Conditional Spectral Analysis of Replicated Multiple Time Series with Application to Nocturnal Physiology

This article considers the problem of analyzing associations between power spectra of multiple time series and cross-sectional outcomes when data are observed from multiple subjects. The motivating application comes from sleep medicine, where researchers are able to non-invasively record physiological time series signals during sleep. The frequency patterns of these signals, which can be quantified through the power spectrum, contain interpretable information about biological processes. An important problem in sleep research is drawing connections between power spectra of time series signals and clinical characteristics; these connections are key to understanding biological pathways through which sleep affects, and can be treated to improve, health. Such analyses are challenging as they must overcome the complicated structure of a power spectrum from multiple time series as a complex positive-definite matrix-valued function. This article proposes a new approach to such analyses based on a tensor-product spline model of Cholesky components of outcome-dependent power spectra. The approach flexibly models power spectra as nonparametric functions of frequency and outcome while preserving geometric constraints. Formulated in a fully Bayesian framework, a Whittle likelihood based Markov chain Monte Carlo (MCMC) algorithm is developed for automated model fitting and for conducting inference on associations between outcomes and spectral measures. The method is used to analyze data from a study of sleep in older adults and uncovers new insights into how stress and arousal are connected to the amount of time one spends in bed

Hyperarousal and Beyond: New Insights to the Pathophysiology of Insomnia Disorder through Functional Neuroimaging Studies

Neuroimaging studies have produced seemingly contradictory findings in regards to the pathophysiology of insomnia. Although most study results are interpreted from the perspective of a “hyperarousal” model, the aggregate findings from neuroimaging studies suggest a more complex model is needed. We provide a review of the major findings from neuroimaging studies, then discuss them in relation to a heuristic model of sleep-wake states that involves three major factors: wake drive, sleep drive, and level of conscious awareness. We propose that insomnia involves dysregulation in these factors, resulting in subtle dysregulation of sleep-wake states throughout the 24 h light/dark cycle

Computerized adaptive measurement of depression: A simulation study

BACKGROUND: Efficient, accurate instruments for measuring depression are increasingly important in clinical practice. We developed a computerized adaptive version of the Beck Depression Inventory (BDI). We examined its efficiency and its usefulness in identifying Major Depressive Episodes (MDE) and in measuring depression severity. METHODS: Subjects were 744 participants in research studies in which each subject completed both the BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale. RESULTS: The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%, equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21 items). The adaptive latent depression score correlated r = .92 with the BDI total score and the latent depression score correlated more highly with the Hamilton (r = .74) than the BDI total score did (r = .70). CONCLUSIONS: Adaptive testing for depression may provide greatly increased efficiency without loss of accuracy in identifying MDE or in measuring depression severity

The consensus sleep diary: Standardizing prospective sleep self-monitoring

Study Objectives: To present an expert consensus, standardized, patient-informed sleep diary. Methods and Results: Sleep diaries from the original expert panel of 25 attendees of the Pittsburgh Assessment Conference1 were collected and reviewed. A smaller subset of experts formed a committee and reviewed the compiled diaries. Items deemed essential were included in a Core sleep diary, and those deemed optional were retained for an expanded diary. Secondly, optional items would be available in other versions. A draft of the Core and optional versions along with a feedback questionnaire were sent to members of the Pittsburgh Assessment Conference. The feedback from the group was integrated and the diary drafts were subjected to 6 focus groups composed of good sleepers, people with insomnia, and people with sleep apnea. The data were summarized into themes and changes to the drafts were made in response to the focus groups. The resultant draft was evaluated by another focus group and subjected to lexile analyses. The lexile analyses suggested that the Core diary instructions are at a sixth-grade reading level and the Core diary was written at a third-grade reading level. Conclusions: The Consensus Sleep Diary was the result of collaborations with insomnia experts and potential users. The adoption of a standard sleep diary for insomnia will facilitate comparisons across studies and advance the field. The proposed diary is intended as a living document which still needs to be tested, refined, and validate

Effectiveness of Liraglutide and Lixisenatide in the Treatment of Type 2 Diabetes: Real-World Evidence from The Health Improvement Network (THIN) Database in the United Kingdom.

