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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p

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

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 (V_passive), and pharyngeal muscle compensation (V_comp)-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 V_comp 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 V_comp, 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

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 (V_passive), and pharyngeal muscle compensation (V_comp)-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 V_comp 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 V_comp, 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