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The file contains three supplementary figures with legends. Figure S1: Characterization of cell lines expressing CITK-specific shRNAs. Figure S2: The expression of CITK correlates with MB patients'' prognosis and CITK is highly expressed in mouse SmoA1 MB. Figure S3: Engineering and characterization of conditional CITK inactivation in mice.

Medulloblastoma is the most common malignant brain tumor in children. Current treatment for medulloblastoma consists of surgery followed by irradiation of the whole neuraxis and high-dose multiagent chemotherapy, a partially effective strategy associated with highly invalidating side effects. Therefore, identification and validation of novel target molecules capable of contrasting medulloblastoma growth without disturbing brain development is needed. Citron kinase protein (CITK), encoded by primary microcephaly gene MCPH17, is required for normal proliferation and survival of neural progenitors. Constitutive loss of CITK leads to cytokinesis failure, chromosome instability, and apoptosis in the developing brain, but has limited effects on other tissues. On this basis, we hypothesized that CITK could be an effective target for medulloblastoma treatment. In medulloblastoma cell lines DAOY and ONS-76, CITK knockdown increased both cytokinesis failure and DNA damage, impairing proliferation and inducing cell senescence and apoptosis via TP53 or TP73. Similar effects were obtained in the NeuroD-SmoA1 transgenic mouse model, in which CITK deletion increased apoptotic cells and senescence markers such as P21CIP1, P27KIP1, and P16INK4A. Most importantly, CITK deletion decreased tumor growth and increased overall survival in these mice, with no apparent side effects. These results suggest that CITK can be a useful molecular target for medulloblastoma treatment.Significance: In vitro and in vivo proof of concept identifies citron kinase protein as a suitable target for medulloblastoma treatment.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/16/4599/F1.large.jpg. Cancer Res; 78(16); 4599–612. ©2018 AACR.

Acute Giardia infections often cause diarrhea and stomach upset. Chronic infections can lead to malnutrition, micronutrient deficiencies, malabsorption and weight loss. This study assessed the prevalence of G. lambia infection and assessed associated risk factors among immunocompomised patients undergoing chemotherapeutic treatment in southern Brazil. A total of 110 immunocompromised patients in Pelotas, RS, Brazil, consented to participate in this study and were recruited. Socioeconomic and epidemiological profile of patients was collected by questionnaire. The prevalence for Giardia were determined through microscopy by the centrifugation-flotation technique using stool samples of every patient. In addition, the genetic characterization of the parasite was carried out by amplifying and sequencing the glutamate dehydrogenase (gdh) gene. By microscopy, the prevalence of giardiasis was 17.3% (19/110). Furthermore, the DNA sequences revealed that 7 (36.8%) out of 19 isolates belonged to assemblage B, while 6 of them (31.6%) belonged to assemblage C, 5 (26.3%) to assemblage A and 1 (5.3%) to assemblage D. Risk factors (p ≤ 0.05) for giardiasis were schooling level (OR=8.0 (1.02 – 62.91) sharing a house with more than three people (OR=14.1 (3.77 – 52.51), water sources (OR=38.9 (10.4 – 145.7), sewage treatment (OR=14.2 (3.1 – 65.5), waste destination (OR=7.44 (2.0 – 27.3), owning pets (OR=4.6 (1.0 – 21.2) and cultivating a vegetable garden (OR=4.2 (1.3 – 13.6). The prevalence of G. lamblia in immunocompromised patients was considered elevate with the identification of four assemblage of the parasite (A, B, C and D). Resumo As infecções agudas por Giardia geralmente causam diarreia e dores de estômago. As infecções crônicas podem levar à desnutrição, deficiências de micronutrientes, má absorção e perda de peso. Este estudo avaliou a prevalência da infecção por G. lambia e os fatores de risco associados em pacientes imunocomprometidos em tratamento quimioterápico no sul do Brasil. Um total de 110 pacientes imunocomprometidos de Pelotas, RS, Brasil, consentiram em participar deste estudo e foram recrutados. O perfil socioeconômico e epidemiológico dos pacientes foi coletado por meio de questionário. A prevalência de Giardia foi determinada através de microscopia pela técnica de centrifugação-flutuação utilizando amostras de fezes de cada paciente. Além disso, a caracterização genética do parasita foi realizada pela amplificação e sequenciamento do gene da glutamato desidrogenase (gdh). À microscopia, a prevalência de giardíase foi de 17,3% (19/110). Além disso, as sequências de DNA revelaram que 7 (36,8%) dos 19 isolados pertenciam ao agrupamento B, enquanto 6 deles (31,6%) pertenciam ao agrupamento C, 5 (26,3%) ao agrupamento A e 1 (5,3%) ao agrupamento D. Os fatores de risco (p ≤ 0,05) para giardíase foram, escolaridade (OR=8,0 (1,02 – 62,91), dividir casa com mais de três pessoas (OR=14,1 (3,77 – 52,51), fontes de água (OR=38,9 (10,4 – 145,7), tratamento de esgoto (OR=14,2 (3,1 – 65,5), destinação do lixo (OR=7,44 (2,0 – 27,3), possuir animais de estimação (OR=4,6 (1,0 – 21,2) e cultivar horta (OR=4,2 (1,3 – 13.6). A prevalência de G. lamblia em pacientes imunocomprometidos foi considerada elevada com a identificação de quatro conjuntos do parasito (A, B, C e D).