INTRODUCTION: The glucagon-like peptide-1 receptor agonists liraglutide and lixisenatide are effective at reducing glycated hemoglobin (HbA1c) levels in patients with type 2 diabetes mellitus (T2DM). Although liraglutide has demonstrated superior efficacy in head-to-head clinical trials, real-world evidence of comparative effectiveness is lacking. This observational study aimed to assess the effectiveness of liraglutide versus lixisenatide in UK clinical practice. METHODS: Electronic medical records from The Health Improvement Network (THIN) UK primary care database were analyzed. Patients aged ≥18 years, diagnosed with T2DM, and prescribed liraglutide or lixisenatide between 01 May 2013 and 31 December 2015 were included in the study. Adjusted linear regression models compared the difference in mean change in HbA1c, body mass index (BMI), and systolic blood pressure (SBP) after 12-month follow-up. The proportion of patients achieving glycemic control (HbA1c 1%; and weight reduction ≥3% within 12 months were determined. Cox proportional hazards modeling was used to evaluate the effect of treatment on time to achieving HbA1c and weight reduction targets. Healthcare resource use (HCRU) (GP, secondary care, hospitalizations) was compared using analysis of covariance. RESULTS: The primary outcome was assessed in 579 liraglutide and 213 lixisenatide new users. Fully adjusted linear regression indicated that liraglutide reduced HbA1c significantly more than lixisenatide (mean treatment difference -0.30; 95% CI -0.56, -0.04; p = 0.025). Compared to lixisenatide, liraglutide recipients were 2.5 times more likely to achieve HbA1c 1% HbA1c reduction (HR 1.29; p = 0.0002). BMI and SBP reductions were greater for the liraglutide group but results were not significant. HCRU was comparable between treatment groups. CONCLUSION: These results from the THIN database indicate that liraglutide treatment provided better outcomes related to glycemic control. FUNDING: Novo Nordisk

Sleep spindle deficits in antipsychotic-naïve early course schizophrenia and in non-psychotic first-degree relatives

Introduction: Chronic medicated patients with schizophrenia have marked reductions in sleep spindle activity and a correlated deficit in sleep-dependent memory consolidation. Using archival data, we investigated whether antipsychotic-naïve early course patients with schizophrenia and young non-psychotic first-degree relatives of patients with schizophrenia also show reduced sleep spindle activity and whether spindle activity correlates with cognitive function and symptoms. Method: Sleep spindles during Stage 2 sleep were compared in antipsychotic-naïve adults newly diagnosed with psychosis, young non-psychotic first-degree relatives of schizophrenia patients and two samples of healthy controls matched to the patients and relatives. The relations of spindle parameters with cognitive measures and symptom ratings were examined. Results: Early course schizophrenia patients showed significantly reduced spindle activity relative to healthy controls and to early course patients with other psychotic disorders. Relatives of schizophrenia patients also showed reduced spindle activity compared with controls. Reduced spindle activity correlated with measures of executive function in early course patients, positive symptoms in schizophrenia and IQ estimates across groups. Conclusions: Like chronic medicated schizophrenia patients, antipsychotic-naïve early course schizophrenia patients and young non-psychotic relatives of individuals with schizophrenia have reduced sleep spindle activity. These findings indicate that the spindle deficit is not an antipsychotic side-effect or a general feature of psychosis. Instead, the spindle deficit may predate the onset of schizophrenia, persist throughout its course and be an endophenotype that contributes to cognitive dysfunction

A Nationally Representative Survey Assessing Restorative Sleep in US Adults

Restorative sleep is a commonly used term but a poorly defined construct. Few studies have assessed restorative sleep in nationally representative samples. We convened a panel of 7 expert physicians and researchers to evaluate and enhance available measures of restorative sleep. We then developed the revised Restorative Sleep Questionnaire (REST-Q), which comprises 9 items assessing feelings resulting from the prior sleep episode, each with 5-point Likert response scales. Finally, we assessed the prevalence of high, somewhat, and low REST-Q scores in a nationally representative sample of US adults (n= 1,055) and examined the relationship of REST-Q scores with other sleep and demographic characteristics. Pairwise correlations were performed between the REST-Q scores and other self-reported sleep measures. Weighted logistic regression analyses were conducted to compare scores on the REST-Q with demographic variables. The prevalence of higher REST-Q scores (4 or 5 on the Likert scale) was 28.1% in the nationally representative sample. REST-Q scores positively correlated with sleep quality (r=0.61) and sleep duration (r=0.32), and negatively correlated with both difficulty falling asleep (r=-0.40) and falling back asleep after waking (r=-0.41). Higher restorative sleep scores (indicating more feelings of restoration upon waking) were more common among those who were: ≥60 years of age (OR=4.20, 95%CI: 1.92-9.17); widowed (OR=2.35, 95%CI:1.01-5.42), and retired (OR=2.02, 95%CI:1.30-3.14). Higher restorative sleep scores were less frequent among those who were not working (OR=0.36, 95%CI: 0.10-1.00) and living in a household with two or more persons (OR=0.51,95%CI:0.29-0.87). Our findings suggest that the REST-Q may be useful for assessing restorative sleep

Genome-wide association studies and cross-population meta-analyses investigating short and long sleep duration

Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression