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Objective Insomnia and restless legs syndrome (RLS) are defined by self-reported symptoms, and polysomnography (PSG) is not routinely indicated. Occult obstructive sleep apnea (OSA), common even in asymptomatic adults, may complicate management of patients presenting with insomnia or restless legs. To this end, we investigated objective sleep apnea metrics in a large retrospective cohort according to self-reported symptom profiles. Methods We compared sleep apnea findings in patients referred to our center according to self-reported symptoms associated with insomnia, sleep apnea, and restless legs. The cohort included over 1900 adults who underwent diagnostic (n = 1418) or split-night (n = 504) PSGs and completed a symptom and medical history questionnaire. Results More than 30% of patients who did not endorse any OSA symptoms, but did endorse insomnia or restless legs symptoms, were found to have OSA based on apnea–hypopnea index (AHI) >5 during overnight laboratory testing. Regression models of the full cohort showed that the risk of OSA was related, as expected, to older age, male sex, elevated body mass index, and presence of OSA symptoms. The presence of insomnia symptoms did not alter the risk of OSA. The presence of restless legs symptoms showed a small odds ratio for lowered OSA risk. Conclusions Objective evidence of OSA occurs similarly in those with insomnia or restless legs symptoms, even among those without self-reported OSA symptoms. Providers should be aware of the potential for occult OSA in populations with insomnia and restless legs, which may complicate their management in addition to presenting an independent medical risk itself.

This paper examined structural, social, and personal characteristics that shape the processes of gender affirmation and body modification among transgender persons (assigned male at birth) in Bogotá, Colombia. Qualitative data from life-history interviews (N=14) and a focus group (N=11) explored research questions concerning the ways in which the internal psychological and external contextual processes influence individuals' decisions and behaviors concerning hormonal treatment, injections, or surgery. Research questions concerning practices and consequences of treatment performed without medical supervision were addressed through qualitative data, as well as quantitative data from 58 transgender participants. Findings indicated variation in ways participants conceptualized gender (e.g., binary or fluid), but an increased feminine presentation was a strong personal desire expressed by many and often encouraged by romantic partners and transgender friends. Transgender individuals within participants' social networks were frequently instrumental not only in providing information about hormones and contouring injections, but also in carrying out procedures-sometimes with negative consequences. Body modification procedures occurred primarily outside the health care system, due to limited access to or awareness of medical care, societal stigma, social norms within the transgender community, and personal decision-making. Public health approaches to protect the health of transgender persons undergoing body modification were suggested.

The diagnosis of insomnia rests on self-report of difficulty initiating or maintaining sleep. However, subjective reports may be unreliable, and possibly may vary by the method of inquiry. We investigated this possibility by comparing within-individual response to direct versus indirect time queries after overnight polysomnography.We obtained self-reported sleep-wake times via morning questionnaires in 879 consecutive adult diagnostic polysomnograms. Responses were compared within subjects (direct versus indirect query) and across groups defined by apnea-hypopnea index and by self-reported insomnia symptoms in pre-sleep questionnaires. Direct queries required a time duration response, while indirect queries required clock times from which we calculated time durations.Direct and indirect queries of sleep latency were the same in only 41% of cases, and total sleep time queries matched in only 5.4%. For both latency and total sleep, the most common discrepancy involved the indirect value being larger than the direct response. The discrepancy between direct and indirect queries was not related to objective sleep metrics. The degree of discrepancy was not related to the presence of insomnia symptoms, although patients reporting insomnia symptoms showed underestimation of total sleep duration by direct response.Self-reported sleep latency and total sleep time are often internally inconsistent when comparing direct and indirect survey queries of each measure. These discrepancies represent substantive challenges to effective clinical practice, particularly when diagnosis and management depends on self-reported sleep patterns, as with insomnia. Although self-reported sleep-wake times remains fundamental to clinical practice, objective measures provide clinically relevant adjunctive information.

Study objectives Ambulatory tracking of sleep and sleep pathology is rapidly increasing with the introduction of wearable devices. The objective of this study was to evaluate a wearable device which used novel computational analysis of the electrocardiogram (ECG), collected over multiple nights, as a method to track the dynamics of sleep quality in health and disease. Methods This study used the ECG as a primary signal, a wearable device, the M1, and an analysis of cardiopulmonary coupling to estimate sleep quality. The M1 measures trunk movements, the ECG, body position, and snoring vibrations. Data from three groups of patients were analyzed: healthy participants and people with sleep apnea and insomnia, obtained from multiple nights of recording. Analysis focused on summary measures and night-to-night variability, specifically the intraclass coefficient. Results Data were collected from 10 healthy participants, 18 people with positive pressure-treated sleep apnea, and 20 people with insomnia, 128, 65, and 121 nights, respectively. In any participant, all nights were consecutive. High-frequency coupling (HFC), the signal biomarker of stable breathing and stable sleep, showed high intraclass coefficients (ICCs) in healthy participants and people with sleep apnea (0.83, 0.89), but only 0.66 in people with insomnia. The only statistically significant difference between weekday and weekend in healthy subjects was HFC duration: 242.8 ± 53.8 vs. 275.8 ± 57.1 minutes (89 vs. 39 total nights), F(1,126) = 9.86, p = .002. Conclusions The M1 and similar wearable devices provide new opportunities to measure sleep in dynamic ways not possible before. These measurements can yield new biological insights and aid clinical management.

Study Objectives: Automated sleep staging has been previously limited by a combination of clinical and physiological heterogeneity. Both factors are in principle addressable with large data sets that enable robust calibration. However, the impact of sample size remains uncertain. The objectives are to investigate the extent to which machine learning methods can approximate the performance of human scorers when supplied with sufficient training cases and to investigate how staging performance depends on the number of training patients, contextual information, model complexity, and imbalance between sleep stage proportions. Methods: A total of 102 features were extracted from six electroencephalography (EEG) channels in routine polysomnography. Two thousand nights were partitioned into equal (n = 1000) training and testing sets for validation. We used epoch-by-epoch Cohen's kappa statistics to measure the agreement between classifier output and human scorer according to American Academy of Sleep Medicine scoring criteria. Results: Epoch-by-epoch Cohen's kappa improved with increasing training EEG recordings until saturation occurred (n = similar to 300). The kappa value was further improved by accounting for contextual (temporal) information, increasing model complexity, and adjusting the model training procedure to account for the imbalance of stage proportions. The final kappa on the testing set was 0.68. Testing on more EEG recordings leads to kappa estimates with lower variance. Conclusion: Training with a large data set enables automated sleep staging that compares favorably with human scorers. Because testing was performed on a large and heterogeneous data set, the performance estimate has low variance and is likely to generalize broadly.

