Novel physiologic predictors of positive airway pressure effectiveness (NICEPAP) study: rationale, design and methods.

PURPOSE: Continuous positive airway pressure (CPAP) is the primary therapy for obstructive sleep apnea (OSA); however the effectiveness of CPAP remains suboptimal. We describe the Novel PhysIologiC prEdictors of Positive Airway Pressure Effectiveness (NICEPAP) study. Its purpose is to determine whether physiological traits of OSA contribute to CPAP effectiveness. METHODS: NICEPAP (NCT05067088) is a prospective, observational cohort study conducted at an academic sleep center. Adults newly diagnosed with OSA (n = 267) are assessed for OSA traits of loop gain, arousal threshold, pharyngeal collapsibility, and muscle compensation from baseline polysomnography. We perform a comprehensive assessment of covariates relevant to CPAP adherence, efficacy, and patient-centered outcomes. Participants are followed for 12 months. Primary outcomes include (1) CPAP adherence (hours/night), (2) CPAP efficacy (apneas-hypopneas/hour), and (3) quality of life at six months measured by objective CPAP data and Functional Outcomes of Sleep Questionnaire. Secondary outcomes include sleep quality, sleepiness, insomnia, and neurocognitive function. RESULTS: Data on covariates, including demographics, sleep symptoms, medical history, medications, sleep quality, OSA and treatment self-efficacy, decisional balance, and socio-economic and social and partner support, are collected using validated instruments. The analysis for primary outcomes includes a generalized linear mixed model for an outcome (e.g., CPAP adherence) with OSA traits as exposures followed by the addition of relevant covariates. CONCLUSION: The findings of the NICEPAP study will inform research aimed to enhance CPAP effectiveness. Understanding the role of physiological OSA traits in CPAP effectiveness is a crucial step toward a precision medicine approach to OSA.

Physiological Traits and Adherence to Sleep Apnea Therapy in Individuals with Coronary Artery Disease.

Rationale: Untreated obstructive sleep apnea (OSA) is associated with adverse outcomes in patients with coronary artery disease (CAD). Continuous positive airway pressure (CPAP) is the most common treatment, but despite interventions addressing established adherence determinants, CPAP use remains poor. Objectives: To determine whether physiological traits that cause OSA are associated with long-term CPAP adherence in patients with CAD. Methods: Participants in the RICCADSA (Randomized Intervention with CPAP in CAD and OSA) trial with objective CPAP adherence (h/night) over 2 years and analyzable raw polysomnography data were included (N = 249). The physiological traits-loop gain, arousal threshold (ArTH), pharyngeal collapsibility (Vpassive), and pharyngeal muscle compensation (Vcomp)-were measured by using polysomnography. Linear mixed models were used to assess the relationship between the traits and adherence. We also compared actual CPAP adherence between those with physiologically predicted "poor" adherence (lowest quartile of predicted adherence) and those with physiologically predicted "good" adherence (all others). Measurements and Main Results: The median (interquartile range) CPAP use declined from 3.2 (1.0-5.8) h/night to 3.0 (0.0-5.6) h/night over 24 months (P < 0.001). In analyses adjusted for demographics, anthropometrics, OSA characteristics, and clinical comorbidities, a lower ArTH was associated with worse CPAP adherence (0.7 h/SD of the ArTH; P = 0.021). Both high and low Vcomp were associated with lower adherence (P = 0.008). Those with predicted poor adherence exhibited markedly lower CPAP use than those with predicted good adherence for up to 2 years of follow-up (group differences of 2.0-3.2 h/night; P < 0.003 for all). Conclusions: A low ArTH, as well as a very low and high Vcomp, are associated with worse long-term CPAP adherence in patients with CAD and OSA. Physiological traits-alongside established determinants-may help predict and improve CPAP adherence. Clinical trial registered with www.clinicaltrials.gov (NCT00519597).

Polysomnographic Phenotypes of Obstructive Sleep Apnea and Incident Type 2 Diabetes: Results from the DREAM Study.

