Evidence map›Paper›PMID 42290980›Full record

ArticleFrontiers in psychiatry2026

Predicting ordinal clinical outcomes in at-risk mental states: a multimodal approach.

Kazuya Nagasawa, Yuko Higuchi, Naohito Kaneko, Kensei Miyazu, Shunsuke Shimataki, Shimako Nishiyama, Yukiko Akasaki, Marino Izumi, Noa Tsujii, Tsutomu Takahashi

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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.

Kazuya NagasawaDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
Yuko HiguchiDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
Naohito KanekoDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
Kensei MiyazuDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
Shunsuke ShimatakiDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
Shimako NishiyamaDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
Yukiko AkasakiDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
Marino IzumiDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
Noa TsujiiDepartment of Child Mental Health and Development, Toyama University Hospital, Toyama, Japan.
Tsutomu TakahashiDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Clinical outcomes in individuals with at-risk mental states (ARMS) are heterogeneous and extend beyond the simple dichotomy between transition and non-transition to psychosis. While previous studies have primarily focused on predicting the transition to psychosis, few have systematically examined multiple outcome stages, including remission and persistent subthreshold symptoms, using integrated neurobiological markers. This study aimed to identify the predictors of multilevel clinical outcomes in ARMS using a multimodal framework that incorporates clinical, functional, and electrophysiological measures. Methods: Eighty-seven subjects with ARMS were included and followed up, and the clinical outcomes were classified into four ordered categories based on a framework derived from the North American Prodrome Longitudinal Study 2 (NAPLS-2): remission, symptomatic, prodromal progression, and psychotic. Ordinal logistic regression analyses were conducted to identify predictors associated with ordered clinical outcomes using baseline measures as candidate predictors. Fifteen explanatory variables were used, including clinical symptoms, cognitive functioning, and electrophysiological measures [amplitudes and latencies of P300, duration mismatch negativity (dMMN), and frequency MMN (fMMN)]. Results: Reduced baseline dMMN amplitude, greater severity of attenuated positive symptoms indexed by unusual thought content, and poor cognitive functioning associated with daily living, assessed using the Schizophrenia Cognition Rating Scale, were independently associated with worse ordered clinical outcomes. Discussion: These findings suggest that future clinical trajectories of ARMS can be predicted by multimodal factors spanning neurophysiological, clinical, and functional domains. Early stratification of individuals at the ARMS stage may contribute to the development of personalized and stage-appropriate intervention strategies tailored to subsequent clinical outcomes.

Indexed as

at-risk mental statecognitionevent-related potentialmismatch negativitypredictionpsychosisschizophrenia

Identifiers

PMID42290980
PMCPMC13253625

What Socratic holds

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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 Socratic graph.