Cardiovascular comorbidities in Chinese inpatients with schizophrenia spectrum disorders.

IF 3 Q2 PSYCHIATRY Schizophrenia (Heidelberg, Germany) Pub Date : 2025-02-19 DOI:10.1038/s41537-025-00576-3
Zhe Dong, Gang Wu, Hongbing Liu, Song Chen, Bin Bi, Fangfang Zhang, Yi Yin, Wei Qu, Baopeng Tian, Fude Yang, Alice Kochunov, Peter Kochunov, Shengmei Ban, Yang Zhao, L Elliot Hong, Yunlong Tan
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Abstract

Cardiovascular diseases (CVDs) are the leading cause of premature mortality in patients with schizophrenia spectrum disorders (SSDs). However, the detailed categorization of these conditions remains insufficiently explored. This study aims to identify CVDs comorbidity patterns among inpatients with SSDs and to investigate associated factors. Electronic medical records (EMRs) data from three neuropsychiatric hospitals (2015-2023) in China was conducted. Comorbidity patterns were revealed through latent class analysis (LCA), and multinomial logit analysis were utilized to evaluate the effect of factors on these patterns, calculating odds ratios (ORs) and 95% confidence intervals (CIs). Among the 2830 inpatients with SSD, four distinct comorbidity patterns were identified based on their dominant characteristics: low-risk CVDs (47.86%), primary hypertension (30.15%), heart failure (12.99%), and cardiac valve and vascular disorders (8.99%). Compared to the low-risk CVD group, male patients demonstrated a higher probability of primary hypertension (OR = 1.15) and heart failure (OR = 5.36). Significant associations were observed between comorbid CVDs and the use of typical antipsychotics, atypical antipsychotics, anxiolytics and sedatives, antidepressants, and mood stabilizers. Notably, perphenazine (OR = 22.06) and chlorpromazine hydrochloride (OR = 7.09) were strongly linked to comorbid heart failure. Among Chinese patients with SSDs, four distinct CVD comorbidity patterns were identified, with hypertension and heart failure displaying strong specificity. Variations in demographic characteristics and psychotropic medication use provide valuable insights for treatment and management.

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