Rationale: Obstructive sleep apnea (OSA) is associated with cardiovascular disease and incident type 2 diabetes (T2DM). Seven OSA phenotypes, labeled on the basis of their most distinguishing polysomnographic features, have been shown to be differentially associated with incident cardiovascular disease. However, little is known about the relevance of polysomnographic phenotypes for the risk of T2DM. Objectives: To assess whether polysomnographic phenotypes are associated with incident T2DM and to compare the predictive value of baseline polysomnographic phenotypes with the Apnea-Hypopnea Index (AHI) for T2DM. Methods: The study included 840 individuals without baseline diabetes from a multisite observational U.S. veteran cohort who underwent OSA evaluation between 2000 and 2004, with follow-up through 2012. The primary outcome was incident T2DM, defined as no diagnosis at baseline and a new physician diagnosis confirmed by fasting blood glucose >126 mg/dL during follow-up. Relationships between the seven polysomnographic phenotypes (1. mild, 2. periodic limb movements of sleep [PLMS], 3. non-rapid eye movement and poor sleep, 4. rapid eye movement and hypoxia, 5. hypopnea and hypoxia, 6. arousal and poor sleep, and 7. combined severe) and incident T2DM were investigated using Cox proportional hazards regression and competing risk regression models with and without adjustment for baseline covariates. Likelihood ratio tests were conducted to compare the predictive value of the phenotypes with the AHI. Results: During a median follow-up period of 61 months, 122 (14.5%) patients developed incident T2DM. After adjustment for baseline sociodemographics, fasting blood glucose, body mass index, comorbidities, and behavioral risk factors, hazard ratios among persons with "hypopnea and hypoxia" and "PLMS" phenotypes as compared with persons with "mild" phenotype were 3.18 (95% confidence interval [CI], 1.53-6.61] and 2.26 (95% CI, 1.06-4.83) for incident T2DM, respectively. Mild OSA (5 ⩽ AHI < 15) (vs. no OSA) was directly associated with incident T2DM in both unadjusted and multivariable-adjusted regression models. The addition of polysomnographic phenotypes, but not AHI, to known T2DM risk factors greatly improved the predictive value of the computed prediction model. Conclusions: Polysomnographic phenotypes "hypopnea and hypoxia" and "PLMS" independently predict risk of T2DM among a predominantly male veteran population. Polysomnographic phenotypes improved T2DM risk prediction comared with the use of AHI.

A Young Man With Hemoptysis and Cavitary Lung Lesions.

CASE PRESENTATION: A man in his 20s presented with 2 months of mild fatigue and intermittent hemoptysis of less than a tablespoon per episode. He was previously healthy and was on no medications. He denied fevers, night sweats, weight loss, wheezing, dyspnea, musculoskeletal symptoms, and rashes. He had emigrated from a South American country to the United States 3 years earlier. He worked as a groundskeeper but had no exposures to animals, mold, or dusts. He reported rare prior cigarette smoking with no history of alcohol or drug use. He was unsure whether he had received the Bacillus Calmette-Guérin vaccine.

Polysomnographic phenotypes and their cardiovascular implications in obstructive sleep apnoea.