Summary The present study aims to compare the effectiveness of surgical and medical therapy in reducing the risk of cancer in Barrett’s esophagus in a long-term evaluation. A prospective cohort was designed that compared Barrett’s esophagus patients submitted to medical treatment with omeprazole or laparoscopic Nissen fundoplication. The groups were compared using propensity score matching paired by Barrett’s esophagus length. A total of 398 patients met inclusion criteria. There were 207 patients in the omeprazole group (Group A) and 191 in the total fundoplication group (Group B). After applying the propensity score matching paired by Barrett’s esophagus length, the groups were 180 (Group A) and 190 (Group B). Median follow-up was 80 months. Group B was significantly superior for controlling GERD symptoms. Group B was more efficient than Group A in promoting Barrett’s esophagus regression or blocking its progression. Group B was more efficient than Group A in preventing the development of dysplasia and cancer. Logistic regression was performed for the outcomes of adenocarcinoma and dysplasia. Age and body mass index were used as covariates in the logistic regression models. Even after regression analysis, Group B was still superior to Group A to prevent esophageal adenocarcinoma or dysplasia transformation (odds ratio [OR]: 0.51; 95% confidence interval [CI]: 0.27–0.97, for adenocarcinoma or any dysplasia; and OR: 0.26; 95% CI: 0.08–0.81, for adenocarcinoma or high-grade dysplasia). Surgical treatment is superior to medical management, allowing for better symptom control, less need for reflux medication use, higher regression rate of the columnar epithelium and intestinal metaplasia, and lower risk for progression to dysplasia and cancer.

Asthma self-management can improve symptom control, but adherence to established self-management behaviors is often poor. With adult asthma uncontrolled in over 60% of U.S. cases, there is a need for scalable, cost-effective tools to improve asthma outcomes. Here we describe a protocol for the Asthma Digital Study, a 24-month, decentralized, pragmatic, open-label, randomized controlled trial investigating the impact of a digital asthma self-management (DASM) program on asthma outcomes in adults. The program leverages consumer-grade devices with a smartphone app to provide "smart nudges," symptom logging, trigger tracking, and other features. Participants are recruited (target N = 900) from throughout the U.S., and randomized to a DASM or control arm (1:1). Co-primary outcomes at one year are a) asthma-associated costs for acute care and b) change from baseline in Asthma Control Test™ scores. Findings may inform decisions around adoption of digital tools for asthma self-management. Trial registration:clinicaltrials.gov identifier: NCT04609644. Registered: Oct 30, 2020.

Background: Intravenous drug users (IVDUs) represent a very small group of patients affected by chronic wounds (CWs). Objectives: To assess the risk factors for CWs in IVDUs, to improve their treatment. Methods: A retrospective review of 7 IVDUs with CWs was performed at the Dermatology of the University of Bologna. Results: A history of 10 years of the most frequent injection was heroin in the gaiter area. The most observed comorbidities were HIV, HCV and HBV. They were treated most with an alginate with silver dressing with an average follow-up of 2.8 years. Conclusions: We would like to highlight the importance of clinical history in this type of patients and that in our experience specialized skin wounds risk assessment and management could be useful, aside from traditional compression therapy.

