Nataliia Kozhemiako & Shaun Purcell We recently used NSRR data to study the so-called spectral slope of the electroencephalogram (EEG), during wake, NREM and REM sleep. This work (described in a bioRxiv pre-print, Kozhemiako et al.) points to the power of NSRR data: thousands of polysomnographic studies that can be rapidly and freely repurposed to address a broad array of research questions. Keep reading
What is the ENIGMA-Sleep? The Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) consortium is a global collaboration of over 1400 scientists across 43 countries, studying neuropsychiatric illnesses and provides a powerful collaborative framework around the world. ENIGMA has more than 50 working groups, pooling large-scale coordinated data and expertise to answer fundamental clinical and neuroscientific questions, which offers testing reproducibility and robustness of findings (1). Keep reading
The NSRR is constantly developing new tools to improve its user experience. One of the newly developed applications, as inspired by the Dementias Platform, is the Cohort Matrix. The NSRR cohort matrix consists of three tabs: "Cohort Overview" tab provides summary of the key characteristics (e.g. sample size, age range, license, etc.), sleep data availability (e.g. polysomnography EDF files, actigraphy, etc.) and links back to the dataset introduction page. Keep reading
Guest Blogger: Mattias Baumert What is the problem being addressed? Our objective was to quantify the burden of cortical arousals throughout sleep and determine its association with long-term cardiovascular (CV) and overall mortality. What was the approach to solving the problem? We quantified arousal burden (AB) as the cumulative duration of all arousal events relative to total sleep time in three large cohort studies. Keep reading
In an effort to highlight new and exciting work related to the NSRR, we are featuring guest blog posts from authors who have recently published using NSRR data. The following references: Zeng S, Li F, Wang R, Li F. Propensity score weighting for covariate adjustment in randomized clinical trials. Statistics in Medicine. 2020;1–17. https://doi.org/10.1002/sim.8805 Please contact support@sleepdata.org if you have new work you would like to share in a guest blog post. Keep reading
A patient's apnea-hypopnea index (AHI) determines whether or not they are eligible for reimbursable treatment. But how certain can we be that a patient's AHI is actually above or below a clinical threshold? In this study using 2049 subjects from MESA dataset from NSRR, we develop a metric for computing a confidence interval around a patient's AHI. Keep reading
Brigham and Women's Hospital, June 9, 2020 – The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), has announced that the National Sleep Research Resource (NSRR), hosted by Brigham and Women's Hospital, was awarded a five-year contract, facilitating an expansion of capabilities and providing support for increased community involvement. Keep reading
The Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b), which began in 2010, studies pregnant women who will be delivering for the first time (nulliparous women). This prospective cohort study evaluates the underlying, interrelated mechanisms of several common adverse pregnancy outcomes, which can be unpredictable in women who have little or no pregnancy history, to help guide their treatment. Keep reading
To paraphrase the adage, a picture is worth a thousand numbers. In order to investigate some basic properties of NSRR datasets, here we generate a number of whole-dataset visualizations. To make sense of these images, we’ll employ a remarkably complex computational pattern recognition and dimension reduction framework, a.k.a. the human visual system. Keep reading
The NSRR is revamping its Tools pages and needs your help! Have you developed a tool for the analysis of sleep data that you'd like others to know about and use? Do you have some tricks and tips for using existing packages that you'd like to share? What about a write-up listing your favorite tools, explaining how you use them and what's good about them? Or perhaps you'd like to share some data analytic problems that aren't met by existing tools? If so, we'd love for you to submit a gues. Keep reading