Study Objectives Adaptive servo-ventilation (ASV) devices provide anticyclic pressure support for the treatment of central and/or complex sleep apnea, including heart failure patients. Variability in responses in the clinic and negative clinical trials motivated assessment of standard and novel signal biomarkers for ASV efficacy. Methods Multiple clinical databases were queried to assess potential signal biomarkers of ASV effectiveness, including the following: (1) attended laboratory adaptive ventilation titrations: 108, of which 66 had mainstream ETCO2 measurements; (2) AirView data in 98 participants, (3) complete data, from diagnostic polysomnogram (PSG) through review and prospective analysis of on-therapy data using SleepyHead freeware in 44 participants; and (4) hemodynamic data in the form of beat-to-beat blood pressure during ASV titration, using a Finometer in five participants. Results Signal biomarkers of reduced ASV efficacy were noted as follows: (1) an arousal index which markedly exceeded the respiratory event index during positive pressure titration; (2) persistent pressure cycling during long-term ASV therapy, visible in online review systems or reviewing data using freeware; (3) the ASV-associated pressure cycling induced arousals, sleep fragmentation, and blood pressure surges; and (4) elevated ratios of 95th percentile to median tidal volume, minute ventilation, and respiratory rate were associated with pressure cycling. High intraclass coefficients (>0.8) for machine apnea–hypopnea index and other extractable metrics were consistent with stability of patterns over multiple nights of use. Global clinical outcomes correlated negatively with pressure cycling. Conclusions Potential polysomnographic- and device-related signal biomarkers of ASV efficacy are described and may allow improved estimation of therapeutic effectiveness of adaptive ventilation.

Background Repetitive transcranial magnetic stimulation (rTMS) has been considered to be a promising technique for the treatment of neuropsychiatric disorders. However, little is known about the effectiveness of rTMS in the treatment of generalized anxiety disorder (GAD). Moreover, treatment data on comorbid GAD and insomnia remain lacking. The aim of this study was to examine the therapeutic effects of 1 Hz rTMS applied over the right parietal lobe on both anxiety and insomnia symptoms in patients with comorbid GAD and insomnia. Methods 36 patients were randomized to either sham or active rTMS group (n = 18 each group). The rTMS was administered over the right posterior parietal cortex (P4 electrode site) at a frequency of 1 Hz and an intensity of 90% of the resting motor threshold. Results Ten days of 1 Hz rTMS to the right parietal lobe significantly improved both anxiety and insomnia symptoms in the active group. Although the anxiety severity was not significantly correlated with insomnia severity at baseline, the improvement in the Hamilton Rating Scale for Anxiety (HRSA) scores were positively correlated with improvement in the Pittsburgh Sleep Quality Index (PSQI) scores. Conclusions The present study is the first randomized sham-controlled study to assess the effectiveness of low frequency rTMS on the right parietal lobe in patients with comorbid GAD and insomnia. Our results suggested that 1 Hz low frequency rTMS administered over the parietal cortex is effective for both anxiety and insomnia symptoms in patients with comorbid GAD and insomnia.

Background The primary metric extracted from the polysomnogram in patients with sleep apnea is the apnea-hypopnea index (or respiratory disturbance index) and its derivatives. Other phenomena of possible importance such as periods of stable breathing, features suggestive of high respiratory control loop gain, and sleep fragmentation phenotypes are not commonly generated in clinical practice or research. A broader phenotype designation can provide insights into biological processes, and possibly clinical therapy outcome effects. Methods The dataset used for this study was the archived baseline diagnostic polysomnograms from the Apnea Positive Pressure Long-term Efficacy Study (APPLES). The electrocardiogram (ECG)-derived cardiopulmonary coupling sleep spectrogram was computed from the polysomnogram. Sleep fragmentation phenotypes used thresholds of sleep efficiency (SE) ≤ 70%, non-rapid eye movement (NREM) sleep N1 ≥ 30%, wake after sleep onset (WASO) ≥ 60 min, and high frequency coupling (HFC) on the ECG-spectrogram ≤ 30%. Sleep consolidation phenotypes used thresholds of SE ≥ 90%, WASO ≤ 30 min, HFC ≥ 50% and N1 ≤ 10%. Multiple and logistic regression analysis explored cross-sectional associations with covariates and across phenotype categories. NREM vs. REM dominant apnea categories were identified when the NREM divided by REM respiratory disturbance index (RDI) was > 1. Results The data was binned first into mild, moderate, severe and extreme categories based on the respiratory disturbance index of

Compare the spike detection performance of three skilled humans and three computer algorithms.40 prolonged EEGs, 35 containing reported spikes, were evaluated. Spikes and sharp waves were marked by the humans and algorithms. Pairwise sensitivity and false positive rates were calculated for each human-human and algorithm-human pair. Differences in human pairwise performance were calculated and compared to the range of algorithm versus human performance differences as a type of statistical Turing test.5474 individual spike events were marked by the humans. Mean, pairwise human sensitivities and false positive rates were 40.0%, 42.1%, and 51.5%, and 0.80, 0.97, and 1.99/min. Only the Persyst 13 (P13) algorithm was comparable to humans - 43.9% and 1.65/min. Evaluation of pairwise differences in sensitivity and false positive rate demonstrated that P13 met statistical noninferiority criteria compared to the humans.Humans had only a fair level of agreement in spike marking. The P13 algorithm was statistically noninferior to the humans.This was the first time that a spike detection algorithm and humans performed similarly. The performance comparison methodology utilized here is generally applicable to problems in which skilled human performance is the desired standard and no external gold standard exists.

All living organisms depend on homeostasis, the complex set of interacting metabolic chemical reactions for maintaining life and well-being. This is no less true for psychiatric well-being than for physical well-being. Indeed, a focus on homeostasis forces us to see how inextricably linked mental and physical well-being are. This paper focuses on these linkages. In particular, it addresses the ways in which understanding of disturbed homeostasis may aid in creating classes of patients with mood and anxiety disorders based on such phenotypes. At the cellular level, we may be able to compensate for the inability to study living brain tissue through the study of homeostatic mechanisms in fibroblasts, pluripotent human cells, and mitochondria and determine how homeostasis is disturbed at the level of these peripheral tissues through exogenous stress. We also emphasize the remarkable opportunities for enhancing knowledge in this area that are offered by advances in technology. The study of human behavior, especially when combined with our greatly improved capacity to study unique but isolated populations, offers particularly clear windows into the relationships among genetic, environmental, and behavioral contributions to homeostasis.