Exposure therapy for social anxiety disorder (SAD) utilizes fear extinction, a memory process enhanced by sleep. We investigated whether naps following exposure sessions might improve symptoms and biomarkers in response to social stress in adults undergoing 5-week exposure-based group SAD therapy. Thirty-two participants aged 18–39 (18 females) with SAD were randomized. Before and after treatment, participants completed the Liebowitz Social Anxiety Scale (LSAS) and underwent a Trier Social Stress Test with psychophysiological monitoring (mpTSST) that included skin conductance (SCL), electromyographic (EMG) and electrocardiographic recording, and an auditory startle procedure while anticipating the social stressor. At sessions 3 and 4, exposure was followed by either a 120-min polysomnographically monitored sleep opportunity (Nap, N = 17) or wakefulness (Wake, N = 15). Primary hypotheses about SAD symptom change (LSAS) and EMG blink-startle response failed to differ with naps, despite significant symptom improvement (LSAS) with therapy. Some secondary biomarkers, however, provided preliminary support for enhanced extinction learning with naps, with trend-level Time (pre-, post-treatment) × Arm interactions and significant reduction from pre- to post treatment in the Nap arm alone for mpTSST SCL and salivary cortisol rise. Because of the small sample size and limited sleep duration, additional well-powered studies with more robust sleep interventions are indicated.

Elise Jortberg,1 Ikaro Silva,1 Viprali Bhatkar,1 Ryan S McGinnis,2 Ellora Sen-Gupta,1 Briana Morey,1 John A Wright Jr,1 Jesus Pindado,1 Matt T Bianchi3 1MC10, Inc., Lexington, MA 02421, USA; 2Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT 05405, USA; 3Neurology Department, Massachusetts General Hospital, Boston, MA 02114, USA Background: Although in-lab polysomnography (PSG) remains the gold standard for objective sleep monitoring, the use of at-home sensor systems has gained popularity in recent years. Two categories of monitoring, autonomic and limb movement physiology, are increasingly recognized as critical for sleep disorder phenotyping, yet at-home options remain limited outside of research protocols. The purpose of this study was to validate the BiostampRC® sensor system for respiration, electrocardiography (ECG), and leg electromyography (EMG) against gold standard PSG recordings.Methods: We report analysis of cardiac and respiratory data from 15 patients and anterior tibialis (AT) data from 19 patients undergoing clinical PSG for any indication who simultaneously wore BiostampRC® sensors on the chest and the bilateral AT muscles. BiostampRC® is a flexible, adhesive, wireless sensor capable of capturing accelerometry, ECG, and EMG. We compared BiostampRC® data and feature extractions with those obtained from PSG.Results: The heart rate extracted from BiostampRC® ECG showed strong agreement with the PSG (cohort root mean square error of 5 beats per minute). We found the thoracic BiostampRC® respiratory waveform, derived from its accelerometer, accurately calculated the respiratory rate (mean average error of 0.26 and root mean square error of 1.84 breaths per minute). The AT EMG signal supported periodic limb movement detection, with area under the curve of the receiver operating characteristic curve equaling 0.88. Upon completion, 88% of subjects indicated willingness to wear BiostampRC® at home on an exit survey.Conclusion: The results demonstrate that BiostampRC® is a tolerable and accurate method for capturing respiration, ECG, and AT EMG time series signals during overnight sleep when compared with simultaneous PSG recordings. The signal quality sufficiently supports analytics of clinical relevance. Larger longitudinal in-home studies are required to support the role of BiostampRC® in clinical management of sleep disorders involving the autonomic nervous system and limb movements. Keywords: electrocardiography, electromyography, respiration, wearable

