuli. Twenty-two secondary outcomes included 12-month changes in neurodevelopmental, behavioral, quality of life, sleep, and health outcomes. Results: Of the 458 participants in the analyzed sample (231 adenotonsillectomy and 237 watchful waiting; mean age, 6.1 years; 230 female [50%]; 123 Black/African American [26.9%]; 75 Hispanic [16.3%]; median AHI, 0.5 [IQR, 0.2-1.1]), 394 children (86%) completed 12-month follow-up visits. There were no statistically significant differences in change from baseline between the 2 groups in executive function (BRIEF GEC T-scores: -3.1 for adenotonsillectomy vs -1.9 for watchful waiting; difference, -0.96 [95% CI, -2.66 to 0.74]) or attention (GNG d-prime scores: 0.2 for adenotonsillectomy vs 0.1 for watchful waiting; difference, 0.05 [95% CI, -0.18 to 0.27]) at 12 months. Behavioral problems, sleepiness, symptoms, and quality of life each improved more with adenotonsillectomy than with watchful waiting. Adenotonsillectomy was associated with a greater 12-month decline in systolic and diastolic blood pressure percentile levels (difference in changes, -9.02 [97% CI, -15.49 to -2.54] and -6.52 [97% CI, -11.59 to -1.45], respectively) and less progression of the AHI to greater than 3 events/h (1.3% of children in the adenotonsillectomy group compared with 13.2% in the watchful waiting group; difference, -11.2% [97% CI, -17.5% to -4.9%]). Six children (2.7%) experienced a serious adverse event associated with adenotonsillectomy. Conclusions: In children with mild SDB, adenotonsillectomy, compared with watchful waiting, did not significantly improve executive function or attention at 12 months. However, children with adenotonsillectomy had improved secondary outcomes, including behavior, symptoms, and quality of life and decreased blood pressure, at 12-month follow-up. Trial Registration: ClinicalTrials.gov Identifier: NCT02562040.

Neighborhoods with Greater Prevalence of Minority Residents Have Lower Continuous Positive Airway Pressure Adherence.

Rationale: Limited data suggest racial disparities in continuous positive airway pressure (CPAP) adherence exist.Objectives: To assess whether CPAP adherence varies by neighborhood racial composition at a national scale.Methods: Telemonitoring data from a CPAP manufacturer database were used to assess adherence in adult patients initiating CPAP therapy between November 2015 and October 2018. Mapping ZIP code to ZIP code tabulation areas, age- and sex-adjusted CPAP adherence data at a neighborhood level was computed as a function of neighborhood racial composition. Secondary analyses adjusted for neighborhood education and poverty.Measurements and Main Results: Among 787,236 patients living in 26,180 ZIP code tabulation areas, the prevalence of CPAP adherence was 1.3% (95% confidence interval [CI], 1.0-1.6%) lower in neighborhoods with high (⩾25%) versus low (<1%) percentages of Black residents and 1.2% (95% CI, 0.9-1.5%) lower in neighborhoods with high versus low percentages of Hispanic residents (P < 0.001 for both), even after adjusting for neighborhood differences in poverty and education. Mean CPAP usage was similar across neighborhoods for the first 2 days, but by 90 days, differences in CPAP usage increased to 22 minutes (95% CI, 18-27 min) between neighborhoods with high versus low percentages of Black residents and 22 minutes (95% CI 17-27 min) between neighborhoods with high versus low percentages of Hispanic residents (P < 0.001 for both).Conclusions: CPAP adherence is lower in neighborhoods with greater proportions of Black and Hispanic residents, independent of education or poverty. These differences lead to a lower likelihood of meeting insurance coverage requirements for CPAP therapy, potentially exacerbating sleep health disparities.

Recommendations for Defining and Reporting Adherence Measured by Biometric Monitoring Technologies: Systematic Review.