SUMMARY Objectives: Anterior temporal lobectomy is curative for many patients with disabling medically refractory temporal lobe epilepsy, but carries an inherent risk of disabling verbal memory loss. Although accurate prediction of iatrogenic memory loss is becoming increasingly possible, it remains unclear how much weight such predictions should have in surgical decision making. Here we aim to create a framework that facilitates a systematic and integrated assessment of the relative risks and benefits of surgery versus medical management for patients with left temporal lobe epilepsy. Methods: We constructed a Markov decision model to evaluate the probabilistic outcomes and associated health utilities associated with choosing to undergo a left anterior temporal lobectomy versus continuing with medical management for patients with medically refractory left temporal lobe epilepsy. Three base-cases were considered, representing a spectrum of surgical candidates encountered in practice, with varying degrees of epilepsy-related disability and potential for decreased quality of life in response to post-surgical verbal memory deficits. Results: For patients with moderately severe seizures and moderate risk of verbal memory loss, medical management was the preferred decision, with increased quality-adjusted life expectancy. However, the preferred choice was sensitive to clinically meaningful changes in several parameters, including quality of life impact of verbal memory decline, quality of life with seizures, mortality rate with medical management, probability of remission following surgery, and probability of remission with medical management. Significance: Our decision model suggests that for patients with left temporal lobe epilepsy, quantitative assessment of risk and benefit should guide recommendation of therapy. In particular, risk for and potential impact of verbal memory decline should be carefully weighed against the degree of disability conferred by continued seizures on a patient-by-patient basis.

Obstructive sleep apnea (OSA) is a prevalent and treatable disorder of neurological and medical importance that is traditionally diagnosed through multi-channel laboratory polysomnography(PSG). However, OSA testing is increasingly performed with portable home devices using limited physiological channels. We tested the hypothesis that single channel respiratory effort alone could support automated quantification of apnea and hypopnea events. We developed a respiratory event detection algorithm applied to thoracic strain-belt data from patients with variable degrees of sleep apnea. We optimized parameters on a training set (n=57) and then tested performance on a validation set (n=59). The optimized algorithm correlated significantly with manual scoring in the validation set (R2 = 0.73 for training set, R2 = 0.55 for validation set; p0.92 and >0.85 using apnea-hypopnea index cutoff values of 5 and 15, respectively. Our findings demonstrate that manually scored AHI values can be approximated from thoracic movements alone. This finding has potential applications for automating laboratory PSG analysis as well as improving the performance of limited channel home monitors.

Within-session habituation and extinction learning co-occur as do subsequent consolidation of habituation (i.e., between-session habituation) and extinction memory. We sought to determine whether, as we predicted: (1) between-session habituation is greater across a night of sleep versus a day awake; (2) time-of-day accounts for differences; (3) between-session habituation predicts consolidation of extinction memory; (4) sleep predicts between-session habituation and/or extinction memory. Participants (N = 28) completed 4-5 sessions alternating between mornings and evenings over 3 successive days (2 nights) with session 1 in either the morning (N = 13) or evening (N = 15). Twelve participants underwent laboratory polysomnography. During 4 sessions, participants completed a loud-tone habituation protocol, while skin conductance response (SCR), blink startle electromyography (EMG), heart-rate acceleration and heart-rate deceleration (HRD) were recorded. For sessions 1 and 2, between-session habituation of EMG, SCR and HRD was greater across sleep. SCR and HRD were generally lower in the morning. Between-session habituation of SCR for sessions 1 and 2 was positively related to intervening (first night) slow wave sleep. In the evening before night 2, participants also underwent fear conditioning and extinction learning phases of a second protocol. Extinction recall was tested the following morning. Extinction recall was predicted only by between-session habituation of SCR across the same night (second night) and by intervening REM. We conclude that: (1) sleep augments between-session habituation, as does morning testing; (2) extinction recall is predicted by concurrent between-session habituation; and (3) both phenomena may be influenced by sleep.

The current clinical standard for quantifying sleep physiology is the laboratory polysomnogram, from which basic sleep–wake stages are determined. However, the complexity of sleep physiology has inspired alternative metrics that are providing additional insights into the rich dynamics of sleep. Electro-encephalography, magneto-encephalography, and functional magnetic resonance imaging represent advanced imaging modalities for understanding brain dynamics. These methods are complemented by autonomic measurements that provide additional important insights. We review here the spectrum of approaches that have been leveraged towards improved understanding of the complexity of sleep.

Sleep disturbance is common in bipolar disorder and negatively impacts its course of illness. The purpose of this study is to assess the feasibility and tolerability of a novel EKG-based home sleep monitoring device (M1) as well as a brief (two session) psychosocial sleep intervention for individuals with bipolar disorder. The sleep intervention is individually tailored for patients with insomnia or hypersomnia and is designed to extend skills designed for non-psychiatric populations as well as include specific considerations for sleep disturbance in bipolar disorder. We found that both the M1 monitor and the sleep intervention were feasible and well tolerated. Participants’ sleep duration improved after the brief sleep intervention, but the sleep was more unstable as measured by the M1. Self-reported sleepiness, sleep quality, and mood symptoms improved; however, only some measures reached statistical significance (i.e., duration of sleep, dysfunction due to sleepiness). These data suggest that the M1 device is a feasible means to obtain objective sleep quality and quantity data in individuals with bipolar disorder. A brief sleep intervention may be helpful in improving sleep in a bipolar population at risk for substantial sleep disturbance, but larger, longitudinal studies are warranted.

Routine EEGs remain a cornerstone test in caring for people with epilepsy. Although rare, a self-limited seizure (clinical or electrographic only) may be observed during such brief EEGs. The implications of observing a seizure in this situation, especially with respect to inferring the underlying seizure frequency, are unclear. The issue is complicated by the inaccuracy of patient-reported estimations of seizure frequency. The treating clinician is often left to wonder whether the single seizure indicates very frequent seizures, or if it is of lesser significance. We applied standard concepts of probabilistic inference to a simple model of seizure incidence to provide some guidance for clinicians facing this situation. Our analysis establishes upper and lower bounds on the seizure rate implied by observing a single seizure during routine EEG. Not surprisingly, with additional information regarding the expected seizure rate, these bounds can be further constrained. This framework should aid the clinician in applying a more principled approach toward decision making in the setting of a single seizure on a routine EEG.

This article is part of a Journal of Biological Rhythms series exploring analysis and statistical topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article, we address issues related to the collection of multiple data points from the same organism or system at different times, since such longitudinal data collection is fundamental to the assessment of biological rhythms. Rhythmic longitudinal data require additional specific statistical considerations, ranging from curve fitting to threshold definitions to accounting for correlation structure. We discuss statistical analyses of longitudinal data including issues of correlational structure and stationarity, markers of biological rhythms, demasking of biological rhythms, and determining phase, waveform, and amplitude of biological rhythms.

