Evidence map›Paper›PMID 40787688›Full record

ArticleFrontiers in psychiatry2025

Research on comorbidity characteristics and patterns of hospitalized participants with schizophrenia in China.

Xinru Huang, Ting Zhang, Bin Li, Yahui Meng, Fen Li

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2025. 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

5 authors.

Xinru HuangSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Ting ZhangMedical Affairs Department, Huai'an No.3 People's Hospital, Hui'an, China.
Bin LiEmergency Department, Xuzhou Oriental People's Hospital, Xuzhou, Jiangsu, China.
Yahui MengMedical Affairs Department, Xuzhou Cancer Hospital, Xuzhou, Jiangsu, China.
Fen LiSchool of Management, Xuzhou Medical University, Xuzhou, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Participants with schizophrenia face the dual impacts of mental illness and physical diseases, which significantly affect their clinical prognosis and quality of life. Methods: This study, which is based on multivariate clinical data, using data-driven approaches (statistical analysis and data mining techniques) to systematically characterize the comorbidities landscape of schizophrenia patients identifying key patterns and clinical profiles to inform optimized treatment strategies and health management interventions. Results: It was found that the comorbidity rate among hospitalized schizophrenia participants is notably high in China. Notably, significant variations in comorbidity profiles were identified across diverse demographic and clinical variables, including age, occupational status, marital status, duration of hospital stay, frequency of hospitalizations, and health insurance status. The comorbidities in schizophrenia participants primarily include acute upper respiratory infections (J00-J06), metabolic disorders (E70-E90), hypertension (I10-I15), and diabetes (E1 0-E14). Furthermore, four strongly associated comorbidities patterns were identified: the metabolic-cardiovascular comorbidities cluster, the co-disease cluster of respiratory system infection, gut respiratory symptom cluster, electrolyte imbalance infection trigger cluster were identified. Discussion: The exploration of comorbidity characteristics and patterns in schizophrenia provides a quantifiable tool for enhancing treatment and health management outcomes for participants while also offering a reference for advancing the application of precision medicine in the treatment and management of schizophrenia.

Indexed as

association rule analysiscomorbidity characteristicscomorbidity modehospitalized participantsschizophrenia

Identifiers

PMID40787688
PMCPMC12332748

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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.