Evidence map›Paper›PMID 41928821›Full record

ArticleResearch square2026

Longitudinal resting-state EEG-based modeling predicts phenoconversion and delineates heterogeneity in isolated REM sleep behavior disorder.

Soonhyun Yook, Jung-Won Shin, Tae-Gon Noh, Gilsoon Park, Sumin Bae, Kang-Min Choi, Jung-Hwan Shin, Han-Joon Kim, Ki-Young Jung, Hosung Kim

Abstract readPreprint
In one paragraph

Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Soonhyun YookUniversity of Southern California.
Jung-Won ShinCHA University.
Tae-Gon NohSeoul National University.
Gilsoon ParkUniversity of Southern California.
Sumin BaeSeoul National University Hospital, Seoul National University College of Medicine.
Kang-Min ChoiSeoul National University of Science and Technology (Seoultech).
Jung-Hwan ShinSeoul National University Hospital, Seoul National University College of Medicine.
Han-Joon KimSeoul National University Hospital, Seoul National University College of Medicine.
Ki-Young JungSeoul National University Hospital, Seoul National University College of Medicine.
Hosung KimUniversity of Southern California.

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

Isolated REM sleep behavior disorder is a high-risk prodromal syndrome for Lewy body diseases but highly heterogeneous. Neurophysiologic markers resolving this heterogeneity and predicting phenoconversion remain limited. We applied Subtype and Stage Inference (SuStaIn) modeling to longitudinal resting-state EEG from a prospective cohort of 285 participants. SuStaIn identified two subtypes: Subtype 1, a posterior beta-dominant, largely non-progressive phenotype associated with higher educational attainment and absence of phenoconversion, and Subtype 2, a frontal slow-wave-dominant phenotype characterized by progressive delta/theta increases and cognitive decline. Longitudinal validation demonstrated substantial subtype shifting in Subtype 1 and stage advancement predominantly in Subtype 2. In Kaplan-Meier analysis, subtype shifting and accelerated annual stage advancement (ΔStage ≥ 2) identified individuals at exceptionally high phenoconversion risk with survival approaching 0-15% by 7.5 years. These findings extend SuStaIn beyond cross-sectional inference by incorporating longitudinal subtype-shifting and stage-advancement features to stratify prodromal heterogeneity and predict neurodegenerative progression.

Identifiers

PMID41928821
PMCPMC13042188

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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.