Context:Women are at increased risk for mood disturbance during the menopause transition. Hot flashes (HFs), sleep disruption, and fluctuating estradiol levels correlate with menopause-associated depression but co-occur, making cause and effect relationships difficult to disentangle.Objective:Using a GnRH agonist (GnRHa) experimental model, we investigated whether depressive symptoms are associated with HFs and/or are explained by concomitant sleep fragmentation in the absence of estradiol fluctuation.Design and Intervention:Depressive symptoms, objective polysomnographic sleep parameters, subjective sleep quality, serum estradiol, and HFs were assessed before and 4 weeks after open-label depot GnRHa (leuprolide 3.75-mg) administration.Setting:Academic medical center.Participants:Twenty-nine healthy nondepressed premenopausal volunteers (mean age, 27.3 years).Results:Serum estradiol was rapidly and uniformly suppressed. HFs developed in 69% of the subjects. On univariate analysis, worsening of mood was predicted by increases in time in light sleep (stage N1), number of transitions to wake, non-REM arousals, subjective sleep quality, and reductions in perceived sleep efficiency (all P < .045), as well as the number of nighttime (P = .006), but not daytime (P = .28), HFs reported. In adjusted models, the number of nighttime HFs reported, increases in non-REM arousals, time in stage N1, transitions to wake, and reduced sleep quality remained significant predictors of mood deterioration (P ≤ .05).Conclusions:Depressive symptoms emerged after estradiol withdrawal in association with objectively and subjectively measured sleep disturbance and the number of nighttime, but not daytime, HFs reported. Results suggest that sleep disruption and perceived nighttime HFs both contribute to vulnerability to menopause-associated depressive symptoms in hypoestrogenic women.

Study Objective:Obstructive sleep apnea (OSA) is a treatable contributor to morbidity and mortality. However, most patients with OSA remain undiagnosed. We used a new machine learning method known ...

Determining the presence and severity of obstructive sleep apnea (OSA) is based on apnea and hypopnea event rates per hour of sleep. Making this determination presents a diagnostic challenge, given that summary metrics do not consider certain factors that influence severity, such as body position and the composition of sleep stages.We retrospectively analyzed 300 consecutive diagnostic PSGs performed at our center to determine the impact of body position and sleep stage on sleep apnea severity.The median percent of REM sleep was 16% (reduced compared to a normal value of ~25%). The median percent supine sleep was 65%. Fewer than half of PSGs contained10 min in each of the 4 possible combinations of REM/NREM and supine/non-supine. Half of patients had2-fold worsening of the apnea-hypopnea index (AHI) in REM sleep, and 60% had2-fold worsening of AHI while supine. Adjusting for body position had greater impact on the AHI than adjusting for reduced REM%. Misclassification--specifically underestimation of OSA severity--is attributed more commonly to body position (20% to 40%) than to sleep stage (~10%).Supine-dominance and REM-dominance commonly contribute to AHI underestimation in single-night PSGs. Misclassification of OSA severity can be mitigated in a patient-specific manner by appropriate consideration of these variables. The results have implications for the interpretation of single-night measurements in clinical practice, especially with trends toward home testing devices that may not measure body position or sleep stage.

Diagnostic test interpretation remains a challenge in clinical practice. Most physicians receive training in the use of Bayes’ rule, which specifies how the sensitivity and specificity of a test for a given disease combine with the pre-test probability to quantify the change in disease probability incurred by a new test result. However, multiple studies demonstrate physicians’ deficiencies in probabilistic reasoning, especially with unexpected test results. Information theory, a branch of probability theory dealing explicitly with the quantification of uncertainty, has been proposed as an alternative framework for diagnostic test interpretation, but is even less familiar to physicians. We have previously addressed one key challenge in the practical application of Bayes theorem: the handling of uncertainty in the critical first step of estimating the pre-test probability of disease. This essay aims to present the essential concepts of information theory to physicians in an accessible manner, and to extend previous work regarding uncertainty in pre-test probability estimation by placing this type of uncertainty within a principled information theoretic framework. We address several obstacles hindering physicians’ application of information theoretic concepts to diagnostic test interpretation. These include issues of terminology (mathematical meanings of certain information theoretic terms differ from clinical or common parlance) as well as the underlying mathematical assumptions. Finally, we illustrate how, in information theoretic terms, one can understand the effect on diagnostic uncertainty of considering ranges instead of simple point estimates of pre-test probability.

The basic treatment goals of pharmacological therapies in sleep medicine are to improve waking function by either improving sleep or by increasing energy during wakefulness. Stimulants to improve waking function include amphetamine derivatives, modafinil, and caffeine. Sleep aids encompass several classes, from benzodiazepine hypnotics to over-the-counter antihistamines. Other medications used in sleep medicine include those initially used in other disorders, such as epilepsy, Parkinson’s disease, and psychiatric disorders. As these medications are prescribed or encountered by providers in diverse fields of medicine, it is important to recognize the distribution of adverse effects, drug interaction profiles, metabolism, and cytochrome substrate activity. In this paper, we review the pharmacological armamentarium in the field of sleep medicine to provide a framework for risk-benefit considerations in clinical practice.

Using the structural-environmental conceptual framework, this study employed mixed methods to address the question of whether sex with female sex workers contributes to HIV risk among male immigrant Latino day laborers in suburban Maryland. Because contextual factors can greatly affect HIV risk for both sex workers and their clients, this study investigated the organizational structure of sex work, factors that predicted men's hiring of sex workers, sexual behaviors performed with sex workers, and the use of condoms. Qualitative research was conducted to inform the development of a quantitative survey, but also provided crucial descriptions about the motivations, locations, arrangements, and sexual activities related to sex work. Key informant interviews (N = 10), in-depth interviews with day laborers (N = 10) and Latina female sex workers (N = 4), and two focus groups with day laborers (N = 11) were conducted, and a quantitative survey administered via Audio-enhanced Computer-assisted Self-interviewing (N = 174). Condom use was nearly universal in encounters with female sex workers, thus indicating that the sex workers were not an important source of HIV transmission in this context. Logistic regression was performed to test a model predicting sex with sex workers. Latino day laborers who reported more immigrant stress and who did not have a partner in the U.S. were more likely to have had sex with a sex worker, as were men who reported binge drinking. Structural and social conditions influenced the hiring of sex workers. Further research is warranted to better understand the interrelationships among these circumstances and to inform the development of programs to address them.