Objectives Sleep, which comprises of rapid eye movement (REM) and non-REM stages 1–3 (N1–N3), is a natural occurring state of decreased arousal that is crucial for normal cardiovascular, immune and cognitive function. The principal sedative drugs produce electroencephalogram beta oscillations, which have been associated with neurocognitive dysfunction. Pharmacological induction of altered arousal states that neurophysiologically approximate natural sleep, termed biomimetic sleep, may eliminate drug-induced neurocognitive dysfunction. Methods We performed a prospective, single-site, three-arm, randomized-controlled, crossover polysomnography pilot study (n = 10) comparing natural, intravenous dexmedetomidine- (1-μg/kg over 10 min [n = 7] or 0.5-μg/kg over 10 min [n = 3]), and zolpidem-induced sleep in healthy volunteers. Sleep quality and psychomotor performance were assessed with polysomnography and the psychomotor vigilance test, respectively. Sleep quality questionnaires were also administered. Results We found that dexmedetomidine promoted N3 sleep in a dose dependent manner, and did not impair performance on the psychomotor vigilance test. In contrast, zolpidem extended release was associated with decreased theta (∼5–8 Hz; N2 and N3) and increased beta oscillations (∼13–25 Hz; N2 and REM). Zolpidem extended release was also associated with increased lapses on the psychomotor vigilance test. No serious adverse events occurred. Conclusions Pharmacological induction of biomimetic N3 sleep with psychomotor sparing benefits is feasible. Significance These results suggest that α2a adrenergic agonists may be developed as a new class of sleep enhancing medications with neurocognitive sparing benefits., National Institutes of Health (Grant TR01 GM104948)

Study Objectives:Home sleep apnea testing (HSAT) is increasingly available for diagnosing obstructive sleep apnea (OSA). One key limitation of most HSAT involves the lack of sleep staging, such tha...

Matt T Bianchi,1,2 Kathryn Russo,1 Harriett Gabbidon,1 Tiaundra Smith,1 Balaji Goparaju,1 M Brandon Westover1 1Neurology Department, Massachusetts General Hospital, 2Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA Abstract: Clinical polysomnography (PSG) databases are a rich resource in the era of “big data” analytics. We explore the uses and potential pitfalls of clinical data mining of PSG using statistical principles and analysis of clinical data from our sleep center. We performed retrospective analysis of self-reported and objective PSG data from adults who underwent overnight PSG (diagnostic tests, n=1835). Self-reported symptoms overlapped markedly between the two most common categories, insomnia and sleep apnea, with the majority reporting symptoms of both disorders. Standard clinical metrics routinely reported on objective data were analyzed for basic properties (missing values, distributions), pairwise correlations, and descriptive phenotyping. Of 41 continuous variables, including clinical and PSG derived, none passed testing for normality. Objective findings of sleep apnea and periodic limb movements were common, with 51% having an apnea–hypopnea index (AHI) >5 per hour and 25% having a leg movement index >15 per hour. Different visualization methods are shown for common variables to explore population distributions. Phenotyping methods based on clinical databases are discussed for sleep architecture, sleep apnea, and insomnia. Inferential pitfalls are discussed using the current dataset and case examples from the literature. The increasing availability of clinical databases for large-scale analytics holds important promise in sleep medicine, especially as it becomes increasingly important to demonstrate the utility of clinical testing methods in management of sleep disorders. Awareness of the strengths, as well as caution regarding the limitations, will maximize the productive use of big data analytics in sleep medicine. Keywords: polysomnography, sleep disorders, subjective symptoms, correlation, plotting, statistics

Objective:To integrate long-term measures of disease-modifying drug efficacy and risk to guide selection of first-line treatment of multiple sclerosis.Methods:We created a Markov decision model to evaluate disability worsening and progressive multifocal leukoencephalopathy (PML) risk in patients receiving natalizumab (NTZ), fingolimod (FGL), or glatiramer acetate (GA) over 30 years. Leveraging publicly available data, we integrated treatment utility, disability worsening, and risk of PML into quality-adjusted life-years (QALYs). We performed sensitivity analyses varying PML risk, mortality and morbidity, and relative risk of disease worsening across clinically relevant ranges.Results:Over the entire reported range of NTZ-associated PML risk, NTZ as first-line therapy is predicted to provide a greater net benefit (15.06 QALYs) than FGL (13.99 QALYs) or GA (12.71 QALYs) treatment over 30 years, after accounting for loss of QALYs due to PML or death (resulting from all causes). NTZ treatment is associated with delayed worsening to an Expanded Disability Status Scale score ≥6.0 vs FGL or GA (22.7, 17.0, and 12.4 years, respectively). Compared to untreated patients, NTZ-treated patients have a greater relative risk of death in the early years of treatment that varies according to PML risk profile.Conclusions:NTZ as a first-line treatment is associated with the highest net benefit across full ranges of PML risk, mortality, and morbidity compared to FGL or GA. Integrated modeling of long-term treatment risks and benefits informs stratified clinical decision-making and can support patient counseling on selection of first-line treatment options.

