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.

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.

Aging-Related Considerations When Evaluating the Forced Expiratory Volume in 1 Second (FEV1) Over Time.

BACKGROUND: Forced expiratory volume in 1 second (FEV1) over time is commonly expressed in liters and percent predicted (%Pred), or alternatively in L/m(3) and Z-scores-which approach is more clinically meaningful has not been evaluated. Because it uniquely accounts for the effect of aging on FEV1 and spirometric performance, we hypothesized that the Z-score approach is more clinically meaningful, based on associations between cardiopulmonary predictors and FEV1 over time. METHODS: Using linear mixed-effects models and data from the Baltimore Longitudinal Study on Aging, including 501 white participants aged 40-95 who had completed at least three longitudinal spirometric assessments, we evaluated the associations between cardiopulmonary predictors (obesity, smoking status, hypertension, chronic bronchitis, diabetes mellitus, and myocardial infarction) and FEV1 over time, in liters, %Pred, L/m(3), and Z-scores. RESULTS: Mean baseline values for FEV1 were 3.240L, 96.4%Pred, 0.621L/m(3), and -0.239 as a Z-score (40.6th percentile). The annual decline in FEV1 was 0.040L, 0.234 %Pred, 0.007L/m(3), and 0.008 Z-score units. Baseline age was associated with FEV1 over time in liters and L/m(3) (p < .001), and included a time interaction for %Pred (p < .001), but was not associated with Z-scores (p = .933). The associations of cardiopulmonary predictors with FEV1 over time were all significant when using Z-scores (p < .05), but varied for other methods of expressing FEV1. CONCLUSION: A Z-score approach is more clinically meaningful when evaluating FEV1 over time, as it accounted for the effect of aging and was more frequently associated with multiple cardiopulmonary predictors.

Disentangling racial/ethnic and socioeconomic differences in self-reported sleep measures: the Boston Area Community Health Survey.

BACKGROUND: Racial/ethnic differences in sleep are widely reported. However, the extent to which socioeconomic factors account for crude variation in sleep parameters by racial/ethnic groups is not clearly understood. METHODS: We studied 4144 individuals in the Boston Area Community Health Survey (2006-2010), a racially/ethnically balanced population-based cohort of black, Hispanic, and white men and women. Self-reported sleep measures were sleep duration, sleep latency, restless sleep, risk for sleep apnea, and sleep medication use. We assessed changes in the age- and sex-adjusted association between race/ethnicity and sleep measures after additional adjustment for individual socioeconomic factors (income, education, and employment) and lifestyle and behavioral factors. RESULTS: Self-identified non-Hispanic black race/ethnicity was significantly associated with higher odds of short sleep duration (fully adjusted odds ratio [OR], 1.93; 95% confidence interval [CI], 1.41-2.64), longer sleep latency (fully adjusted, 20.9% longer; 95% CI, 4.1-41.9), and lower odds of pharmaceutical sleep aid use (fully adjusted OR: 0.47, 95% CI: 0.34, 0.65) than white race/ethnicity. Education level accounted for the most substantial reduction in estimates of the age- and sex-adjusted association between black race/ethnicity and short sleep duration and sleep latency. Having less than a 4-year college education was associated with approximately 55% lower sleep latency than having postgraduate education. No significant associations were observed comparing Hispanic to white participants. CONCLUSIONS: Significant variation was observed between black and white race/ethnicity in short sleep duration, sleep latency, and sleep aid use. Although considerable variation in sleep by race/ethnicity was explained by education level, additional variation in self-reported sleep by race/ethnicity may be due to other unmeasured socioeconomic, lifestyle, or behavioral factors.

Geographic variations in sleep duration: a multilevel analysis from the Boston Area Community Health (BACH) Survey.

BACKGROUND: Sleep plays an important role in health and varies by social determinants. Little is known, however, about geographic variations in sleep and the role of individual-level and neighbourhood-level factors. METHODS: We used a multilevel modelling approach to quantify neighbourhood variation in self-reported sleep duration (very short <5 h; short 5-6.9 h; normative 7-8.9 h; long ≥9 h) among 3591 participants of the Boston Area Community Health Survey. We determined whether geographic variations persisted with control for individual-level demographic, socioeconomic status (SES) and lifestyle factors. We then determined the role of neighbourhood SES (nSES) in geographic variations. Additional models considered individual health factors. RESULTS: Between neighbourhood differences accounted for a substantial portion of total variability in sleep duration. Neighbourhood variation persisted with control for demographics, SES and lifestyle factors. These characteristics accounted for a portion (6-20%) of between-neighbourhood variance in very short, short and long sleep, while nSES accounted for the majority of the remaining between-neighbourhood variances. Low and medium nSES were associated with very short and short sleep (eg, very short sleep OR=2.08; 95% CI 1.38 to 3.14 for low vs high nSES), but not long sleep. Further inclusion of health factors did not appreciably increase the amount of between-neighbourhood variance explained nor did it alter associations. CONCLUSIONS: Sleep duration varied by neighbourhood in a diverse urban setting in the northeastern USA. Individual-level demographics, SES and lifestyle factors explained some geographic variability, while nSES explained a substantial amount. Mechanisms associated with nSES should be examined in future studies to help understand and reduce geographic variations in sleep.

Diagnosis and Treatment of Sleep Apnea in patients' homes: the rationale and methods of the "GoToSleep" randomized-controlled trial.

BACKGROUND: The "Diagnosis and Treatment of Sleep Apnea in Cerebrovascular Disease" (GoToSleep) study is evaluating a strategy to improve the diagnosis and treatment of sleep apnea among veterans with stroke or transient ischemic attack (TIA) who also have hypertension. Specifically, the GoToSleep study was designed to overcome some of the barriers that exist within the Veterans Health Administration (VHA) to the timely diagnosis and treatment of sleep apnea by using ambulatory home-based polysomnography and auto-titrating continuous positive airway pressure (CPAP) to reduce the reliance on laboratory-based sleep studies. METHODS: The GoToSleep study is a prospective, multi-site, randomized, controlled strategy trial among an expected 318 veterans with cerebrovascular disease and hypertension who are assigned to an intervention group or a control group. Patients in the intervention group receive unattended polysomnography at baseline, and those with sleep apnea receive auto-titrating CPAP therapy for up to one year. Patients in the control group receive usual care and unattended polysomnography at the end of the study to identify the rate of undiagnosed sleep apnea. The primary objectives of the GoToSleep study are to determine whether a diagnostic and therapeutic intervention strategy among veterans with cerebrovascular disease and hypertension improves: (1) detection of sleep apnea; (2) appropriate treatment for sleep apnea; and (3) control of hypertension. Twenty-four-hour blood pressure assessments are made at baseline and at the end of the one-year study period for both groups. Antihypertensive medications and their doses are recorded at the time of the 24-hour blood pressure measurements. DISCUSSION: This manuscript provides the rationale for 4 key components of the design of the GoToSleep trial: the inclusion of patients with cerebrovascular disease and hypertension without the use of a measure of daytime sleepiness as an eligibility criterion; the use of portable polysomnography and auto-titrating CPAP in patients' homes rather than using sleep laboratory polysomnography with fixed pressure CPAP; the analytic approach to evaluating change in blood pressure in the context of change in antihypertensive medications; and the use of a usual care control group.