Tamires Tiemi Kishi, Monica Levy Andersen, Ygor Matos Luciano, Viviane Akemi Kakazu, Sergio Tufik, Gabriel Natan Pires
{"title":"Methods for REM Sleep Density Analysis: A Scoping Review.","authors":"Tamires Tiemi Kishi, Monica Levy Andersen, Ygor Matos Luciano, Viviane Akemi Kakazu, Sergio Tufik, Gabriel Natan Pires","doi":"10.3390/clockssleep5040051","DOIUrl":null,"url":null,"abstract":"<p><p>Rapid eye movements (REM) sleep density is the parameter proposed to explain the variability in the amount of eye movements during REM sleep. Alterations in REM sleep density have been proposed as a screening criterion for individuals with depression and other mental health conditions, but its accuracy has not been properly evaluated. The lack of consensus and the variability of the methods used to score it reduces the external validity of the results, hindering an adequate analysis of its diagnostic accuracy and clinical applicability. This scoping review aimed to identify and quantify the methods used to score REM sleep density, describing their main characteristics. A literature search was conducted in PubMed, Scopus, PsycInfo, and Web of Science. Only studies with objective measures for REM sleep density analysis in individuals with depression were considered eligible. The final sample comprised 57 articles, covering 64 analyses of REM sleep density. The relative frequency methods were the predominant measurement parameter for analyzing REM sleep density across studies. The most frequently adopted REM estimation unit was the number of REM events followed by mini-epochs containing REM. The most common unit of measurement were frequency/time measures. The results demonstrate that there is no consistency in the methods used to calculate REM sleep density in the literature, and a high percentage of studies do not describe their methods in sufficient detail. The most used method was the number of REM episodes per minute of REM sleep, but its use is neither unanimous nor consensual. The methodological inconsistencies and omissions among studies limit the replicability, comparability, and clinical applicability of REM sleep density. Future guidelines should discuss and include a specific methodology for the scoring of REM sleep density, so it can be consensually implemented in clinical services and research.</p>","PeriodicalId":33568,"journal":{"name":"Clocks & Sleep","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10742531/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clocks & Sleep","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/clockssleep5040051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
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Abstract
Rapid eye movements (REM) sleep density is the parameter proposed to explain the variability in the amount of eye movements during REM sleep. Alterations in REM sleep density have been proposed as a screening criterion for individuals with depression and other mental health conditions, but its accuracy has not been properly evaluated. The lack of consensus and the variability of the methods used to score it reduces the external validity of the results, hindering an adequate analysis of its diagnostic accuracy and clinical applicability. This scoping review aimed to identify and quantify the methods used to score REM sleep density, describing their main characteristics. A literature search was conducted in PubMed, Scopus, PsycInfo, and Web of Science. Only studies with objective measures for REM sleep density analysis in individuals with depression were considered eligible. The final sample comprised 57 articles, covering 64 analyses of REM sleep density. The relative frequency methods were the predominant measurement parameter for analyzing REM sleep density across studies. The most frequently adopted REM estimation unit was the number of REM events followed by mini-epochs containing REM. The most common unit of measurement were frequency/time measures. The results demonstrate that there is no consistency in the methods used to calculate REM sleep density in the literature, and a high percentage of studies do not describe their methods in sufficient detail. The most used method was the number of REM episodes per minute of REM sleep, but its use is neither unanimous nor consensual. The methodological inconsistencies and omissions among studies limit the replicability, comparability, and clinical applicability of REM sleep density. Future guidelines should discuss and include a specific methodology for the scoring of REM sleep density, so it can be consensually implemented in clinical services and research.