一个多变量预测模型,以分层分层,对成年性结肠炎患者重新入院90天的风险
Claudia Dziegielewski1, Sarang Gupta2, Julia Lombardi3
1Department of Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada.
预测性结肠炎在出院时重新入院的风险是可能的. 一个模型确定了关键因素,以帮助针对性干预,并减少重症性结肠炎 (UC) 患者的再入院.
科学领域:
- 胃肠病学 胃肠病学
- 医疗保健服务研究 医疗服务研究
- 临床流行病学 临床流行病学
背景情况:
- 性结肠炎 (UC) 患者由于严重的疾病爆发,经常面临重新住院治疗.
- 预测出院后再住院的风险可以使有针对性的门诊护理减少再入院.
研究的目的:
- 开发和验证90天UC相关的再住院风险的预测模型.
- 确定在医院出院时可用的再住院风险的关键预测因素.
主要方法:
- 在2009-2016年期间住院的成年UC患者的回顾性研究.
- 使用人口,临床和卫生服务数据开发的多变量后勤回归模型.
- 模型使用引导重新抽样验证,并对性能指标 (灵敏度,特异性,PPV,NPV) 进行评估.
主要成果:
- 10.9%的UC住院患者在90天内再次住院.
- 重新入院90天的重要预测因素包括男性性别,入院时间和出院时的麻醉药物处方.
- 之前的胃肠科医生咨询具有保护性 (aOR 0.11). 模型表现出良好的歧视 (c-统计值0.78).
结论:
- 在出院时,一组简短的变量可以有效预测UC患者的再住院风险.
- 调查结果表明,有针对性的干预措施有潜力,以缓解再接收率.
- 预测模型的进一步外部验证是有必要的.
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