一个预测模型严重的孕产妇发病率和产后死亡率住院治疗
Heather A Frey1, Robert Ashmead, Alyssa Farmer
1Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, the Ohio Colleges of Medicine Government Resource Center and the Departments of Internal Medicine/Endocrinology and Diabetes and Metabolism, The Ohio State University, and the Bureau of Maternal, Child and Family Health, Ohio Department of Health, Columbus, Ohio.
Obstetrics and gynecology
|August 3, 2023
概括
一个新的模型使用出院数据预测产后严重的孕产妇发病率或死亡率. 该工具有助于识别高风险个体,以改善产后护理策略.
科学领域:
- 孕产妇健康 孕产妇健康
- 公共卫生 公共卫生
- 医疗保健服务研究 医疗服务研究
背景情况:
- 严重的孕产妇发病率和死亡率 (SMM) 构成了重大的公共卫生挑战.
- 风险分层模型对于识别高风险怀孕和优化产后护理至关重要.
研究的目的:
- 开发和验证SMM或死亡率的风险分层模型.
- 该模型利用了医院出院时可用的信息.
主要方法:
- 俄俄州医疗补助计划入学者的基于人口的队列研究 (2012-2017年).
- 使用了相关的出生/胎儿死亡记录和医疗补助申请数据.
- 后勤回归模型被开发和内部验证.
主要成果:
- SMM的发病率或死亡率是140.5/10,000通过42天和330.7/10,000通过1年产后.
- 模型包括BMI,年龄,妊娠年龄,分娩方式和先前存在的疾病等因素.
- 两种模型都显示了适度的预测性能 (AUC 0.77和0.72) 和良好的校准.
结论:
- 在出院时可获得产后SMM或死亡率的验证预测模型.
- 这个模型可以为高风险个体提供患者咨询和产后护理优化信息.
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