The interplay between platelets and tumor cells is known to play important roles in metastasis by enhancing tumor cell survival, tumor-vascular interactions, and escape from immune surveillance. However, platelet-covered circulating tumor cells (CTC) are extremely difficult to isolate due to masking or downregulation of surface epitopes. Here we describe a microfluidic platform that takes advantage of the satellite platelets on the surface of these "stealth" CTCs as a ubiquitous surface marker for isolation. Compared to conventional CTC enrichment techniques which rely on known surface markers expressed by tumor cells, platelet-targeted isolation is generally applicable to CTCs of both epithelial and mesenchymal phenotypes. Our approach first depletes unbound, free platelets by means of hydrodynamic size-based sorting, followed by immunoaffinity-based capture of platelet-covered CTCs using a herringbone micromixing device. This method enabled the reliable isolation of CTCs from 66% of lung and 60% of breast cancer (both epithelial) patient samples, as well as in 83% of melanoma (mesenchymal) samples. Interestingly, we observed special populations of CTCs that were extensively covered by platelets, as well as CTC-leukocyte clusters. Because these cloaked CTCs often escape conventional positive and negative isolation mechanisms, further characterization of these cells may uncover important yet overlooked biological information in blood-borne metastasis and cancer immunology.

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible—elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications.

Introduction/Background High-grade serous ovarian carcinoma (HGSOC), the most common and deadly epithelial ovarian cancer histotype is characterized by a heterogeneous genomic landscape. After surgery, all patients are treated with adjuvant platinum (Pt)-based chemotherapy to which the response is heterogeneous, ranging from cases sensitive (Platinum-sensitive, Pt-s cases), to intrinsically resistant patients, who relapse within 6 months from the end of therapy (Pt-resistant, Pt-r). The aim of the study was to investigate the mechanisms characterizing the biology of primary resistance to upfront Pt-based chemotherapy through an integrated pathway analysis. Methodology Gene and miRNA microarray experiments were carried out on 36 Pt-s and 41 Pt-r tumor samples. Gene and miRNA expression have been integrated using Micrographite algorithm. Expression levels of selected predictive and prognostic genes were validated on a total of 242 HGSOC samples by qRT-PCR and on the Curated Ovarian Database (including 838 HGSOC). Results Expression profiles of 131 mRNAs and five miRNAs, belonging to five different and functionally-related molecular pathways, discriminate Pt-s and Pt-r cases. We selected 23 elements of the networks for orthogonal validation and 19 coding genes confirmed as differentially expressed between Pt-r and Pt-s cases. Among them, 16 elements also showed independent prognostic value in terms of PFS and OS in multivariate analysis. The prognostic impact of this signature was in silico validated on the Curated Ovarian Database, resulting in a 3-gene signature as independent prognostic biomarker of survival for HGSOC. Conclusion In the current study, we used an integrated pathway analysis on miRNA and gene expression signatures to capture the key pathways shaping the different biology of Pt-r and Pt-s tumors, validating our results using two independent cohorts of HGSOC biopsies. Finally, we investigated the association of the validated signature with survival across multiple HGSOC databases. This strategy identified a three-gene signature with predictive and prognostic impact in HGSOC. Disclosure Nothing to disclose

Sleep related Stroke (SRS) is common and has been associated with cerebral small vessel diseases (SVD) in ischemic strokes (ISs). We tested the hypothesis that SRS is associated with SVD in both ischemic and hemorrhagic stroke.Prospectively collected data from patients consecutively enrolled after intracerebral hemorrhage (ICH) related to SVD or after IS were analyzed. Symptom onset was recorded as SRS versus awake. Each ICH was grouped according to lobar and deep locations. The IS cohort was etiologically characterized based on the Causative Classification of Stroke system. Frequencies of SRS within and between ICH and IS cohorts as well as its associations (etiology, risk factors) were analyzed.We analyzed 1812 IS (mean age 67.9 years ± 15.9 years, 46.4% female) and 1038 ICH patients (mean age 72.5 years ± 13.0 years, 45.4% female). SRS was significantly more common among SVD-related ICH patients (n = 276, 26.6%) when compared to all IS (n = 363, 20.0%, P.001) and in both, small artery occlusion (SAO) related IS and lobar ICH within the respective IS and ICH cohorts (16.3% SRS versus 9.1% awake for SAO within all IS, P.001; and 57.1% SRS versus 47.7% awake for lobar bleeds within all ICH, P = .008). These associations remained significant after controlling for age, sex and risk factors.SRS was associated with SVD. The SAO etiology and cerebral amyloid angiopathy related lobar ICH suggest that the presence of SVD can interact with sleep or arousal related hemodynamic changes to cause ischemic and hemorrhagic stroke.

