001007829 001__ 1007829
001007829 005__ 20240226075242.0
001007829 0247_ $$2doi$$a10.1002/mds.29389
001007829 0247_ $$2ISSN$$a0885-3185
001007829 0247_ $$2ISSN$$a1531-8257
001007829 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-02214
001007829 0247_ $$2pmid$$a37071758
001007829 0247_ $$2WOS$$aWOS:000969916600001
001007829 037__ $$aFZJ-2023-02214
001007829 082__ $$a610
001007829 1001_ $$0P:(DE-Juel1)184882$$aSeger, Aline$$b0$$eCorresponding author$$ufzj
001007829 245__ $$aEvaluation of a Structured Screening Assessment to Detect Isolated Rapid Eye Movement Sleep Behavior Disorder
001007829 260__ $$aNew York, NY$$bWiley$$c2023
001007829 3367_ $$2DRIVER$$aarticle
001007829 3367_ $$2DataCite$$aOutput Types/Journal article
001007829 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1706531744_11227
001007829 3367_ $$2BibTeX$$aARTICLE
001007829 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001007829 3367_ $$00$$2EndNote$$aJournal Article
001007829 520__ $$aABSTRACT: Background: Isolated rapid eye movement(REM) sleep behavior disorder (iRBD) cohorts have providedinsights into the earliest neurodegenerative processes inα-synucleinopathies. Even though polysomnography (PSG)remains the gold standard for diagnosis, an accuratequestionnaire-based algorithm to identify eligible subjectscould facilitate efficient recruitment in research.Objective: This study aimed to optimize the identificationof subjects with iRBD from the general population.Methods: Between June 2020 and July 2021, we placednewspaper advertisements, including the single-questionscreen for RBD (RBD1Q). Participants’ evaluationsincluded a structured telephone screening consisting ofthe RBD screening questionnaire (RBDSQ) and additionalsleep-related questionnaires. We examined anamnesticinformation predicting PSG-proven iRBD using logisticregressions and receiver operating characteristic curves.Results: Five hundred forty-three participants answeredthe advertisements, and 185 subjects fulfilling inclusionand exclusion criteria were screened. Of these,124 received PSG after expert selection, and 78 (62.9%)were diagnosed with iRBD. Selected items of theRBDSQ, the Pittsburgh Sleep Quality Index, the STOPBangquestionnaire, and age predicted iRBD with highaccuracy in a multiple logistic regression model (areaunder the curve >80%). When comparing the algorithmto the sleep expert decision, 77 instead of 124 polysomnographies(62.1%) would have been carried out,and 63 (80.8%) iRBD patients would have been identified;32 of 46 (69.6%) unnecessary PSG examinationscould have been avoided.Conclusions: Our proposed algorithm displayed highdiagnostic accuracy for PSG-proven iRBD costeffectivelyand may be a convenient tool for research andclinical settings. External validation sets are warranted toprove reliability. © 2023 The Authors. Movement Disorderspublished by Wiley Periodicals LLC on behalf ofInternational Parkinson and Movement Disorder Society.Key Words: general population; Parkinson’s disease;prediction; questionnaire; rapid eye movement sleepbehavior disorder
001007829 536__ $$0G:(DE-HGF)POF4-5252$$a5252 - Brain Dysfunction and Plasticity (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001007829 536__ $$0G:(GEPRIS)431549029$$aDFG project 431549029 - SFB 1451: Schlüsselmechanismen normaler und krankheitsbedingt gestörter motorischer Kontrolle (431549029)$$c431549029$$x1
001007829 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001007829 7001_ $$00000-0001-5858-7762$$aOphey, Anja$$b1
001007829 7001_ $$0P:(DE-HGF)0$$aHeitzmann, Wiebke$$b2
001007829 7001_ $$0P:(DE-Juel1)161350$$aDoppler, Christopher E. J.$$b3
001007829 7001_ $$0P:(DE-HGF)0$$aLindner, Marie-Sophie$$b4
001007829 7001_ $$0P:(DE-Juel1)184720$$aBrune, Corinna$$b5
001007829 7001_ $$0P:(DE-HGF)0$$aKickartz, Johanna$$b6
001007829 7001_ $$0P:(DE-HGF)0$$aDafsari, Haidar S.$$b7
001007829 7001_ $$0P:(DE-HGF)0$$aOertel, Wolfgang H.$$b8
001007829 7001_ $$0P:(DE-Juel1)131720$$aFink, Gereon R.$$b9
001007829 7001_ $$00000-0003-0477-2289$$aJost, Stefanie T.$$b10
001007829 7001_ $$0P:(DE-Juel1)179044$$aSommerauer, Michael$$b11$$eCorresponding author$$ufzj
001007829 773__ $$0PERI:(DE-600)2041249-6$$a10.1002/mds.29389$$gp. mds.29389$$n6$$p990-999$$tMovement disorders$$v38$$x0885-3185$$y2023
001007829 8564_ $$uhttps://juser.fz-juelich.de/record/1007829/files/PDF.pdf$$yOpenAccess
001007829 909CO $$ooai:juser.fz-juelich.de:1007829$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
001007829 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)184882$$aForschungszentrum Jülich$$b0$$kFZJ
001007829 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)161350$$aForschungszentrum Jülich$$b3$$kFZJ
001007829 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)131720$$aForschungszentrum Jülich$$b9$$kFZJ
001007829 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)179044$$aForschungszentrum Jülich$$b11$$kFZJ
001007829 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5252$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0
001007829 9141_ $$y2023
001007829 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2023-10-24
001007829 915__ $$0LIC:(DE-HGF)CCBYNCND4$$2HGFVOC$$aCreative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0
001007829 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bMOVEMENT DISORD : 2022$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)3001$$2StatID$$aDEAL Wiley$$d2023-10-24$$wger
001007829 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001007829 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bMOVEMENT DISORD : 2022$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine$$d2023-10-24
001007829 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2023-10-24$$wger
001007829 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2023-10-24
001007829 920__ $$lyes
001007829 9201_ $$0I:(DE-Juel1)INM-3-20090406$$kINM-3$$lKognitive Neurowissenschaften$$x0
001007829 980__ $$ajournal
001007829 980__ $$aVDB
001007829 980__ $$aI:(DE-Juel1)INM-3-20090406
001007829 980__ $$aUNRESTRICTED
001007829 9801_ $$aFullTexts