Time estimation is a complex cognitive task that is especially challenging when the time period includes sleep. To determine the accuracy of sleep duration perception, we investigated 44 healthy subjects participating in multi-day inpatient sleep protocols during which they had extended nighttime and short daytime sleep opportunities but no time cues or knowledge of time of day.The first sleep opportunity was at habitual sleep time and duration. The subsequent 3, 4, or 11 days had 12-h nighttime sleep opportunities and 4-h daytime nap opportunities, potentially creating an experimentally induced "insomnia" with substantial time awake during scheduled sleep.Subjective sleep duration estimates were accurate for the first (habitual) sleep opportunity. The subjective reports following nighttime 12-h sleep opportunities significantly underestimated objective sleep duration, while those following daytime 4-h sleep opportunities significantly overestimated objective sleep duration. Misperception errors were not explained by poor sleep efficiency, which was lower during 4-h (~39%) than 12-h opportunities (~71%). Subjective sleep estimates after 4-h opportunities correlated with the percentage of REM and N3 sleep. Subjective sleep estimates following 12-h opportunities were, unexpectedly, negatively correlated with NREM stage 2 sleep.The estimation of sleep duration in the absence of time cues may depend on length of sleep opportunity and/or time of day. The results have implications for understanding sleep state misperception, which is an important consideration in patients with insomnia.

Improving our understanding of sleep physiology and pathophysiology is an important goal for both medical and general wellness reasons. Although the gold standard for assessing sleep remains the laboratory polysomnogram, there is an increasing interest in portable monitoring devices that provide the opportunity for assessing sleep in real-world environments such as the home. Portable devices allow repeated measurements, evaluation of temporal patterns, and self-experimentation. We review recent developments in devices designed to monitor sleep-wake activity, as well as monitors designed for other purposes that could in principle be applied in the field of sleep (such as cardiac or respiratory sensing). As the body of supporting validation data grows, these devices hold promise for a variety of health and wellness goals. From a clinical and research standpoint, the capacity to obtain longitudinal sleep-wake data may improve disease phenotyping, individualized treatment decisions, and individualized health optimization. From a wellness standpoint, commercially available devices may allow individuals to track their own sleep with the goal of finding patterns and correlations with modifiable behaviors such as exercise, diet, and sleep aids.

To address the question: does non-convulsive status epilepticus warrant the same aggressive treatment as convulsive status epilepticus?We used a decision model to evaluate the risks and benefits of treating non-convulsive status epilepticus with intravenous anesthetics and ICU-level aggressive care. We investigated how the decision to use aggressive versus non-aggressive management for non-convulsive status epilepticus impacts expected patient outcome for four etiologies: absence epilepsy, discontinued antiepileptic drugs, intraparenchymal hemorrhage, and hypoxic ischemic encephalopathy. Each etiology was defined by distinct values for five key parameters: baseline mortality rate of the inciting etiology; efficacy of non-aggressive treatment in gaining control of seizures; the relative contribution of seizures to overall mortality; the degree of excess disability expected in the case of delayed seizure control; and the mortality risk of aggressive treatment.Non-aggressive treatment was favored for etiologies with low morbidity and mortality such as absence epilepsy and discontinued antiepileptic drugs. The risk of aggressive treatment was only warranted in etiologies where there was significant risk of seizure-induced neurologic damage. In the case of post-anoxic status epilepticus, expected outcomes were poor regardless of the treatment chosen. The favored strategy in each case was determined by strong interactions of all five model parameters.Determination of the optimal management approach to non-convulsive status epilepticus is complex and is ultimately determined by the inciting etiology.

Mammalian sleep is a complex phenomenon governed by the interplay of neural circuits and signaling systems. The impact of genetic manipulations on sleep-wake dynamics provides important insights into this complex behavior. Here we review the sleep-related phenotypes of over 50 transgenic animal models spanning a variety of signaling systems. This heterogeneous literature includes outcomes spanning motor activity patterns, sleep-wake stage architecture, responses to sleep deprivation, circadian rhythmicity, and other perturbations such as food restriction, temperature challenge, and infection exposure. Insights from these animal experiments hold potential to converge with the well-known sleep-wake neurocircuitry as well as the increasingly available human genetic information, especially in patient populations exhibiting sleep-wake pathology.

Male circumcision has received increased attention for its potential to reduce sexual transmission of HIV. Research on the acceptability of circumcision as a means of HIV prevention among men who have sex with men is limited. Men who have sex with men in Bogotá, Colombia, either participated in a focus group in which they shared information regarding their perceptions of circumcision or completed a survey that assessed circumcision experiences, attitudes, beliefs and willingness. Few participants reported they were circumcised, yet most participants reported knowing something about the procedure. Overall, attitudes towards circumcision were mixed: although circumcision was viewed as safe, it was also viewed as unnatural and cruel to babies. Beliefs that circumcision could improve sexual functioning and protect against STIs and HIV were not widely endorsed by survey participants, although focus-group participants discussed the potential impacts of circumcision on the availability of sexual partners and sexual performance. Some focus-group participants and many survey participants reported a hypothetical willingness to get circumcised if strong evidence of its effectiveness could be provided, barriers removed and recovery time minimised.

Telemedicine is an increasingly recognized option for cost-effective management of chronic conditions. We surveyed Sleep Clinic patients about their experiences and preferences regarding different forms of telemedicine. Adult Sleep Clinic patients seen between 2009 and 2011 received a brief survey either by postal mail (n=156) or, for those with an available email address, electronically (n=282). The overall response rate was 28.1% (n=123 responses), with email response rates being higher than postal mail responses. The most commonly reported barriers to in-person physician visits were parking cost (44%), time away from work/school (34%), and cost of gas (26%). Whereas 89% of respondents indicated using telephone and 55% of respondents indicated using email to communicate with providers, none reported experience with video telemedicine. Despite this lack of experience, over 60% reported feeling comfortable or willing to try it. Of those who were uncomfortable about video telemedicine, the two main reasons were that in-person visits feel more natural (48%) and that the doctor might need to perform an examination (24%). More than half of respondents reported willingness to pay a copay for a video visit. Video telemedicine represents a feasible option for chronic sleep disorders management.