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.

The Journal of Biological Rhythms will be publishing articles 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. By using case examples and highlighting the pearls and pitfalls of statistical inference, the authors will identify and explain ways in which experimental scientists can avoid common analytical and statistical mistakes and use appropriate analytical and statistical methods in their research. In this first article, we address the first steps in analysis of data: understanding the underlying statistical distribution of the data and establishing associative versus causal relationships. These ideas are then applied to sample size, power calculations, correlation testing, differences between description and prediction, and the narrative fallacy.

Objectives/Hypothesis Nasal surgery has been implicated to improve continuous positive airway pressure (CPAP) compliance in patients with obstructive sleep apnea (OSA) and nasal obstruction. However, the cost-effectiveness of nasal surgery to improve CPAP compliance is not known. We modeled the cost-effectiveness of two types of nasal surgery versus no surgery in patients with OSA and nasal obstruction undergoing CPAP therapy. Study Design Cost-effectiveness decision tree model. Methods We built a decision tree model to identify conditions under which nasal surgery would be cost-effective to improve CPAP adherence over the standard of care. We compared turbinate reduction and septoplasty to nonsurgical treatment over varied time horizons from a third-party payer perspective. We included variables for cost of untreated OSA, surgical cost and complications, improved compliance postoperatively, and quality of life. Results Our study identified nasal surgery as a cost-effective strategy to improve compliance of OSA patients using CPAP across a range of plausible model assumptions regarding the cost of untreated OSA, the probability of adherence improvement, and a chronic time horizon. The relatively lower surgical cost of turbinate reduction made it more cost-effective at earlier time horizons, whereas septoplasty became cost-effective after a longer timespan. Conclusions Across a range of plausible values in a clinically relevant decision model, nasal surgery is a cost-effective strategy to improve CPAP compliance in OSA patients with nasal obstruction. Our results suggest that OSA patients with nasal obstruction who struggle with CPAP therapy compliance should undergo evaluation for nasal surgery. Level of Evidence 2c Laryngoscope, 127:977–983, 2017

Perception of sleep-wake times may differ from objective measures, although the mechanisms remain elusive. Quantifying the misperception phenotype involves two operational challenges: defining objective sleep latency and treating sleep latency and total sleep time as independent factors. We evaluated a novel approach to address these challenges and test the hypothesis that sleep fragmentation underlies misperception.We performed a retrospective analysis on patients with or without obstructive sleep apnea during overnight diagnostic polysomnography in our laboratory (n = 391; n = 252). We compared subjective and objective sleep-wake durations to characterize misperception. We introduce a new metric, sleep during subjective latency (SDSL), which captures latency misperception without defining objective sleep latency and allows correction for latency misperception when assessing total sleep time (TST) misperception.The stage content of SDSL is related to latency misperception, but in the opposite manner as our hypothesis: those with20 minutes of SDSL had less N1%, more N3%, and lower transition frequency. After adjusting for misperceived sleep during subjective sleep latency, TST misperception was greater in those with longer bouts of REM and N2 stages (OSA patients) as well as N3 (non-OSA patients), which also did not support our hypothesis.Despite the advantages of SDSL as a phenotyping tool to overcome operational issues with quantifying misperception, our results argue against the hypothesis that light or fragmented sleep underlies misperception. Further investigation of sleep physiology utilizing alternative methods than that captured by conventional stages may yield additional mechanistic insights into misperception.A commentary on this article appears in this issue on page 1211.

