Economic Assessment of 4 Approaches to the Diagnosis and Initial Treatment of Sleep Apnea

BACKGROUND: A dilemma faced by health-care administrators is that need greatly outstrips capacity for diagnosing and treating sleep apnea, with such decisions carrying significant economic consequences. Our objective was to develop an economic model to estimate the relative costs of 4 approaches for diagnosis and initial treatment of sleep apnea. METHODS: The analysis consisted of developing a mathematical model depicting possible diagnostic and treatment approaches to the care of patients with sleep apnea; developing 4 clinical scenarios to describe distinct approaches to the management of sleep apnea patients (in-laboratory, unattended, direct-to-autotitrating PAP [auto-PAP], and mixed); and identifying costs associated with each scenario. We created a hypothetical cohort of 1,000 patients with 85% prevalence of sleep apnea to generate cost estimates. RESULTS: The driver of per-patient costs was the total number of sleep studies, which varied widely across scenarios: from 425 for the direct-to-auto-PAP approach to 1,441 in the unattended approach. The scenarios also differed in per-patient costs: Per-patient costs excluding facility startup costs were $456 for direct-to-auto-PAP,$913 for in-laboratory, $991 for mixed, and$1,090 for unattended. CONCLUSIONS: Approaches to diagnosing and treating sleep apnea that emphasized early application of auto-PAP had lower per-patient costs

Chronic obstructive pulmonary disease in older persons: A comparison of two spirometric definitions

SummaryBackgroundAmong older persons, we previously endorsed a two-step spirometric definition of chronic obstructive pulmonary disease (COPD) that requires a ratio of forced expiratory volume in 1sec to forced vital capacity (FEV1/FVC) below .70, and an FEV1 below the 5th or 10th standardized residual percentile (“SR-tile strategy”).ObjectiveTo evaluate the clinical validity of an SR-tile strategy, compared to a current definition of COPD, as published by the Global Initiative for Obstructive Lung Disease (GOLD-COPD), in older persons.MethodsWe assessed national data from 2480 persons aged 65–80 years. In separate analyses, we evaluated the association of an SR-tile strategy with mortality and respiratory symptoms, relative to GOLD-COPD. As per convention, GOLD-COPD was defined solely by an FEV1/FVC<.70, with severity staged according to FEV1 cut-points at 80 and 50 percent predicted (%Pred).ResultsAmong 831 participants with GOLD-COPD, the risk of death was elevated only in 179 (21.5%) of those who also had an FEV1<5th SR-tile; and the odds of having respiratory symptoms were elevated only in 310 (37.4%) of those who also had an FEV1<10th SR-tile. In contrast, GOLD-COPD staged at an FEV1 50–79%Pred led to misclassification (overestimation) in terms of 209 (66.4%) and 77 (24.6%) participants, respectively, not having an increased risk of death or likelihood of respiratory symptoms.ConclusionRelative to an SR-tile strategy, the majority of older persons with GOLD-COPD had neither an increased risk of death nor an increased likelihood of respiratory symptoms. These results raise concerns about the clinical validity of GOLD guidelines in older persons

Age Differences in the Association of Obstructive Sleep Apnea Risk with Cognition and Quality of Life

Using a sample of 2925 stroke-free participants drawn from a national population-based study, we examined cross-sectional associations of obstructive sleep apnea risk (OSA) with cognition and quality of life and whether these vary with age, while controlling for demographics and co-morbidities. Included participants from the REasons for Geographic And Racial Differences in Stroke Study were aged 47-93. OSA risk was categorized as high or low based on responses to the Berlin Sleep Questionnaire. Cognitive function was assessed with standardized fluency and recall measures. Depressive symptoms were assessed with the four-item Center for Epidemiologic Studies Depression Scale. Health-related Quality of Life (HRQoL) was assessed with the Medical Outcomes Study Short Form-12 (SF-12). MANCOVA statistics were applied separately to the cognitive and quality of life dependent variables while accounting for potential confounders (demographics, co-morbidities). In fully adjusted models, those at high risk for OSA had significantly lower cognitive scores (Wilks’ Lambda = 0.996, F(3, 2786) = 3.31, p < .05) and lower quality of life (depressive symptoms and HRQoL) (Wilks’ Lambda = 0.989, F(3, 2786) = 10.02, p < .0001). However, some of the associations were age-dependent. Differences in cognition and quality of life between those at high and low obstructive sleep apnea risk were most pronounced during middle age, with attenuated effects after age 70

Sex-Specific Prediction Models for Sleep Apnea From the Hispanic Community Health Study/Study of Latinos

OBJECTIVE: We developed and validated the first-ever sleep apnea (SA) risk calculator in a large population-based cohort of Hispanic/Latino subjects. METHODS: Cross-sectional data on adults from the Hispanic Community Health Study/Study of Latinos (2008-2011) were analyzed. Subjective and objective sleep measurements were obtained. Clinically significant SA was defined as an apnea-hypopnea index ≥ 15 events per hour. Using logistic regression, four prediction models were created: three sex-specific models (female-only, male-only, and a sex × covariate interaction model to allow differential predictor effects), and one overall model with sex included as a main effect only. Models underwent 10-fold cross-validation and were assessed by using the C statistic. SA and its predictive variables; a total of 17 variables were considered. RESULTS: A total of 12,158 participants had complete sleep data available; 7,363 (61%) were women. The population-weighted prevalence of SA (apnea-hypopnea index ≥ 15 events per hour) was 6.1% in female subjects and 13.5% in male subjects. Male-only (C statistic, 0.808) and female-only (C statistic, 0.836) prediction models had the same predictor variables (ie, age, BMI, self-reported snoring). The sex-interaction model (C statistic, 0.836) contained sex, age, age × sex, BMI, BMI × sex, and self-reported snoring. The final overall model (C statistic, 0.832) contained age, BMI, snoring, and sex. We developed two websites for our SA risk calculator: one in English (https://www.montefiore.org/sleepapneariskcalc.html) and another in Spanish (http://www.montefiore.org/sleepapneariskcalc-es.html). CONCLUSIONS: We created an internally validated, highly discriminating, well-calibrated, and parsimonious prediction model for SA. Contrary to the study hypothesis, the variables did not have different predictive magnitudes in male and female subjects

Circumstances and consequences of falls among people with chronic stroke

Falls are common after stroke; however, circumstances and consequences are relatively unknown. Our objectives were to identify the differences between fallers and non-fallers among people with chronic stroke, identify the circumstances of fall events, and examine the consequences of the falls. This is a secondary data analysis; all participants included sustained a stroke. Variables included demographics, stroke characteristics, and comorbidities. Falls were collected via self-report, and circumstances and consequences were derived from participant description of the event and categorized as appropriate. Among 160 participants, 53 (33%) reported a fall during the 1 yr period. Circumstances of falls were categorized as intrinsic or extrinsic. Location and circumstance of the fall were included: 70% occurred at home and 40% were associated with impaired physical or mental state (e.g., inattention to tying shoes). Additionally, 21% of falls were associated with activities of daily living and mobility and 34% with slips or trips. The majority who fell sustained an injury (72%). Injuries ranged from bruising to fractures, and 55% of those with an injury sought medical care (32% to emergency department). Poststroke falls are associated with an alarming rate of injury and healthcare utilization. Targeting mental and physical states may be key to fall prevention

Sleep quality in middle-aged and elderly Chinese: distribution, associated factors and associations with cardio-metabolic risk factors

