Evidence map›Paper›PMID 42711408›Full record

ArticleMolecular psychiatry2026

Dynamic, differentiated clinical trajectories and prediction in clinical high risk for psychosis.

Yuxuan Xiong, Guisen Wu, Xiaochen Tang, Yiyi Yang, Dan Zhang, Wensi Zheng, Yanyan Wei, Lihua Xu, Huiru Cui, Haichun Liu and 4 more

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

14 authors.

Yuxuan Xiong *Neuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Guisen Wu *Neuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Xiaochen TangNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Yiyi YangNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Dan ZhangNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Wensi ZhengNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Yanyan WeiNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Lihua XuNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Huiru CuiNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Haichun LiuDepartment of Automation, Shanghai Jiao Tong University, Shanghai, PR China.
Yingying TangNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
Chunbo LiNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.ORCID http://orcid.org/0009-0000-5029-069X
Jijun WangNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China. jijunwang27@163.com.ORCID http://orcid.org/0009-0009-7874-4898
Tianhong ZhangNeuromodulation Center, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China. zhang_tianhong@126.com.ORCID http://orcid.org/0000-0002-5379-7119

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical subtypes of individuals at clinical high risk for psychosis (CHR), classified by baseline symptoms and cognitive performance, may follow distinct trajectories of symptom progression and functional outcomes. Baseline symptom, cognitive and EEG data were collected from 204 CHR individuals aged 13-38 years, who subsequently completed clinical assessments at 2 months, 1 year, and 2 years. Although baseline positive symptom scores and highest past-year global functioning did not differ significantly, the subtypes demonstrated divergent progression patterns across follow-ups. Baseline cognitive performance exerted sustained influence over subsequent assessments, with visuospatial learning and working memory showing significant long-term effects on positive symptoms or global functioning, highlighting them as core cognitive domains with longitudinal, cross-subtype impact on CHR progression. Brain network features also contributed to long-term outcomes. The involvement of microstate D was sustained over time, with its occurrence linked to functional outcomes in the most impaired subtype and its coverage associated with positive symptom trajectories in the moderately impaired subtype. We further constructed a predictive model incorporating the interaction between microstate D and subtype that effectively identified individuals who converted to psychosis, underscoring its potential as a dynamic biomarker for more precise CHR clinical profiles.

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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.