Marilyn Moro,1 Balaji Goparaju,1 Jelina Castillo,1 Yvonne Alameddine,1 Matt T Bianchi1,2 1Neurology Department, Massachusetts General Hospital, 2Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA Introduction: Periodic limb movements of sleep (PLMS) may increase cardiovascular and cerebrovascular morbidity. However, most people with PLMS are either asymptomatic or have nonspecific symptoms. Therefore, predicting elevated PLMS in the absence of restless legs syndrome remains an important clinical challenge.Methods: We undertook a retrospective analysis of demographic data, subjective symptoms, and objective polysomnography (PSG) findings in a clinical cohort with or without obstructive sleep apnea (OSA) from our laboratory (n=443 with OSA, n=209 without OSA). Correlation analysis and regression modeling were performed to determine predictors of periodic limb movement index (PLMI). Markov decision analysis with TreeAge software compared strategies to detect PLMS: in-laboratory PSG, at-home testing, and a clinical prediction tool based on the regression analysis.Results: Elevated PLMI values (>15 per hour) were observed in >25% of patients. PLMI values in No-OSA patients correlated with age, sex, self-reported nocturnal leg jerks, restless legs syndrome symptoms, and hypertension. In OSA patients, PLMI correlated only with age and self-reported psychiatric medications. Regression models indicated only a modest predictive value of demographics, symptoms, and clinical history. Decision modeling suggests that at-home testing is favored as the pretest probability of PLMS increases, given plausible assumptions regarding PLMS morbidity, costs, and assumed benefits of pharmacological therapy.Conclusion: Although elevated PLMI values were commonly observed, routinely acquired clinical information had only weak predictive utility. As the clinical importance of elevated PLMI continues to evolve, it is likely that objective measures such as PSG or at-home PLMS monitors will prove increasingly important for clinical and research endeavors.Keywords: periodic limb movements, polysomnography, predictors, sleep, decision analysis, cost-effectiveness, diagnostic

Objectives Absence of somatosensory evoked potentials is considered a nearly perfect predictor of poor outcome after cardiac arrest. However, reports of good outcomes despite absent somatosensory evoked potentials and high rates of withdrawal of life-sustaining therapies have raised concerns that estimates of the prognostic value of absent somatosensory evoked potentials may be biased by self-fulfilling prophecies. We aimed to develop an unbiased estimate of the false positive rate of absent somatosensory evoked potentials as a predictor of poor outcome after cardiac arrest. Data sources PubMed. Study selection We selected 35 studies in cardiac arrest prognostication that reported somatosensory evoked potentials. Data extraction In each study, we identified rates of withdrawal of life-sustaining therapies and good outcomes despite absent somatosensory evoked potentials. We appraised studies for potential biases using the Quality in Prognosis Studies tool. Using these data, we developed a statistical model to estimate the false positive rate of absent somatosensory evoked potentials adjusted for withdrawal of life-sustaining therapies rate. Data synthesis Two-thousand one-hundred thirty-three subjects underwent somatosensory evoked potential testing. Five-hundred ninety-four had absent somatosensory evoked potentials; of these, 14 had good functional outcomes. The rate of withdrawal of life-sustaining therapies for subjects with absent somatosensory evoked potential could be estimated in 14 of the 35 studies (mean 80%, median 100%). The false positive rate for absent somatosensory evoked potential in predicting poor neurologic outcome, adjusted for a withdrawal of life-sustaining therapies rate of 80%, is 7.7% (95% CI, 4-13%). Conclusions Absent cortical somatosensory evoked potentials do not infallibly predict poor outcome in patients with coma following cardiac arrest. The chances of survival in subjects with absent somatosensory evoked potentials, though low, may be substantially higher than generally believed.

Objectives Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the complexity of PSG signals and physiological heterogeneity between patients. Deep neural networks, which have recently achieved expert-level performance for other complex medical tasks, are ideally suited to PSG scoring, given sufficient training data. Methods We used a combination of deep recurrent and convolutional neural networks (RCNN) for supervised learning of clinical labels designating sleep stages, sleep apnea events, and limb movements. The data for testing and training were derived from 10 000 clinical PSGs and 5804 research PSGs. Results When trained on the clinical dataset, the RCNN reproduces PSG diagnostic scoring for sleep staging, sleep apnea, and limb movements with accuracies of 87.6%, 88.2% and 84.7% on held-out test data, a level of performance comparable to human experts. The RCNN model performs equally well when tested on the independent research PSG database. Only small reductions in accuracy were noted when training on limited channels to mimic at-home monitoring devices: frontal leads only for sleep staging, and thoracic belt signals only for the apnea-hypopnea index. Conclusions By creating accurate deep learning models for sleep scoring, our work opens the path toward broader and more timely access to sleep diagnostics. Accurate scoring automation can improve the utility and efficiency of in-lab and at-home approaches to sleep diagnostics, potentially extending the reach of sleep expertise beyond specialty clinics.

