Evidence map›Paper›PMID 35689554›Full record

ArticleSchizophrenia bulletin2022

Dynamic Patterns of Symptoms and Functioning in Predicting Deliberate Self-harm in Patients with First-Episode Schizophrenia-Spectrum Disorders Over 3 Years.

Ting Yat Wong, Sherry Kit Wa Chan, Charlton Cheung, Christy Lai Ming Hui, Yi Nam Suen, Wing Chung Chang, Edwin Ho Ming Lee, Eric Yu Hai Chen

Abstract read
In one paragraph

Article in Schizophrenia bulletin, 2022. 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. Article
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

8 authors.

Ting Yat WongDepartment of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.ORCID 0000-0003-4356-1978
Sherry Kit Wa ChanDepartment of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.ORCID 0000-0003-2712-5826
Charlton CheungDepartment of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.
Christy Lai Ming HuiDepartment of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.
Yi Nam SuenDepartment of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.ORCID 0000-0003-2766-8476
Wing Chung ChangDepartment of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.ORCID 0000-0002-3581-8895
Edwin Ho Ming LeeDepartment of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.
Eric Yu Hai ChenDepartment of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPatients with schizophrenia have a significant risk of self-harm. We aimed to explore the dynamic relationship between symptomatology, functioning and deliberate self-harm (DSH) and evaluate the feasibility of developing a self-harm risk prediction tool for patients with first-episode schizophrenia (FES).

methodsPatients with FES (n = 1234) were followed up for 36 months. Symptomatology, functioning, treatment adherence and self-harm information were obtained monthly over the follow-up period. A time-varying vector autoregressive (VAR) model was used to study the contribution of clinical variables to self-harm over the 36th month. Random forest models for self-harm were established to classify the individuals with self-harm and predict future self-harm events.

resultsOver a 36-month period, 187 patients with FES had one or more self-harm events. The depressive symptoms contributed the most to self-harm prediction during the first year, while the importance of positive psychotic symptoms increased from the second year onwards. The random forest model with all static information and symptom instability achieved a good area under the receiver operating characteristic curve (AUROC = 0.77 ± 0.023) for identifying patients with DSH. With a sliding window analysis, the averaged AUROC of predicting a self-event was 0.65 ± 0.102 (ranging from 0.54 to 0.78) with the best model being 6-month predicted future 6-month self-harm for month 11-23 (AUROC = 0.7).

conclusionsResults highlight the importance of the dynamic relationship of depressive and positive psychotic symptoms with self-harm and the possibility of self-harm prediction in FES with longitudinal clinical data.

Indexed as

Psychotic DisordersSchizophreniaSelf-Injurious BehaviorHumansRisk Factorsfirst-episode schizophrenialongitudinalprediction modelself-harmsymptom instability

Identifiers

PMID35689554
PMCPMC9434452

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