BACKGROUND: Obstructive sleep apnoea (OSA) is a heterogeneous disorder, and improved understanding of physiologic phenotypes and their clinical implications is needed. We aimed to determine whether routine polysomnographic data can be used to identify OSA phenotypes (clusters) and to assess the associations between the phenotypes and cardiovascular outcomes. METHODS: Cross-sectional and longitudinal analyses of a multisite, observational US Veteran (n=1247) cohort were performed. Principal components-based clustering was used to identify polysomnographic features in OSA's four pathophysiological domains (sleep architecture disturbance, autonomic dysregulation, breathing disturbance and hypoxia). Using these features, OSA phenotypes were identified by cluster analysis (K-means). Cox survival analysis was used to evaluate longitudinal relationships between clusters and the combined outcome of incident transient ischaemic attack, stroke, acute coronary syndrome or death. RESULTS: Seven patient clusters were identified based on distinguishing polysomnographic features: 'mild', 'periodic limb movements of sleep (PLMS)', 'NREM and arousal', 'REM and hypoxia', 'hypopnoea and hypoxia', 'arousal and poor sleep' and 'combined severe'. In adjusted analyses, the risk (compared with 'mild') of the combined outcome (HR (95% CI)) was significantly increased for 'PLMS', (2.02 (1.32 to 3.08)), 'hypopnoea and hypoxia' (1.74 (1.02 to 2.99)) and 'combined severe' (1.69 (1.09 to 2.62)). Conventional apnoea-hypopnoea index (AHI) severity categories of moderate (15≤AHI<30) and severe (AHI ≥30), compared with mild/none category (AHI <15), were not associated with increased risk. CONCLUSIONS: Among patients referred for OSA evaluation, routine polysomnographic data can identify physiological phenotypes that capture risk of adverse cardiovascular outcomes otherwise missed by conventional OSA severity classification.

Phenotypes in obstructive sleep apnea: A definition, examples and evolution of approaches.

Obstructive sleep apnea (OSA) is a complex and heterogeneous disorder and the apnea hypopnea index alone can not capture the diverse spectrum of the condition. Enhanced phenotyping can improve prognostication, patient selection for clinical trials, understanding of mechanisms, and personalized treatments. In OSA, multiple condition characteristics have been termed "phenotypes." To help classify patients into relevant prognostic and therapeutic categories, an OSA phenotype can be operationally defined as: "A category of patients with OSA distinguished from others by a single or combination of disease features, in relation to clinically meaningful attributes (symptoms, response to therapy, health outcomes, quality of life)." We review approaches to clinical phenotyping in OSA, citing examples of increasing analytic complexity. Although clinical feature based OSA phenotypes with significant prognostic and treatment implications have been identified (e.g., excessive daytime sleepiness OSA), many current categorizations lack association with meaningful outcomes. Recent work focused on pathophysiologic risk factors for OSA (e.g., arousal threshold, craniofacial morphology, chemoreflex sensitivity) appears to capture heterogeneity in OSA, but requires clinical validation. Lastly, we discuss the use of machine learning as a promising phenotyping strategy that can integrate multiple types of data (genomic, molecular, cellular, clinical) to identify unique, meaningful OSA phenotypes.

The Determining Risk of Vascular Events by Apnea Monitoring (DREAM) study: design, rationale, and methods.

PURPOSE: The goal of the Determining Risk of Vascular Events by Apnea Monitoring (DREAM) study is to develop a prognostic model for cardiovascular outcomes, based on physiologic variables-related to breathing, sleep architecture, and oxygenation-measured during polysomnography in US veterans. METHODS: The DREAM study is a multi-site, retrospective observational cohort study conducted at three Veterans Affairs (VA) centers (West Haven, CT; Indianapolis, IN; Cleveland, OH). Veterans undergoing polysomnography between January 1, 2000 and December 31, 2004 were included based on referral for evaluation of sleep-disordered breathing, documented history and physical prior to sleep testing, and ≥2-h sleep monitoring. Demographic, anthropomorphic, medical, medication, and social history factors were recorded. Measures to determine sleep apnea, sleep architecture, and oxygenation were recorded from polysomnography. VA Patient Treatment File, VA-Medicare Data, Vista Computerized Patient Record System, and VA Vital Status File were reviewed on dates subsequent to polysomnography, ranging from 0.06 to 8.8 years (5.5 ± 1.3 years; mean ± SD). RESULTS: The study population includes 1840 predominantly male, middle-aged veterans. As designed, the main primary outcome is the composite endpoint of acute coronary syndrome, stroke, transient ischemic attack, or death. Secondary outcomes include incidents of neoplasm, congestive heart failure, cardiac arrhythmia, diabetes, depression, and post-traumatic stress disorder. Laboratory outcomes include measures of glycemic control, cholesterol, and kidney function. (Actual results are pending.) CONCLUSIONS: This manuscript provides the rationale for the inclusion of veterans in a study to determine the association between physiologic sleep measures and cardiovascular outcomes and specifically the development of a corresponding outcome-based prognostic model.