The most common measures of diagnostic test performance, sensitivity and specificity, involve two simplifying assumptions: that disease status is binary (present or absent), and test results are binary (positive or negative). Bayes’ theorem tells us that these features must be combined with a third ingredient, the prior or pretest probability (PreTP) of disease, to update the disease probability following the observed test result. As we1 2 and others3 4 have written, readers and authors of medical literature often interpret test results in ways that violate Bayes’ rule. Publications celebrating diagnostic tests that on close inspection perform near-chance level represent an important example of this interpretation risk.5 6 In some cases, even frankly paradoxical combinations of sensitivity and specificity are reported, for example, with certain physical examination findings,7 in which a ‘positive’ result lowers the disease probability, and ‘negative’ result increases it. We recently pointed out a simple litmus test that can be used at a glance to recognise the potential for chance or paradoxical performance, which we term the ‘rule of 100’.6 Any test for which the sensitivity and specificity add to 100% ![Formula][1] does not modify the PreTP of disease, that is, the result (positive or negative) provides a post-test probability (PostTP), identical to the PreTP. Such tests therefore provide no information. Here is a three-line proof: ![Formula][2] The second line of the proof makes use of the fact that ![Formula][3] when ![Formula][4] For those comfortable with combining sensitivity and specificity into the likelihood ratio (LR) value, … [1]: /embed/mml-math-1.gif [2]: /embed/mml-math-2.gif [3]: /embed/mml-math-3.gif [4]: /embed/mml-math-4.gif

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 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

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.

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.

What makes economic and ecological networks so unlike other highly skewed networks in their tendency toward turbulence and collapse? Here, we explore the consequences of a defining feature of these networks: their nodes are tied together by flow. We show that flow networks tend to the power law degree distribution (PLDD) due to a self-reinforcing process involving position within the global network structure, and thus present the first random graph model for PLDDs that does not depend on a rich-get-richer function of nodal degree. We also show that in contrast to non-flow networks, PLDD flow networks are dramatically more vulnerable to catastrophic failure than non-PLDD flow networks, a finding with potential explanatory power in our age of resource- and financial-interdependence and turbulence., Social Networks, 2013

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.

Nasal surgery has been implicated to improve continuous positive airway pressure (CPAP) compliance in patients with obstructive sleep apnea (OSA) and nasal obstruction. However, the cost-effectiveness of nasal surgery to improve CPAP compliance is not known. We modeled the cost-effectiveness of two types of nasal surgery versus no surgery in patients with OSA and nasal obstruction undergoing CPAP therapy.Cost-effectiveness decision tree model.We built a decision tree model to identify conditions under which nasal surgery would be cost-effective to improve CPAP adherence over the standard of care. We compared turbinate reduction and septoplasty to nonsurgical treatment over varied time horizons from a third-party payer perspective. We included variables for cost of untreated OSA, surgical cost and complications, improved compliance postoperatively, and quality of life.Our study identified nasal surgery as a cost-effective strategy to improve compliance of OSA patients using CPAP across a range of plausible model assumptions regarding the cost of untreated OSA, the probability of adherence improvement, and a chronic time horizon. The relatively lower surgical cost of turbinate reduction made it more cost-effective at earlier time horizons, whereas septoplasty became cost-effective after a longer timespan.Across a range of plausible values in a clinically relevant decision model, nasal surgery is a cost-effective strategy to improve CPAP compliance in OSA patients with nasal obstruction. Our results suggest that OSA patients with nasal obstruction who struggle with CPAP therapy compliance should undergo evaluation for nasal surgery.2c Laryngoscope, 127:977-983, 2017.

The objective of this Land seismic case study is to share the learnings ENI and CGG gained from a field test performed in the course of a production project located in South Tunisia. The objective of this study was to evaluate how to optimally use the available field equipment to Maximize the information content of the seismic data for the purpose of enhanced structural and quantitative interpretation. The use of single vibrators, of smaller receiver arrays and reduced slip time, did allow, using the same equipment, to efficiently acquire the seismic data with a trace density significantly higher than conventional coverage. Final Imaging results illustrate that Trace density and not source strength, is the key parameter that controls the qualitative and quantitative seismic Imaging value of the Subsurface

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.