Background Poor sleep quality has been associated with increased risk of heart disease, diabetes and mortality. However, limited information exists on the distribution and determinants of sleep quality and its associations with cardio-metabolic risk factors in Chinese populations. We aimed to evaluate this in the current study. Methods A cross-sectional survey conducted in 2005 of 1,458 men and 1,831 women aged 50–70 years from urban and rural areas of Beijing and Shanghai. Using a questionnaire, sleep quality was measured in levels of well, common and poor. Comprehensive measures of socio-demographical and health factors and biomarkers of cardio-metabolic disease were recorded. These were evaluated in association with sleep quality using logistic regression models. Results Half of the population reported good sleep quality. After adjusting for potential confounders, women and Beijing residents had almost half the probability to report good sleep quality. Good physical and mental health (good levels of self-rated health (OR 2.48; 95%CI 2.08 to 2.96) and no depression (OR 4.05; 95%CI 3.12 to 5.26)) related to an increased chance of reporting good sleep quality, whereas short sleep duration (<7 hrs OR 0.10; 95%CI 0.07 to 0.14)) decreased it substantially. There were significant associations between levels of sleep quality and concentrations of plasma insulin, total and LDL cholesterol, and index of insulin resistance. Conclusion Levels of good sleep quality in middle-age and elderly Chinese were low. Gender, geographical location, self-rated health, depression and sleep quantity were major factors associated with sleep quality. Prospective studies are required to distil the factors that determine sleep quality and the effects that sleep patterns exert on cardio-metabolic health

Development, Validation, and Assessment of an Ischemic Stroke or Transient Ischemic Attack-Specific Prediction Tool for Obstructive Sleep Apnea

BACKGROUND: Screening instruments for obstructive sleep apnea (OSA), as used routinely to guide clinicians regarding patient referral for polysomnography (PSG), rely heavily on symptomatology. We sought to develop and validate a cerebrovascular disease-specific OSA prediction model less reliant on symptomatology, and to compare its performance with commonly used screening instruments within a population with ischemic stroke or transient ischemic attack (TIA). METHODS: Using data on demographic factors, anthropometric measurements, medical history, stroke severity, sleep questionnaires, and PSG from 2 independently derived, multisite, randomized trials that enrolled patients with stroke or TIA, we developed and validated a model to predict the presence of OSA (i.e., Apnea-Hypopnea Index ≥5 events per hour). Model performance was compared with that of the Berlin Questionnaire, Epworth Sleepiness Scale (ESS), the Snoring, Tiredness, Observed apnea, high blood Pressure, Body mass index, Age, Neck circumference, and Gender instrument, and the Sleep Apnea Clinical Score. RESULTS: The new SLEEP Inventory (Sex, Left heart failure, ESS, Enlarged neck, weight [in Pounds], Insulin resistance/diabetes, and National Institutes of Health Stroke Scale) performed modestly better than other instruments in identifying patients with OSA, showing reasonable discrimination in the development (c-statistic .732) and validation (c-statistic .731) study populations, and having the highest negative predictive value of all in struments. CONCLUSIONS: Clinicians should be aware of these limitations in OSA screening instruments when making decisions about referral for PSG. The high negative predictive value of the SLEEP INventory may be useful in determining and prioritizing patients with stroke or TIA least in need of overnight PSG

Day Napping and Short Night Sleeping Are Associated With Higher Risk of Diabetes in Older Adults

OBJECTIVE—To examine whether day napping or short night sleeping is associated with higher risk of diabetes. RESEARCH DESIGN AND METHODS—This was a prospective study of hours of day napping and night sleeping assessed in 1996–1997 in relation to diabetes diagnosed between 2000 and 2006 (n = 10,143) among 174,542 participants in the National Institutes of Health (NIH)-AARP Diet and Health Study. Odds ratios (ORs) and 95% CI were derived from multivariate logistic regression models. RESULTS—Longer day napping was associated with a higher risk of diabetes. After adjustment for potential confounders, ORs were 1.23 (95% CI 1.18–1.29) for those reporting <1 h and 1.55 (95% CI 1.45–1.66) for those reporting ≥1 h of napping compared with individuals who did not nap ($P_{trend}$ < 0.0001). For night sleeping, with 7–8 h as the referent, the OR was 1.46 (95% CI 1.31–1.63) for <5 h, 1.11 (1.06–1.16) for 5–6 h, and 1.11 (0.99–1.24) for ≥9 h. In both analyses, additional adjustment for BMI only modestly attenuated the associations. Further analysis showed a statistically significant interaction between hours of napping and sleeping on diabetes ($P_{interaction}$ < 0.0001). Among participants with no napping, only short night sleeping was associated with higher occurrence of diabetes, whereas among those with ≥1 h of napping, both long and short sleeping was associated with higher risk. CONCLUSIONS—Day napping and short night sleeping are associated with higher risk of diabetes. The association between sleep duration and diabetes may be modified by napping habit

