A predictive model for readmission within 1-year post-discharge in patients with schizophrenia.

BACKGROUND: Schizophrenia is a pervasive and severe mental disorder characterized by significant disability and high rates of recurrence. The persistently high rates of readmission after discharge present a serious challenge and source of stress in treating this population. Early identification of this risk is critical for implementing targeted interventions. The present study aimed to develop an easy-to-use predictive instrument for identifying the risk of readmission within 1-year post-discharge among schizophrenia patients in China. METHODS: A prediction model, based on static factors, was developed using data from 247 schizophrenia inpatients admitted to the Mental Health Center in Wuxi, China, from July 1 to December 31, 2020. For internal validation, an additional 106 patients were included. Multivariate Cox regression was applied to identify independent predictors and to create a nomogram for predicting the likelihood of readmission within 1-year post-discharge. The model's performance in terms of discrimination and calibration was evaluated using bootstrapping with 1000 resamples. RESULTS: Multivariate cox regression demonstrated that involuntary admission (adjusted hazard ratio [aHR] 4.35, 95% confidence interval [CI] 2.13-8.86), repeat admissions (aHR 3.49, 95% CI 2.08-5.85), the prescription of antipsychotic polypharmacy (aHR 2.16, 95% CI 1.34-3.48), and a course of disease ≥ 20 years (aHR 1.80, 95% CI 1.04-3.12) were independent predictors for the readmission of schizophrenia patients within 1-year post-discharge. The area under the curve (AUC) and concordance index (C-index) of the nomogram constructed from these four factors were 0.820 and 0.780 in the training set, and 0.846 and 0.796 for the validation set, respectively. Furthermore, the calibration curves of the nomogram for both the training and validation sets closely approximated the ideal diagonal line. Additionally, decision curve analyses (DCAs) demonstrated a significantly better net benefit with this model. CONCLUSIONS: A nomogram, developed using pre-discharge static factors, was designed to predict the likelihood of readmission within 1-year post-discharge for patients with schizophrenia. This tool may offer clinicians an accurate and effective way for the timely prediction and early management of psychiatric readmissions.

Gender differences among long-stay inpatients with schizophrenia in China: A cross-sectional study.

Objective: We sought to examine the independent correlates of long-term hospitalization in a sample of Chinese inpatients with schizophrenia (SCZ) from a gender-based perspective. Methods: This was a cross-sectional study that was carried out in a tertiary psychiatric hospital. All adult inpatients in this hospital were screened from January to March 2020, 251 of whom were identified as long-stay inpatients with SCZ (LSIS) and 224 as short-stay inpatients with SCZ (SSIS). Demographic and clinical information of the two groups was collected through medical records, scale assessments and interviews. Gender differences were analyzed, and independent correlates of long-stay between genders were explored by logistic regression analyses. Results: Compared to SSIS, greater proportions of LSIS patients were male (64.1%), single (82.1%), unemployed (81.7%) and had no family caregivers (54.2%). For LSIS per se, proportionally more males were single (88.8%), had no family caregiver (65.8%), had concomitant physical disease (65.2%) and had a history of hazardous behavior (27.3%) than their female counterparts. For females, the top independent risk factors for a long stay included poor functioning (OR = 5.9, 95% CI: 2.9-12.0), older age (OR = 4.3, 95% CI: 2.1-9.1) and being single (OR = 3.9, 95% CI: 1.8-8.4). Similar to women, both older age (OR = 5.3, 95% CI: 2.5-11.2) and poor functioning (OR = 4.0, 95% CI: 2.1-7.9) were also independent factors for long-term hospitalization of male patients; however, having no family caregiver (OR = 10.2, 95% CI: 4.6-22.6) was the primary risk factor for men. Conclusions: Both clinical and nonclinical factors play important roles in long-term hospitalization in Chinese patients with schizophrenia. There are overlaps and distinctions across genders with respect to the independent factors of long stays. These findings provide clues for developing better service strategies for this population, and highlight the importance of paying attention to gender differences in further research in this field.