精神分裂症患者再入院风险预测模型的系统评价

Risk prediction models for hospital readmission in patients with schizophrenia： a systematic review

中文关键词:  精神分裂症  再入院  预测模型  系统评价

英文关键词:Schizophrenia  Readmission  Prediction models  Systematic review

中文摘要:

      背景 精神分裂症患者再入院率高，是精神卫生领域面临的重要临床挑战与社会负担。近年来，多种针对精神分裂症患者再入院风险预测模型被开发以辅助临床决策，但其预测性能及临床适用性仍有待全面评估。目的 系统评价精神分裂症患者再入院风险预测模型，为开发性能优良且适用性高的精神分裂症患者再入院风险预测模型提供参考。方法 于2025年7月5日，系统检索PubMed、Embase、Cochrane Library、Web of Science、CINAHL、中国知网、中国生物医学文献数据库、万方数据库和维普数据库，收集关于精神分裂症患者再入院风险预测模型的文献。检索时限为建库至2025年7月1日。由两名研究者独立筛选文献、提取数据，并对纳入文献的偏倚风险与模型适用性进行评价。结果 本研究共纳入9篇文献，涉及18个精神分裂症患者再入院风险预测模型。其中，4个模型报告了建模的受试者工作特征（ROC）曲线下面积（AUC），范围为0.734~0.820；16个模型报告了内部验证的AUC（0.642~0.879），1个模型报告了外部验证的AUC（0.841）。核心预测因子包括病程和抗精神病药物联用。所有纳入文献的偏倚风险评价结果均为高风险。结论 精神分裂症患者再入院风险预测模型的研究尚处于探索阶段，模型预测性能良好，但偏倚风险较高，对模型预测性能的评估不足。

英文摘要:

      Background Individuals with schizophrenia are prone to higher rates of hospital readmission， presenting significant clinical challenges and imposing considerable social burdens within the mental health domain. In recent years， various risk prediction models have been developed to forecast readmission in patients with schizophrenia and support clinical decision-making， but their predictive performance and clinical applicability require comprehensive evaluation.Objective To systematically evaluate the risk prediction models for readmission in patients with schizophrenia， so as to provide insights for the development of high-performance and highly applicable readmission risk prediction models for patients with schizophrenia.Methods On July 5， 2025， a systematic literature search was conducted across multiple electronic databases， including PubMed， Embase， Cochrane Library， Web of Science， CINAHL， CNKI， China Biomedical Literature Database， Wanfang Database， and VIP Database， to identify risk prediction models for readmission in patients with schizophrenia. The search period was from the establishment of the databases to July 1， 2025. Two researchers independently performed literature screening， data extraction， risk of bias assessment， and applicability assessment.Results A total of 9 studies were included in this review， encompassing 18 risk prediction models for readmission in patients with schizophrenia. Among them， 4 models reported the area under the receiver operating characteristic （ROC） curve （AUC）， ranging from 0.734 to 0.820， 16 models provided AUC values of 0.642–0.879 for internal validation， and 1 model demonstrated an AUC of 0.841 for external validation. Key predictors included disease duration and the concomitant therapy of antipsychotic medications. The risk of bias was assessed as "high" in all included studies.Conclusion The development of risk prediction models for readmission in patients with schizophrenia remains in an exploratory stage. Although the model exhibits favorable predictive performance， it is associated with a high risk of bias and insufficient performance evaluation.