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分娩住院后严重孕产妇发病率和死亡率预测模型。

A Prediction Model for Severe Maternal Morbidity and Mortality After Delivery Hospitalization.

机构信息

Department 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.

出版信息

Obstet Gynecol. 2023 Sep 1;142(3):585-593. doi: 10.1097/AOG.0000000000005281. Epub 2023 Aug 3.

Abstract

OBJECTIVE

To develop a risk stratification model for severe maternal morbidity (SMM) or mortality after the delivery hospitalization based on information available at the time of hospital discharge.

METHODS

This population-based cohort study included all pregnancies among Ohio residents with Medicaid insurance from 2012 to 2017. Pregnant individuals were identified using linked live birth and fetal death records and Medicaid claims data. Inclusion was restricted to those with continuous postpartum Medicaid enrollment and delivery at 20 or more weeks of gestation. The primary outcome of the study was SMM or mortality after the delivery hospitalization and was assessed up to 42 days postpartum and up to 1 year postpartum separately. Variables considered for the model included patient-, obstetric health care professional-, and system-level data available in vital records or Medicaid claims data. Parsimonious models were created with logistic regression and were internally validated. Receiver operating characteristic curves were used to evaluate model performance, and model calibration was assessed.

RESULTS

There were 343,842 pregnant individuals who met inclusion criteria with continuous Medicaid enrollment through 42 days postpartum and 287,513 with continuous enrollment through 1 year. After delivery hospitalization discharge, the incidence of SMM or mortality was 140.5 per 10,000 pregnancies through 42 days of delivery and 330.7 per 10,000 pregnancies through 1 year postpartum. The final model predicting SMM or mortality through 42 days postpartum included maternal prepregnancy body mass index, age, gestational age at delivery, mode of delivery, chorioamnionitis, and maternal diagnosis of cardiac disease, preeclampsia or gestational hypertension, or a mental health condition. Similar variables were included in the model predicting SMM or mortality through 365 days with chronic hypertension, pregestational diabetes, and illicit substance use added and chorioamnionitis removed. Both models demonstrated moderate prediction (area under the curve [AUC] 0.77, 95% CI 0.76-0.78 for 42-day model; AUC 0.72, 95% CI 0.71-0.73 for the 1-year model) and good calibration.

CONCLUSION

A prediction model for SMM or mortality up to 1 year postpartum was created and internally validated with information available to health care professionals at the time of hospital discharge. The utility of this model for patient counseling and strategies to optimize postpartum care for high-risk individuals will require further evaluation.

摘要

目的

基于出院时可获得的信息,为产后住院期间发生严重产妇发病率(SMM)或死亡率开发风险分层模型。

方法

本基于人群的队列研究纳入了 2012 年至 2017 年期间俄亥俄州居民中接受医疗补助保险的所有妊娠。使用活产和胎儿死亡记录以及医疗补助索赔数据来识别孕妇。纳入标准为产后连续接受医疗补助和妊娠 20 周或以上的分娩。本研究的主要结局是产后住院期间发生的 SMM 或死亡率,并分别在产后 42 天和产后 1 年进行评估。用于模型的变量包括患者、产科医疗保健专业人员和系统层面的在生命记录或医疗补助索赔数据中可用的信息。使用逻辑回归创建简约模型,并进行内部验证。使用接收者操作特征曲线评估模型性能,并评估模型校准度。

结果

有 343842 名孕妇符合纳入标准,其中 343842 名孕妇在产后 42 天内连续接受医疗补助,287513 名孕妇在产后 1 年内连续接受医疗补助。产后住院出院后,42 天内 SMM 或死亡率为每 10000 例妊娠 140.5 例,产后 1 年内 SMM 或死亡率为每 10000 例妊娠 330.7 例。预测产后 42 天内 SMM 或死亡率的最终模型包括产妇孕前体重指数、年龄、分娩时的孕周、分娩方式、绒毛膜羊膜炎以及产妇心脏病、子痫前期或妊娠期高血压或精神健康状况的诊断。在预测产后 365 天内 SMM 或死亡率的模型中,添加了慢性高血压、孕前糖尿病和非法药物使用,去除了绒毛膜羊膜炎,并包含了相似的变量。两个模型均显示出中度预测能力(42 天模型的曲线下面积 [AUC] 为 0.77,95%CI 为 0.76-0.78;1 年模型的 AUC 为 0.72,95%CI 为 0.71-0.73)和良好的校准度。

结论

利用出院时医疗保健专业人员可获得的信息,为产后 1 年内发生 SMM 或死亡率的情况创建了预测模型,并进行了内部验证。该模型用于患者咨询和优化高危人群产后护理的策略的有效性,需要进一步评估。

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