Attitudes of US medical trainees towards neurology education: "Neurophobia" - a global issue.

BACKGROUND: Several studies in the United Kingdom and Asia have suggested that medical students and residents have particular difficulty in diagnosing and managing patients with neurological problems. Little recent information is available for US trainees. We examined whether students and residents at a US university have difficulty in dealing with patients with neurological problems, identified the perceived sources of these difficulties and provide suggestions for the development of an effective educational experience in neurology. METHODS: A questionnaire was administered to third and fourth year medical students at a US school of medicine and to residents of an internal medicine residency program affiliated with that school. Perceived difficulties with eight medical specialties, including neurology, were examined. Methods considered to be most useful for learning medicine were documented. Reasons why neurology is perceived as difficult and ways to improve neurological teaching were assessed. RESULTS: 152 surveys were completed. Participation rates varied, with medical students having higher response rates (> 50%) than medical residents (27%-48%). Respondents felt that neurology was the medical specialty they had least knowledge in (p < 0.001) and was most difficult (p < 0.001). Trainees also felt they had the least confidence when dealing with patients with neurological complaints (p < 0.001). Residents felt more competent in neurology than students (p < 0.001). The paramount reasons for perceived difficulties with neurology were the complexity of neuroanatomy, limited patient exposure and insufficient teaching. Transition from pre-clinical to clinical medicine led to a doubling of "poor" ratings for neurological teaching. Over 80% of the respondents felt that neurology teaching could be improved through greater exposure to patients and more bedside tutorials. CONCLUSIONS: Medical students and residents at this US medical university found neurology difficult. Although this is consistent with prior reports from Europe and Asia, studies in other universities are needed to confirm generalizability of these findings. The optimal opportunity for improvement is during the transition from preclinical to clinical years. Enhanced integration of basic neurosciences and clinical neurology with emphasis on increased bedside tutorials and patient exposure should improve teaching. Studies are needed to quantify the effect of these interventions on confidence of trainees when dealing with patients presenting with neurological complaints.

The influence of measurement conditions on the Hammett acidity function of solid pharmaceutical excipients.

In this work the Hammett acidity function has been measured to assess the relative acidity of excipients used in the preparation of pharmaceutical solid dosage forms. A systematic series of experiments is reported which illustrates how the selection of the measurement conditions can influence the results of such determinations. Although the technique is somewhat empirical and relies on several key assumptions it is shown that very consistent results can be achieved by carefully controlling the measurement conditions. It is also shown that by taking this approach laboratory-to-laboratory variation can be reduced to a negligible level and the influences of subtle changes in the acidity of pharmaceutical excipients due to intrinsic variations in their physical properties or due to different processing histories can be detected and quantified.

Simulation of roller compaction using a laboratory scale compaction simulator.

A method for simulation of the roller compaction process using a laboratory scale compaction simulator was developed. The simulation was evaluated using microcrystalline cellulose as model material and ribbon solid fraction and tensile strength as key ribbon properties. When compacted to the same solid fractions, real and simulated ribbons exhibited similar compression behavior and equivalent mechanical properties (tensile strengths). Thus, simulated and real ribbons are expected to result in equivalent granulations. Although the simulation cannot account for some roller compaction aspects (non-homogeneous ribbon density and material bypass) it enables prediction of the effects that critical parameters such as roll speed, pressure and radius have on the properties of ribbons using a fraction of material required by conventional roller compaction equipment. Furthermore, constant ribbon solid fraction and/or tensile strength may be utilized as scale up and transfer factors for the roller compaction process. The improved material efficiency and product transfer methods could enable formulation of tablet dosage forms earlier in drug product development.