开发风险预测模型,用于在双相情感障碍中要求计划外精神病重收治疗
Xiao Liu1, Xiao-Yu Wang1, Bing-Zhe Chen1
1Department of psychiatry, The Third People's Hospital of Tianshui, No. 17 Jingbiao Road, Tianshui City, Gansu Province, China.
Scientific reports
|September 29, 2025
概括
这项研究开发了一种对双相情感障碍 (BD) 未计划的精神病再入院的预测模型. 男性性别,慢性病和侵略性得分增加了风险,而年龄较大降低了风险.
科学领域:
- 精神病学和心理健康 精神病学和心理健康
- 医疗保健服务研究 医疗服务研究
背景情况:
- 双相情感障碍 (BD) 的高再录取率构成了重大的公共卫生和经济挑战.
- 现有的研究往往侧重于再接收因素,而不是BD的预测建模.
- 需要有效的工具来识别高风险的非计划性精神病学再接收 (RUPR) 患者.
研究的目的:
- 开发和验证基于名录的预测模型,用于双相情感障碍 (BD) 患者的1年计划外精神病再入院 (RUPR).
- 确定与BD再接收风险相关的关键人口和临床因素.
- 为简化 BD 管理和识别高风险个人提供一个工具.
主要方法:
- 一项回顾性研究从2021年1月到2023年11月对448名患有BD的住院患者进行了查.
- 收集的数据包括人口统计数据,并发性慢性身体疾病 (CSD),社会支持评级表 (SSRS),洞察力和治疗态度调查问卷 (ITAQ) 和修改的公开攻击性表 (MOAS) 评分.
- 用多变量逻辑回归和名ogram分析来构建预测模型.
主要成果:
- 在重新入院和未重新入院患者之间观察到性别,年龄,CSD,伴侣身份,SSRS,ITAQ和MOAS分数的显著差异.
- 男性性别,并发性CSD,更高的MOAS分数,以及较低的SSRS和ITAQ分数与再接收风险增加有关.
- 年龄>60岁被发现降低了再接收风险. 该模型实现了0.85的AUC,并显示出很好的适应性 (霍斯默-莱梅肖测试P=0.63).
结论:
- 开发的基于名录的预测模型有效地识别了患有双相情感障碍的高风险非计划性精神病再入院的患者.
- 关键预测因素包括男性性别,并发性慢性体质疾病,侵略程度,社会支持和治疗态度.
- 这种模型可以帮助临床医生在双相情感障碍患者的积极管理和资源配置.
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