This pilot study evaluated the impact of Bikram Yoga on subjective and objective sleep parameters. We compared subjective (diary) and objective (headband sleep monitor) sleep measures on yoga versus nonyoga days during a 14-day period. Subjects () were not constrained regarding yoga-practice days, other exercise, caffeine, alcohol, or naps. These activities did not segregate by choice of yoga days. Standard sleep metrics were unaffected by yoga, including sleep latency, total sleep time, and percentage of time spent in rapid eye movement (REM), light non-REM, deep non-REM, or wake after sleep onset (WASO). Consistent with prior work, transition probability analysis was a more sensitive index of sleep architecture changes than standard metrics. Specifically, Bikram Yoga was associated with significantly faster return to sleep after nocturnal awakenings. We conclude that objective home sleep monitoring is feasible in a low-constraint, real-world study design. Further studies on patients with insomnia will determine whether the results generalize or not.

Functional connectivity networks have become a central focus in neuroscience because they reveal key higher-dimensional features of normal and abnormal nervous system physiology. Functional networks reflect activity-based coupling between brain regions that may be constrained by relatively static anatomical connections, yet these networks appear to support tremendously dynamic behaviors. Within this growing field, the stability and temporal characteristics of functional connectivity brain networks have not been well characterized. We evaluated the temporal stability of spontaneous functional connectivity networks derived from multi-day scalp encephalogram (EEG) recordings in five healthy human subjects. Topological stability and graph characteristics of networks derived from averaged data epochs ranging from 1 s to multiple hours across different states of consciousness were compared. We show that, although functional networks are highly variable on the order of seconds, stable network templates emerge after as little as ∼100 s of recording and persist across different states and frequency bands (albeit with slightly different characteristics in different states and frequencies). Within these network templates, the most common edges are markedly consistent, constituting a network “core.” Although average network topologies persist across time, measures of global network connectivity, density and clustering coefficient, are state and frequency specific, with sparsest but most highly clustered networks seen during sleep and in the gamma frequency band. These findings support the notion that a core functional organization underlies spontaneous cortical processing and may provide a reference template on which unstable, transient, and rapidly adaptive long-range assemblies are overlaid in a frequency-dependent manner.

SUMMARY Purpose: How long after starting a new medication must a patient go without seizures before they can be regarded as seizure-free? A recent International League Against Epilepsy (ILAE) task force proposed using a ‘‘Rule of Three’’ as an operational definition of seizure freedom, according to which a patient should be considered seizure-free following an intervention after a period without seizures has elapsed equal to three times the longest preintervention interseizure interval over the previous year. This rule was motivated in large part by statistical considerations advanced in a classic 1983 paper by Hanley and Lippman-Hand. However, strict adherence to the statistical logic of this rule generally requires waiting much longer than recommended by the ILAE task force. Therefore, we set out to determine whether an alternative approach to the Rule of Three might be possible, and under what conditions the rule may be expected to hold or would need to be extended. Methods: Probabilistic modeling and application of Bayes’ rule. Key Findings: We find that an alternative approach to the problem of inferring seizure freedom supports using the Rule of Three in the way proposed by the ILAE in many cases, particularly in evaluating responses to a first trial of antiseizure medication, and to favorably-selected epilepsy surgical candidates. In cases where the a priori odds of success are less favorable, our analysis requires longer seizure-free observation periods before declaring seizure freedom, up to six times the average preintervention interseizure interval. Thekey to our approach is totake into account not only the time elapsed without seizures but also empirical data regarding the a priori probability of achieving seizure freedom conferred by a particular intervention. Significance: In many cases it may be reasonable to consider a patient seizure-free after they have gone without seizures for a period equal to three times the preintervention interseizure interval, as proposed on pragmatic grounds in a recent ILAE position paper, although in other commonly encountered cases a waiting time up to six times this interval is required. In this work we have provided a coherent theoretical basis for modified criterion for seizure freedom, which we call the ‘‘Rule of Three

Over the past two decades, the increased ability to analyze network relationships among neural structures has provided novel insights into brain function. Most network approaches, however, focus on static representations of the brain's physical or statistical connectivity. Few studies have examined how brain functional networks evolve spontaneously over long epochs of continuous time. To address this, we examine functional connectivity networks deduced from continuous long-term electrocorticogram recordings. For a population of six human patients, we identify a persistent pattern of connections that form a frequency-band-dependent network template, and a set of core connections that appear frequently and together. These structures are robust, emerging from brief time intervals (∼100 s) regardless of cognitive state. These results suggest that a metastable, frequency-band-dependent scaffold of brain connectivity exists from which transient activity emerges and recedes.

Sleep fragmentation of any cause is disruptive to the rejuvenating value of sleep. However, methods to quantify sleep architecture remain limited. We have previously shown that human sleep–wake stage distributions exhibit multi-exponential dynamics, which are fragmented by obstructive sleep apnea (OSA), suggesting that Markov models may be a useful method to quantify architecture in health and disease. Sleep stage data were obtained from two subsets of the Sleep Heart Health Study database: control subjects with no medications, no OSA, no medical co-morbidities and no sleepiness (n = 374); and subjects with severe OSA (n = 338). Sleep architecture was simplified into three stages: wake after sleep onset (WASO); non-rapid eye movement (NREM) sleep; and rapid eye movement (REM) sleep. The connectivity and transition rates among eight ‘generator’ states of a first-order continuous-time Markov model were inferred from the observed (‘phenotypic’) distributions: three exponentials each of NREM sleep and WASO; and two exponentials of REM sleep. Ultradian REM cycling was accomplished by imposing time-variation to REM state entry rates. Fragmentation in subjects with severe OSA involved faster transition probabilities as well as additional state transition paths within the model. The Markov models exhibit two important features of human sleep architecture: multi-exponential stage dynamics (accounting for observed bout distributions); and probabilistic transitions (an inherent source of variability). In addition, the model quantifies the fragmentation associated with severe OSA. Markov sleep models may prove important for quantifying sleep disruption to provide objective metrics to correlate with endpoints ranging from sleepiness to cardiovascular morbidity.

Identifying predictors of subjective sleepiness and severity of sleep apnea are important yet challenging goals in sleep medicine. Classification algorithms may provide insights, especially when large data sets are available. We analyzed polysomnography and clinical features available from the Sleep Heart Health Study. The Epworth Sleepiness Scale and the apnea-hypopnea index were the targets of three classifiers: k-nearest neighbor, naive Bayes and support vector machine algorithms. Classification was based on up to 26 features including demographics, polysomnogram, and electrocardiogram (spectrogram). Naive Bayes was best for predicting abnormal Epworth class (0-10 versus 11-24), although prediction was weak: polysomnogram features had 16.7% sensitivity and 88.8% specificity; spectrogram features had 5.3% sensitivity and 96.5% specificity. The support vector machine performed similarly to naive Bayes for predicting sleep apnea class (0-5 versus >5): 59.0% sensitivity and 74.5% specificity using clinical features and 43.4% sensitivity and 83.5% specificity using spectrographic features compared with the naive Bayes classifier, which had 57.5% sensitivity and 73.7% specificity (clinical), and 39.0% sensitivity and 82.7% specificity (spectrogram). Mutual information analysis confirmed the minimal dependency of the Epworth score on any feature, while the apnea-hypopnea index showed modest dependency on body mass index, arousal index, oxygenation and spectrogram features. Apnea classification was modestly accurate, using either clinical or spectrogram features, and showed lower sensitivity and higher specificity than common sleep apnea screening tools. Thus, clinical prediction of sleep apnea may be feasible with easily obtained demographic and electrocardiographic analysis, but the utility of the Epworth is questioned by its minimal relation to clinical, electrocardiographic, or polysomnographic features.