Diagnosing and managing sleep apnea in patients with chronic cerebrovascular disease: a randomized trial of a home-based strategy

Background Obstructive sleep apnea is common and associated with poor outcomes after stroke or transient ischemic attack (TIA). We sought to determine whether the intervention strategy improved sleep apnea detection, obstructive sleep apnea (OSA) treatment, and hypertension control among patients with chronic cerebrovascular disease and hypertension. Methods In this randomized controlled strategy trial intervention, patients received unattended polysomnography at baseline, and patients with OSA (apnea-hypopnea index ≥5 events/h) received auto-titrating continuous positive airway pressure (CPAP) for up to 1 year. Control patients received usual care and unattended polysomnography at the end of the study, to identify undiagnosed OSA. Both groups received 24-h blood pressure assessments at baseline and end of the study. “Excellent” CPAP adherence was defined as cumulative use of ≥4 h/night for ≥70% of the nights. Results Among 225 randomized patients (115 control; 110 intervention), 61.9% (120/194) had sleep apnea. The strategy successfully diagnosed sleep apnea with 97.1% (102/105) valid studies; 90.6% (48/53, 95% CI 82.7–98.4%) of sleep apnea was undiagnosed among control patients. The intervention improved long-term excellent CPAP use: 38.6% (22/57) intervention versus 0% (0/2) control (p < 0.0001). The intervention did not improve hypertension control in this population with well-controlled baseline blood pressure: intervention, 132.7 mmHg (±standard deviation, 14.1) versus control, 133.8 mmHg (±14.0) (adjusted difference, −1.1 mmHg, 95% CI (−4.2, 2.0)), p = 0.48). Conclusions Patients with cerebrovascular disease and hypertension have a high prevalence of OSA. The use of portable polysomnography, and auto-titrating CPAP in the patients’ homes, improved both the diagnosis and the treatment for sleep apnea compared with usual care but did not lower blood pressure

Infarct Location and Sleep Apnea: Evaluating the Potential Association in Acute Ischemic Stroke.

Background: The literature about the relationship between obstructive sleep apnea (OSA) and stroke location is conflicting with some studies finding an association and others demonstrating no relationship. Among acute ischemic stroke patients, we sought to examine the relationship between stroke location and the prevalence of OSA; OSA severity based on apnea-hypopnea index (AHI), arousal frequency, and measure of hypoxia; and number of central and obstructive respiratory events. Methods: Data were obtained from patients who participated in a randomized controlled trial (NCT01446913) that evaluated the effectiveness of a strategy of diagnosing and treating OSA among patients with acute ischemic stroke and transient ischemic attack. Stroke location was classified by brain imaging reports into subdivisions of lobes, subcortical areas, brainstem, cerebellum, and vascular territory. The association between acute stroke location and polysomnographic findings was evaluated using logistic regression for OSA presence and negative binomial regression for AHI. Results: Among 73 patients with complete polysomnography and stroke location data, 58 (79%) had OSA. In unadjusted models, no stroke location variable was associated with the prevalence or severity of OSA. Similarly, in multivariable modeling, groupings of stroke location were also not associated with OSA presence. Conclusions: These results indicate that OSA is present in the majority of stroke patients and imply that stroke location cannot be used to identify a group with higher risk of OSA. The results also suggest that OSA likely predated the stroke. Given this high overall prevalence, strong consideration should be given to obtaining polysomnography for all ischemic stroke patients