在精神分裂症患者退院后1年内再入院的预测模型
Mingru Hou1, Yuqing Wu2, Jianhua Xue3
1Department of General Psychiatry, The Affiliated Mental Health Center of Jiangnan University, Wuxi, Jiangsu, 214151, China.
BMC psychiatry
|August 22, 2024
概括
一个新的名图预测了使用非自愿入院和先前入院等因素在一年内预测精神分裂症再入院风险. 这种工具有助于早期干预精神分裂症患者,改善治疗结果.
科学领域:
- 精神病学和心理健康研究研究
- 临床预测建模临床预测建模
- 公共卫生 公共卫生
背景情况:
- 精神分裂症是一种严重的精神障碍,复发率很高,这给治疗带来了重大挑战.
- 释放后高回收率需要针对性干预的早期风险识别.
- 开发可访问的预测工具对于管理精神分裂症患者再入院至关重要.
研究的目的:
- 开发一种易于使用的预测工具,用于识别在中国退院后一年内有再入院风险的精神分裂症患者.
- 基于静态的,排放前的因素,创建一个名录来预测1年的再接收概率.
主要方法:
- 使用来自中国无锡247名精神分裂症住院患者的数据开发了一个预测模型.
- 多变量考克斯回归确定了重收的独立预测因素.
- 通过使用106名额外的患者构建并内部验证了一个名图.
主要成果:
- 非自愿入院,重复入院,抗精神病药物多药和疾病持续时间 (≥20年) 是重新入院的重要预测因素.
- 该名录显示了良好的区分 (AUC 0.820-0.846) 和训练和验证组中的校准.
- 决策曲线分析证实了该模型的临床实用性和净益处.
结论:
- 使用出院前静态因子的诺莫图准确预测精神分裂症患者的一年再入院风险.
- 这种预测工具可以帮助临床医生及时评估风险,及早管理精神病学再入院.
- 开发的名录为改善退院后护理和降低再接收率提供了有效的策略.
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