INTRODUCTION Cigarette smoking has become an important influence of morbidity and mortality for HIV-positive individuals in the era of highly active antiretroviral therapy. Although smoking is common among military personnel and veterans, the lasting impact of military service on smoking at a later stage of life has not been examined. The current study investigated present and past influences on current smoking among HIV-positive male veterans. METHODS Participants were 200 HIV-positive men served by the Veterans Affairs Medical Center. A survey was administered via audio-enhanced computer-assisted self-interview, and additional information was extracted from the computerized patient record system. RESULTS Logistic regression was performed to test hypotheses concerning the participants' current situations as well as characteristics of their past military service. Having smokers in one's environment, being more depressed, and having used alcohol or drugs were associated with having smoked in the previous 30 days, whereas stronger endorsement of attitudes stating adverse effects of smoking was linked to lower likelihood of smoking. Neither having been in a military conflict nor the length of the military service was significantly related to current smoking. CONCLUSIONS Remote experiences in the military did not have a sustained effect on smoking behavior years later. Implications of this study for the development of smoking cessation programs targeting HIV-positive veterans include the importance of altering attitudes about tobacco, treating underlying depression, addressing social influence, decreasing substance use, and increasing awareness of the heightened vulnerability to a variety of negative consequences of smoking among infected individuals.

Development of the human brain follows a complex trajectory of age-specific anatomical and physiological changes. The application of network analysis provides an illuminating perspective on the dynamic interregional and global properties of this intricate and complex system. Here, we provide a critical synopsis of methods of network analysis with a focus on developing brain networks. After discussing basic concepts and approaches to network analysis, we explore the primary events of anatomical cortical development from gestation through adolescence. Upon this framework, we describe early work revealing the evolution of age-specific functional brain networks in normal neurodevelopment. Finally, we review how these relationships can be altered in disease and perhaps even rectified with treatment. While this method of description and inquiry remains in early form, there is already substantial evidence that the application of network models and analysis to understanding normal and abnormal human neural development holds tremendous promise for future discovery.

Being able to confidently ascertain the amount of sleep is critical to the clinical management of epilepsy. Sleep misperception is the phenomenon in which an individual underestimates the amount of time spent asleep. Little is known about sleep misperception in patients with epilepsy. We conducted retrospective chart reviews on individuals who self-identified as having epilepsy in a questionnaire database of patients undergoing polysomnography (PSG) at the Massachusetts General Hospital Sleep Laboratory. Our metric for sleep misperception was the difference between subjective and objective sleep latency (S-O SL) and subjective and objective total sleep time (S-O TST) with subjective values based on questionnaire and objective values based on PSG. We confirmed 64 patients with epilepsy. We then selected age- and sex-matched diagnostic PSG data for comparison from 50 patients with insomnia symptoms but no obstructive sleep apnea (OSA) and another 50 patients with OSA but no insomnia symptoms. In our cohort with epilepsy, the median SL overestimation was 20 min (p0.05), and the median TST underestimation was 45 min (p0.05). Sleep misperception was similar regardless of potential confounding factors such as categorical epilepsy refractoriness, cognitive impairment, or psychiatric comorbidity. Our findings suggest that sleep misperception occurs similarly in patients with epilepsy as in patients without epilepsy with insomnia. Our findings further support the potential clinical utility of objective PSG testing in patients with epilepsy, as this may not only identify occult OSA but also disclose sleep misperception.

This study investigated relationships between Latino gay-identified men in metropolitan New York City and their non-gay-identified male partners. Phase 1 consisted of in-depth interviews (N = 33), and Phase 2 consisted of quantitative surveys (N = 120) with Brazilian, Colombian, and Dominican men who have sex with men (MSM). A majority of participants reported having had sex with heterosexually identified men, and in many cases, the relationship was sustained over time. We found mixed results concerning an attitude sometimes attributed to Latinos that sexual orientation is defined by sexual role, with receptive MSM seen as gay and insertive MSM seen as straight. Although there were no significant associations between partner sexual orientation and unprotected anal intercourse, gay men were less likely to take the insertive role in oral or anal sex with straight-identified male partners than with gay partners.

This study examined factors associated with communication about condom use and unprotected anal intercourse (UAI) in a U.S. sample of immigrant Latino MSM (N = 356), with a focus on culturally based beliefs. Logistic regression analysis revealed that communication about condom use at participants' most recent encounter was associated with a lower likelihood of UAI during that encounter. UAI was more likely when the partner was a main partner and there was seroconcordance. A separate logistic regression indicated that communication about condom use was less likely when the most recent encounter involved a main partner, greater sexual desire, and intoxication due to substance use. Although cultural beliefs were not predictive of communication about condom use or UAI at the most recent encounter, they were related to the occurrence of UAI in the previous three months. There is a need for more research on the interplay of culture, safer sex communication, and sexual risk.