BACKGROUND: Suboptimal adherence to data collection procedures or a study intervention is often the cause of a failed clinical trial. Data from connected sensors, including wearables, referred to here as biometric monitoring technologies (BioMeTs), are capable of capturing adherence to both digital therapeutics and digital data collection procedures, thereby providing the opportunity to identify the determinants of adherence and thereafter, methods to maximize adherence. OBJECTIVE: We aim to describe the methods and definitions by which adherence has been captured and reported using BioMeTs in recent years. Identifying key gaps allowed us to make recommendations regarding minimum reporting requirements and consistency of definitions for BioMeT-based adherence data. METHODS: We conducted a systematic review of studies published between 2014 and 2019, which deployed a BioMeT outside the clinical or laboratory setting for which a quantitative, nonsurrogate, sensor-based measurement of adherence was reported. After systematically screening the manuscripts for eligibility, we extracted details regarding study design, participants, the BioMeT or BioMeTs used, and the definition and units of adherence. The primary definitions of adherence were categorized as a continuous variable based on duration (highest resolution), a continuous variable based on the number of measurements completed, or a categorical variable (lowest resolution). RESULTS: Our PubMed search terms identified 940 manuscripts; 100 (10.6%) met our eligibility criteria and contained descriptions of 110 BioMeTs. During literature screening, we found that 30% (53/177) of the studies that used a BioMeT outside of the clinical or laboratory setting failed to report a sensor-based, nonsurrogate, quantitative measurement of adherence. We identified 37 unique definitions of adherence reported for the 110 BioMeTs and observed that uniformity of adherence definitions was associated with the resolution of the data reported. When adherence was reported as a continuous time-based variable, the same definition of adherence was adopted for 92% (46/50) of the tools. However, when adherence data were simplified to a categorical variable, we observed 25 unique definitions of adherence reported for 37 tools. CONCLUSIONS: We recommend that quantitative, nonsurrogate, sensor-based adherence data be reported for all BioMeTs when feasible; a clear description of the sensor or sensors used to capture adherence data, the algorithm or algorithms that convert sample-level measurements to a metric of adherence, and the analytic validation data demonstrating that BioMeT-generated adherence is an accurate and reliable measurement of actual use be provided when available; and primary adherence data be reported as a continuous variable followed by categorical definitions if needed, and that the categories adopted are supported by clinical validation data and/or consistent with previous reports.

A Qualitative Assessment of the Acceptability of Smartphone Applications for Improving Sleep Behaviors in Low-Income and Minority Adolescents.

Background: Daily behaviors such as sleep can be targeted by smartphone app-based interventions, with potential utility among young people of minority ethnic backgrounds who commonly access smartphone devices and are short sleepers. There is a need to understand the acceptability and youth's readiness to use apps to improve sleep, and to identify desired app components that would motivate engagement. Participants and Methods: We conducted three focus group discussions (N = 27 total, age 14-18 years) within low- and middle-income ethnically diverse Boston neighborhoods. We also interviewed 10 participants who provided specific feedback on two commercially available sleep-promoting apps, one of which they had used on their smartphone preceding the interviews. All focus group discussions and interviews were audio-recorded, transcribed, and thematically analyzed. Results: We identified several barriers to adoption of sleep hygiene interventions, namely reluctance to follow scheduled sleep routines on weekends and concern about "parting" with electronics at bedtime. Participants were intrigued by the idea of adopting an app-based sleep intervention, but were skeptical that they could successfully adopt sleep hygiene practices, and were more interested in making changes on school days than on weekends. Nonetheless, the overall feedback on two commercial sleep apps, neither targeted at youth, was positive, with a good adherence and engagement rate, and perceived health benefits. Conclusions: Our findings highlight the need to adapt sleep hygiene recommendations to targeted populations, considering preferences and social and cultural contextual factors. Our research also underscores the importance of the platform, setting, and messenger when delivering health information to adolescents.

Associations between Obstructive Sleep Apnea, Sleep Duration, and Abnormal Fasting Glucose. The Multi-Ethnic Study of Atherosclerosis.

