ReviewSleep2024
The National Sleep Research Resource: making data findable, accessible, interoperable, reusable and promoting sleep science.
Review in Sleep, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Sleep slow oscillation emergence on the scalp as a renewal point process.PLoS computational biology · 2026Article
- Slow wave canonical activity deviation concept: Toward a slow wave-based EEG-fMRI reference map for health-associated network function.iScience · 2026Article
- Article
- Development of a rule-based natural language processing algorithm to extract sleep information in pediatric primary care patients with a sleep diagnosis.Sleep advances : a journal of the Sleep Research Society · 2026Article
- SLEEPYLAND: trust begins with fair evaluation of automatic sleep staging models.NPJ digital medicine · 2025Article
- Harvard Electroencephalography Database: A comprehensive clinical electroencephalographic resource from four Boston hospitals.Epilepsia · 2025Article
- Research Priorities for Translating Endophenotyping of Adult Obstructive Sleep Apnea to the Clinic: An Official American Thoracic Society Research Statement.American journal of respiratory and critical care medicine · 2025Article
- Big data approaches for novel mechanistic insights on sleep and circadian rhythms: a workshop summary.Sleep · 2025Article
- Editorial: Biological and digital markers in sleep, circadian rhythm and epilepsy using artificial intelligence.Frontiers in physiology · 2025Article
- Early childhood sleep quality in a pediatric cohort: sex-specific differences.Frontiers in sleep · 2025Article
- Construction of an index system of core competence assessment for sleep medicine nurse specialists in China: a Delphi study.BMC nursing · 2024Article
- Article
- Sensors, technologies, and classification algorithms for monitoring and diagnosis of sleep apnea.Digital healthReview
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
This paper presents a comprehensive overview of the National Sleep Research Resource (NSRR), a National Heart Lung and Blood Institute-supported repository developed to share data from clinical studies focused on the evaluation of sleep disorders. The NSRR addresses challenges presented by the heterogeneity of sleep-related data, leveraging innovative strategies to optimize the quality and accessibility of available datasets. It provides authorized users with secure centralized access to a large quantity of sleep-related data including polysomnography, actigraphy, demographics, patient-reported outcomes, and other data. In developing the NSRR, we have implemented data processing protocols that ensure de-identification and compliance with FAIR (Findable, Accessible, Interoperable, Reusable) principles. Heterogeneity stemming from intrinsic variation in the collection, annotation, definition, and interpretation of data has proven to be one of the primary obstacles to efficient sharing of datasets. Approaches employed by the NSRR to address this heterogeneity include (1) development of standardized sleep terminologies utilizing a compositional coding scheme, (2) specification of comprehensive metadata, (3) harmonization of commonly used variables, and (3) computational tools developed to standardize signal processing. We have also leveraged external resources to engineer a domain-specific approach to data harmonization. We describe the scope of data within the NSRR, its role in promoting sleep and circadian research through data sharing, and harmonization of large datasets and analytical tools. Finally, we identify opportunities for approaches for the field of sleep medicine to further support data standardization and sharing.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.