Introduction The human electroencephalogram (EEG) of sleep undergoes profound changes with age, such as decreased sleep spindle amplitude and density in non-rapid eye movement stage 2 (NREM2). However, it is unknown how accurately a patient’s age can be predicted from EEG activity during sleep. A quantitative characterization of age-related EEG provides important insights into healthy aging. Moreover, the ability to detect deviations of EEG patterns from those typical for age could provide insights into age-related neurological disorders, and might provide a way to gauge the effects of interventions designed to preserve or improve brain health. Here we develop a model to predict a patient’s age based on large-scale and heterogeneous sleep EEG datasets. The prediction is called “brain age” (BA). Methods Datasets: (1) MGH sleep dataset: 3100 patients aged 18–80 years. (2) sleep-heart health study (SHHS): 3680 paired recordings aged 18–80 years, where each pair is recorded approximately 5 years apart from the same subject. This dataset is used to verify the longitudinal reliability of the brain age. EEG features: 102 features are extracted from 30s-epochs, and then averaged separately for the 5 sleep stages, yielding 510 features to summarize each patient’s overnight sleep. We also analyze medications and clinical variables to identify factors that help account for brain age being older or younger than chronological age. Results For 1000 testing patients from MGH dataset, the Pearson’s correlation between EEG-based brain age and chronological age is 0.86 (95% CI 0.84–0.87). The mean absolute prediction error (MAE) is 6.6 years. For SHHS dataset, training the model on a subset of 2000 records and testing on the other 1680 records achieves correlation at 0.71 (95% CI 0.69–0.73) and MAE 5.9 yrs. The average difference of BA between each pair is 4.8yrs. Training the entire MGH dataset and testing on SHHS achieves correlation at 0.61 (95% CI 0.59–0.63) and MAE 8.6 yrs. The average difference of BA between each pair is 3.7 yrs. In the MGH dataset, older brain age (predicted age greater than chronological age) is associated diabetes (Kruskal-Wallis test p-value 0.01) and weakly associated with wake time after sleep onset (Pearson’s correlation p-value 0.07). Conclusion Our results indicate that, at the population level, chronological age can be accurately predicted from overnight sleep EEG. Moreover, brain age accurately tracks chronological age. Further research is needed to characterize how EEG-based brain age relates to cognitive function and to what degree and by what means brain age is modifiable.

The assumption is often made that aggressive care in the form of early decompressive hemicraniectomy is appropriate for young patients who suffer a massive stroke. However, neither their attitude toward aggressive treatment, nor their perception of acceptable quality of life after a stroke, has been adequately studied.We conducted a cross-sectional questionnaire-based survey that consisted of demographic information and attitude toward neurological disability based on the highest acceptable modified Rankin Scale (mRS) that they would be "willing to live with." Young adults in the Los Angeles County were surveyed and grouped by whether or not they would want early decompressive hemicraniectomy after a massive stroke. Logistic regression analysis was used to determine the factors associated with willingness to accept decompressive hemicraniectomy.Sixty-eight community-dwelling young adults (mean age: 24 +/- 6 years) were surveyed. The highest acceptable mRS (0-5) participants felt "willing to live with" were: 10.3% (0), 29.4% (1), 27.9% (2), 20.6% (3), 8.8% (4), 2.9% (5). Despite being presented with a hypothetical high likelihood of long-term disability, 46 of 68 (68%) reported they would undergo hemicraniectomy. Neither the demographic factors nor the highest acceptable mRS was associated with the willingness to seek decompressive hemicraniectomy.Our study supports the commonly held assumption that the majority of young adults would favor early decompressive hemicraniectomy after a massive ischemic stroke. We also show that a substantial minority in this age group is reluctant to accept this aggressive measure, emphasizing the importance of discussing the individual's previously stated wishes, even in the young population.

The anxiolytic, hypnotic, and anti-convulsant properties of benzodiazepines (BDZs) require modulation of distinct GABA(A) receptor alpha-subtypes. BDZ modulation of GABA(A) receptors is often described in terms of increased opening frequency, and contrasted with the increased open durations occurring with barbiturate modulation. Several studies spanning single channel, rapid kinetic, and whole cell techniques have suggested that BDZs effect this observed change in frequency through increased affinity for GABA. BDZ-sensitive αβγ isoforms exist at extrasynaptic as well as synaptic locations, where they encounter markedly different concentration and time-course of GABA exposure. Interestingly, this affinity-based mechanism (specifically, decreasing the GABA unbinding rate) is only predicted to increase opening frequency under conditions that allow the unbinding and rebinding cycles typical of prolonged exposure to low GABA concentrations, which are more likely to occur at extrasynaptic GABA(A) receptors. In contrast, when rebinding is less likely, such as may occur in certain synaptic conditions, the number, but not the frequency, of channel openings increases in response to BDZ modulation. In conclusion, not only can multiple kinetic mechanisms alter channel opening frequency, but a single mechanism - increased affinity - impacts opening frequency differently under different contexts of GABA(A) receptor activation.

A fundamental challenge associated with screening tests is recognition of the impact of disease prevalence upon the predictive value of the result. For example, in the common circumstance of screening for low prevalence dis- eases, even good tests may have unacceptably high false positive rates. The converse situation, screening in high preva- lence populations, is less common but occurs with obstructive sleep apnea (OSA): even ostensibly good screening tests may have unacceptably high false negative rates. The challenge of recognizing false negative OSA screening results has important implications as screens are increasingly implemented in high risk populations. This raises two clinically impor- tant questions: 1) How sensitive and specific should a screening test be to minimize false negative results across a spec- trum of baseline prevalence; and 2) Given a screening test with known sensitivity and specificity, in what range of disease prevalence may the test be reasonably applied? Simple graphics are presented that incorporate acceptable risk thresholds and illustrate combinations of prevalence, sensitivity, and specificity in which disease probability remains high despite a negative test result. Adopting a Bayesian approach, together with acceptable risk thresholds, may help to avoid potential pitfalls of false negative screening results. Although the baseline prevalence in the United States of obstructive sleep apnea (OSA) is estimated in the range of 3- 28% (1), in certain populations the prevalence is much higher. For example, higher prevalence has been reported for patients with refractory epilepsy (33%) (2), recent stroke (58%) (3), refractory hypertension (63%) (4), heart failure (35%) (5), polycystic ovary syndrome (65%) (6), anterior ischemic optic neuropathy (89%) (7), children with Down's Syndrome (63%) (8), and those undergoing bariatric surgery (80%) (9-10). Treatment of OSA may be associated with improved outcomes in some settings (11). One particular area of interest involves OSA in the peri-operative setting, which may be associated with complications and/or longer hospital stay (12-13). Given the limited resources for labora- tory polysomnogram (PSG) as a screening tool, screening questionnaires may assist in OSA risk stratification. A screening tool with the acronym "STOP-Bang" was recently developed to provide dichotomous risk stratification (low versus high OSA risk) in general surgical populations (12-13). In this population, adverse outcomes involving res- piratory compromise were increased in the peri-operative period in those with OSA, defined as an apnea-hypopnea index (AHI) >5 by standard PSG. The STOP-Bang screen involves four yes/no patient questions (snoring, daytime tiredness, observed nocturnal apnea, high blood pressure), combined with four yes/no clinical features (BMI >35, age >50, neck circumference >40 cm, male gender). This simple tool was validated in a surgical population (177 patients, including general, gynecologic, orthopedic, urologic, plastic, ophthalmologic, and neurosurgery cases) (13), with a posi- tive result defined as >3 "yes" responses. Within the study limitations (including high refusal and no-show rates for PSG), the sensitivity for OSA varied with OSA severity