RATIONALE: No data exist as to the role of ethnicity in the associations between obstructive sleep apnea (OSA), sleep duration, and metabolic dysfunction. OBJECTIVES: To examine links between OSA, objectively measured habitual sleep duration, and fasting glucose in U.S. ethnic groups. METHODS: The Multi-Ethnic Study of Atherosclerosis is a multisite community-based study that conducted polysomnography and wrist actigraphy. In 2,151 subjects (1,839 in fully adjusted models), the apnea-hypopnea index was used to classify OSA as none (0-4.9/h), mild (5-14.9/h), or moderate to severe (≥15/h). Actigraphic sleep duration was classified as short (≤5 h/night), intermediate (>5 and <8 h/night), or long (≥8 h/night). Subjects were classified as having normal fasting glucose (<100 mg/dl and no hypoglycemic medication use) or abnormal fasting glucose (≥100 mg/dl and/or hypoglycemic medication use). MEASUREMENTS AND MAIN RESULTS: The sample was 45.8% male, age 68.5 ± 9.2 (mean ± SD) years, and 27.3% African American, 37.2% white, 11.8% Chinese, and 23.8% Hispanic. The prevalence of abnormal fasting glucose was 40.2%. Relative to subjects without apnea, moderate-to-severe OSA was significantly associated with abnormal fasting glucose in African Americans (odds ratio, 2.14; 95% confidence interval, 1.12-4.08) and white participants (odds ratio, 2.85; 95% confidence interval, 1.20-6.75), but not among Chinese or Hispanic subjects, after adjusting for site, age, sex, waist circumference, and sleep duration (P = 0.06 for ethnicity-by-OSA severity interaction). In contrast, sleep duration was not significantly associated with abnormal fasting glucose after considering the influence of OSA. CONCLUSIONS: This large multiethnic study confirmed previous reports of an independent association between OSA and metabolic dysfunction, and suggested that this association may vary by ethnicity.

Clinical predictors of the respiratory arousal threshold in patients with obstructive sleep apnea.

RATIONALE: A low respiratory arousal threshold (ArTH) is one of several traits involved in obstructive sleep apnea pathogenesis and may be a therapeutic target; however, there is no simple way to identify patients without invasive measurements. OBJECTIVES: To determine the physiologic determinates of the ArTH and develop a clinical tool that can identify patients with low ArTH. METHODS: Anthropometric data were collected in 146 participants who underwent overnight polysomnography with an epiglottic catheter to measure the ArTH (nadir epiglottic pressure before arousal). The ArTH was measured from up to 20 non-REM and REM respiratory events selected randomly. Multiple linear regression was used to determine the independent predictors of the ArTH. Logistic regression was used to develop a clinical scoring system. MEASUREMENTS AND MAIN RESULTS: Nadir oxygen saturation as measured by pulse oximetry, apnea-hypopnea index, and the fraction of events that were hypopneas (Fhypopneas) were independent predictors of the ArTH (r(2) = 0.59; P < 0.001). Using this information, we used receiver operating characteristic analysis and logistic regression to develop a clinical score to predict a low ArTH, which allocated a score of 1 to each criterion that was satisfied: (apnea-hypopnea index, <30 events per hour) + (nadir oxygen saturation as measured by pulse oximetry >82.5%) + (Fhypopneas >58.3%). A score of 2 or above correctly predicted a low arousal threshold in 84.1% of participants with a sensitivity of 80.4% and a specificity of 88.0%, a finding that was confirmed using leave-one-out cross-validation analysis. CONCLUSIONS: Our results demonstrate that individuals with a low ArTH can be identified from standard, clinically available variables. This finding could facilitate larger interventional studies targeting the ArTH.

Obesity and sleep apnea are independently associated with adverse left ventricular remodeling and clinical outcome in patients with atrial fibrillation and preserved ventricular function.

AIMS: Obesity is associated with the development of atrial fibrillation (AF), and both obesity and AF are independently associated with the development of heart failure with preserved ejection fraction. We tested the hypothesis that sleep apnea (SA) would have a body mass index (BMI) independent association with adverse left ventricular (LV) remodeling and clinical outcomes in patients with AF and preserved LV function. METHODS AND RESULTS: From 720 consecutive patients with AF, 403 patients without myocardial disease (preserved LV function) were identified and followed up for 3.3 ± 1.5 years. The primary outcome was a combination of all-cause mortality/heart failure hospitalization. Left ventricular mass and LV mass-to-volume ratio were higher in patients with SA and obesity (P < .0001 for all). Body mass index (ß per log = .47; P < .0001) and SA (ß = .05; P = .045) were independently associated with LV mass index. Patients with treated SA had a lower LV mass index (but not LV mass-to-volume ratio) compared with untreated (P = .002). In a best overall multivariable model, SA therapy (ß = -.129; P = .001) and BMI (ß per log = .373; P = .0007) had opposing associations with LV mass index. Sleep apnea (hazard ratio [HR] = 2.94; P = .0004) and BMI (HR per 1 kg/m(2) = 1.08; P = .004) were associated with clinical outcome in unadjusted analysis. Only SA was associated with clinical outcome in a best overall multivariable model (HR = 2.14; P = .02). CONCLUSION: Sleep apnea and obesity are independently associated with adverse LV remodeling and clinical outcomes in patients with preserved LV function, whereas continuous positive airway pressure therapy is associated with a beneficial effect on LV remodeling. Research investigating SA therapies in patients at high risk for LV remodeling and heart failure is warranted.

A pilot study investigating the effects of continuous positive airway pressure treatment and weight-loss surgery on autonomic activity in obese obstructive sleep apnea patients.

BACKGROUND: We have previously demonstrated that severity of obstructive sleep apnea (OSA) as measured by the apnea-hypopnea index (AHI) is a significant independent predictor of readily-computed time-domain metrics of short-term heart rate variability (HRV). METHODS: We aimed to assess time-domain HRV measured over 5-min while awake in a trial of obese subjects undergoing one of two OSA therapies: weight-loss surgery (n=12, 2 males, median and interquartile range (IQR) for BMI 43.7 [42.0, 51.4] kg/m2, and AHI 18.1 [16.3, 67.5] events/h) or continuous positive airway pressure (CPAP) (n=15, 11 males, median BMI 33.8 [31.3, 37.9] kg/m2, and AHI 36.5 [24.7, 77.3] events/h). Polysomnography was followed by electrocardiography during wakefulness; measurements were repeated at 6 and 12-18 months post-intervention. RESULTS: Despite similar measurements at baseline, subjects who underwent surgery exhibited greater improvement in short-term HRV than those who underwent CPAP (p=0.04). CONCLUSIONS: Our data suggest a possible divergence in autonomic function between the effects of weight loss resulting from bariatric surgery, and the amelioration of obstructive respiratory events resulting from CPAP treatment. Randomized studies are necessary before clinical recommendations can be made.

Obstructive sleep apnea and obesity: A review of epidemiology, pathophysiology and the effect of weight-loss treatments.

Despite the commonly-accepted paradigm that patients with obstructive sleep apnea (OSA) also invariably have obesity, OSA prevalence extends beyond obesity. This necessitates a reevaluation of screening strategies, biomarkers of increased OSA risk, and heightened awareness among healthcare providers about the array of OSA treatments for diverse adult populations. While obesity contributes importantly to OSA pathogenesis, there is substantial evidence that non-anatomical factors also play a crucial role, especially in patients who do not have obesity. In recent years, notwithstanding the recognition of diverse contributors to OSA pathogenesis, research has frequently focused on weight reduction to address OSA. Insights from past experiences with bariatric surgery in OSA serve as a lens to anticipate potential outcomes of emerging anti-obesity pharmacotherapies. Pharmacological alternatives, particularly incretin agonists, exhibit promise in weight reduction and OSA improvement, but encounter obstacles such as potential side effects and high costs. With this comprehensive narrative review, we delve into the complex epidemiological and pathophysiological connections between OSA and obesity. Additionally, we emphasize the importance of a multifaceted approach to OSA treatment, recognizing that while weight management is crucial, there is a need for comprehensive strategies that go beyond traditional weight-centric perspectives.

Impacts on study design when implementing digital measures in Parkinson's disease-modifying therapy trials.

Introduction: Parkinson's Disease affects over 8.5 million people and there are currently no medications approved to treat underlying disease. Clinical trials for disease modifying therapies (DMT) are hampered by a lack of sufficiently sensitive measures to detect treatment effect. Reliable digital assessments of motor function allow for frequent at-home measurements that may be able to sensitively detect disease progression. Methods: Here, we estimate the test-retest reliability of a suite of at-home motor measures derived from raw triaxial accelerometry data collected from 44 participants (21 with confirmed PD) and use the estimates to simulate digital measures in DMT trials. We consider three schedules of assessments and fit linear mixed models to the simulated data to determine whether a treatment effect can be detected. Results: We find at-home measures vary in reliability; many have ICCs as high as or higher than MDS-UPDRS part III total score. Compared with quarterly in-clinic assessments, frequent at-home measures reduce the sample size needed to detect a 30% reduction in disease progression from over 300 per study arm to 150 or less than 100 for bursts and evenly spaced at-home assessments, respectively. The results regarding superiority of at-home assessments for detecting change over time are robust to relaxing assumptions regarding the responsiveness to disease progression and variability in progression rates. Discussion: Overall, at-home measures have a favorable reliability profile for sensitive detection of treatment effects in DMT trials. Future work is needed to better understand the causes of variability in PD progression and identify the most appropriate statistical methods for effect detection.

A proposed multi-domain, digital model for capturing functional status and health-related quality of life in oncology.

Whereas traditional oncology clinical trial endpoints remain key for assessing novel treatments, capturing patients' functional status is increasingly recognized as an important aspect for supporting clinical decisions and assessing outcomes in clinical trials. Existing functional status assessments suffer from various limitations, some of which may be addressed by adopting digital health technologies (DHTs) as a means of collecting both objective and self-reported outcomes. In this mini-review, we propose a device-agnostic multi-domain model for oncology capturing functional status, which includes physical activity data, vital signs, sleep variables, and measures related to health-related quality of life enabled by connected digital tools. By using DHTs for all aspects of data collection, our proposed model allows for high-resolution measurement of objective data as patients navigate their daily lives outside of the hospital setting. This is complemented by electronic questionnaires administered at intervals appropriate for each instrument. Preliminary testing and practical considerations to address before adoption are also discussed. Finally, we highlight multi-institutional pre-competitive collaborations as a means of successfully transitioning the proposed digitally enabled data collection model from feasibility studies to interventional trials and care management.

Regulatory Pathways for Qualification and Acceptance of Digital Health Technology-Derived Clinical Trial Endpoints: Considerations for Sponsors.

Despite widespread interest and substantial investment in the adoption of sensor-based digital health technologies (sDHTs) for remote data capture in drug development trials, no drug has been approved based on an sDHT-derived primary endpoint in the United States (US). One reason for this lack of advancement is the complexity of obtaining regulatory endorsement for those endpoints within current US regulatory pathways. The goal of our review is to describe the two choices currently available to pharmaceutical study Sponsors: (i) they may navigate the traditional route of compiling the evidence to support the sDHT-derived endpoint in their investigational new drug (IND) application, requiring specific expertise and substantial resources; or (ii) they may navigate the drug development tool (DDT) pathway with the goal of qualifying their sDHT-derived endpoint as a biomarker or clinical outcome assessment applicable to a broader context of use (COU), either alone or as part of a partnership or consortium. We describe the nuances of each pathway; the evidentiary requirements for supporting an sDHT-derived endpoint and the technology used to capture it; and the impact that an sDHT's regulatory status may have on a Sponsor's decision to use it for data capture. By systematically comparing the IND and DDT pathways, our over-arching goals are to support the increasing deployment of sDHTs within the clinical research setting and help advance regulatory science in the field of digital medicine.

Evaluation of right ventricular remodeling using cardiac magnetic resonance imaging in co-existent chronic obstructive pulmonary disease and obstructive sleep apnea.

Untreated chronic obstructive pulmonary disease (COPD) co-existing with obstructive sleep apnea (OSA), also known as overlap syndrome, has higher cardiovascular mortality than COPD alone but its underlying mechanism remains unclear. We hypothesize that the presence of overlap syndrome is associated with more extensive right ventricular (RV) remodeling compared to patients with COPD alone. Adult COPD patients (GOLD stage 2 or higher) with at least 10 pack-years of smoking history were included. Overnight laboratory-based polysomnography was performed to test for OSA. Subjects with an apnea-hypopnea index (AHI) >10/h were classified as having overlap syndrome (n = 7), else classified as having COPD-only (n = 11). A cardiac MRI was performed to assess right and left cardiac chambers sizes, ventricular masses, and cine function. RV mass index (RVMI) was markedly higher in the overlap group than the COPD-only group (19 ± 6 versus 11 ± 6; p = 0.02). Overlap syndrome subjects had a reduced RV remodeling index (defined as the ratio between RVMI and RV end-diastolic volume index) compared to the COPD-only group (0.27 ± 0.06 versus 0.18 ± 0.08; p = 0.02). In the overlap syndrome subjects, the extent of RV remodeling was associated with severity of oxygen desaturation (R(2) = 0.65, p = 0.03). Our pilot results suggest that untreated overlap syndrome may cause more extensive RV remodeling than COPD alone.

Scoring sleep with artificial intelligence enables quantification of sleep stage ambiguity: hypnodensity based on multiple expert scorers and auto-scoring.

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.

Study protocol: A comparison of mobile and clinic-based spirometry for capturing the treatment effect in moderate asthma.

Several inefficiencies in drug development trial implementation may be improved by moving data collection from the clinic to mobile, allowing for more frequent measurements and therefore increased statistical power while aligning to a patient-centric approach to trial design. Sensor-based digital health technologies such as mobile spirometry (mSpirometry) are comparable to clinic spirometry for capturing outcomes, such as forced expiratory volume in 1 s (FEV1); however, the impact of remote spirometry measurements on the detection of treatment effect has not been investigated. A protocol for a multicenter, single-arm, open-label interventional trial of long-acting beta agonist (LABA) therapy among 60 participants with uncontrolled moderate asthma is described. Participants will complete twice-daily mSpirometry at home and clinic spirometry during weekly visits, alongside continuous use of a wrist-worn wearable and regular completion of several diaries capturing asthma symptoms as well as participant- and site-reported satisfaction and ease of use of mSpirometry. The co-primary objectives of this study are (A) to quantify the treatment effect of LABA therapy among participants with moderate asthma, using both clinical spirometry (FEV1c ) and mSpirometry (FEV1m ); and (B) to investigate whether FEV1m is as accurate as FEV1c in detecting the treatment effect using a mixed-effect model for repeated measures. Study results will help inform whether the deployment of mSpirometry and a wrist-worn wearable for remote data collection are feasible in a multicenter setting among participants with moderate asthma, which may then be generalizable to other populations with respiratory disease.

Nasal versus oronasal continuous positive airway pressure masks for obstructive sleep apnea: a pilot investigation of pressure requirement, residual disease, and leak.

PURPOSE: This single-blinded, randomized, controlled pilot study aimed to investigate whether there is a difference between nasal and oronasal masks in therapeutic continuous positive airway pressure (CPAP) requirement, residual disease, or leak when treating obstructive sleep apnea (OSA) and if differences were related to measures of upper airway size. METHODS: Patients with severe OSA currently using CPAP at ≥4 h/night with a nasal mask were examined (including Mallampati scale, incisal relationship, and mandibular protrusion) and then randomized to receive auto-positive airway pressure (PAP) or fixed CPAP at a manually titrated pressure for 1 week each at home, with immediate crossover. Within each week, a nasal mask and two oronasal masks were to be used for two or three nights each in random order. Data were downloaded from the device. RESULTS: Twelve patients completed the trial (mean ± SD AHI 59.8 ± 28.6 events/h; CPAP 11.1 ± 3.2 cmH(2)O; BMI 37.7 ± 5.0 kg/m(2)). During auto-PAP, the median 95th percentile pressure delivered with all masks was within 0.5 cmH(2)O (p > 0.05). During CPAP, median residual AHI was 0.61 (IQR = 1.18) for the nasal mask, 1.70 (IQR = 4.04) for oronasal mask 1, and 2.48 (IQR = 3.74) for oronasal mask 2 (p = 0.03). The 95th percentile leak was lowest with the nasal mask during both CPAP and auto-PAP (both p < 0.01). Differences in pressure or residual disease were not related to measures of upper airway shape or body habitus. CONCLUSIONS: In obese OSA patients changing from a nasal to oronasal mask increased leak and residual AHI but did not affect the therapeutic pressure requirement. The findings of the current study highlight mask leak as the major difficulty in the use of oronasal masks.

Verification, analytical validation and clinical validation (V3) of wearable dosimeters and light loggers.

Background: Light exposure is an important driver and modulator of human physiology, behavior and overall health, including the biological clock, sleep-wake cycles, mood and alertness. Light can also be used as a directed intervention, e.g., in the form of light therapy in seasonal affective disorder (SAD), jetlag prevention and treatment, or to treat circadian disorders. Recently, a system of quantities and units related to the physiological effects of light was standardized by the International Commission on Illumination (CIE S 026/E:2018). At the same time, biometric monitoring technologies (BioMeTs) to capture personalized light exposure were developed. However, because there are currently no standard approaches to evaluate the digital dosimeters, the need to provide a firm framework for the characterization, calibration, and reporting for these digital sensors is urgent. Objective: This article provides such a framework by applying the principles of verification, analytic validation and clinical validation (V3) as a state-of-the-art approach for tools and standards in digital medicine to light dosimetry. Results: This article describes opportunities for the use of digital dosimeters for basic research, for monitoring light exposure, and for measuring adherence in both clinical and non-clinical populations to light-based interventions in clinical trials.