External Validation of the fullPIERS Risk Prediction Model in a U.S. Cohort of Individuals with Preeclampsia.

IF 1.5 4区 医学 Q3 OBSTETRICS & GYNECOLOGY
Danielle Long, Kari Flicker, Maya Vishnia, Madeleine Wright, Matilda Francis, Kenyone S King, Lauren Gilgannon, Aref Rastegar, Neha Gupta, Rohini Kousalya Siva, Lea Nehme, Tetsuya Kawakita
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引用次数: 0

Abstract

Objective:  This study aimed to externally validate the Preeclampsia Integrated Estimate of Risk (fullPIERS) risk prediction model in a cohort of pregnant individuals with preeclampsia in the United States.

Study design:  This was a retrospective study of individuals with preeclampsia who delivered at 22 weeks or greater from January 1, 2010, to December 31, 2020. The primary outcome was a composite of maternal mortality or other serious complications of preeclampsia occurring within 48 hours of admission. We calculated the probability of the composite outcome using the fullPIERS prediction model based on data available within 12 hours of admission, including gestational age, chest pain or dyspnea, serum creatinine levels, platelet count, aspartate transaminase levels, and oxygen saturation. We assessed the model performance using the area under the curve (AUC) of the receiver operating characteristic curve. The optimal cutoff point was determined using Liu's method. A calibration plot was used to evaluate the model's goodness-of-fit.

Results:  Among 1,510 individuals with preeclampsia, 82 (5.4%) experienced the composite outcome within 48 hours. The fullPIERS model achieved an AUC of 0.80 (95% confidence interval [CI]: 0.75-0.86). The predicted probability for individuals with the composite outcome (median: 18.8%; interquartile range: 2.9-59.1) was significantly higher than those without the outcome (median: 0.9%; interquartile range: 0.4-2.7). The optimal cutoff point of 5.5% yielded a sensitivity of 70.7% (95% CI: 59.6-80.3), a specificity of 85% (95% CI: 82.7-86.5), a positive likelihood ratio of 4.6 (95% CI: 3.8-5.5), and an odds ratio of 13.3 (95% CI: 8.1-21.8). The calibration plot indicated that the model underestimated risk when the predicted probability was below 1% and overestimated risk when the predicted probability exceeded 5%.

Conclusion:  The fullPIERS model demonstrated good discrimination in this U.S. cohort of individuals with preeclampsia, suggesting it may be a useful tool for health care providers to identify individuals at risk for severe complications.

Key points: · The fullPIERS risk prediction model has not been validated in a U.S.

Cohort: . · The model showed good predictive accuracy (AUC: 0.80) for severe maternal complications but had calibration issues at extreme-risk levels.. · This study confirms the fullPIERS model's applicability in the United States..

在美国子痫前期患者队列中对 fullPIERS 风险预测模型进行外部验证。
目的: 在美国子痫前期孕妇队列中对全PIERS风险预测模型进行外部验证:在美国子痫前期孕妇队列中对全PIERS风险预测模型进行外部验证:这是一项回顾性研究,研究对象为 2010 年 1 月 1 日至 2020 年 12 月 31 日期间 22 周或以上分娩的子痫前期患者。主要研究结果是入院 48 小时内发生的产妇死亡或子痫前期其他严重并发症的综合结果。我们根据入院 12 小时内的可用数据,包括孕龄、胸痛或呼吸困难、血清肌酐水平、血小板计数、天门冬氨酸转氨酶水平和血氧饱和度,使用全PIERS 预测模型计算了综合结果的概率。我们使用接收者操作特征曲线的曲线下面积(AUC)来评估模型的性能。采用刘氏方法确定了最佳截断点。校准图用于评估模型的拟合优度:结果:在 1510 名子痫前期患者中,82 人(5.4%)在 48 小时内出现了综合结果。全PIERS模型的AUC为0.80(95%置信区间:0.75-0.86)。出现综合结果者的预测概率(中位数:18.8%;四分位数间距:2.9-59.1)明显高于未出现综合结果者(中位数:0.9%;四分位数间距:0.4-2.7)。最佳临界点为 5.5%,灵敏度为 70.7%(95% CI:59.6-80.3),特异度为 85%(95% CI:82.7-86.5),阳性似然比为 4.6(95% CI:3.8-5.5),几率比为 13.3(95% CI:8.1-21.8)。校准图显示,当预测概率低于 1%时,模型低估了风险,而当预测概率超过 5%时,模型高估了风险:全PIERS模型在这个美国子痫前期患者队列中表现出良好的识别能力,表明它可能是医疗服务提供者识别有严重并发症风险的患者的有用工具。
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来源期刊
American journal of perinatology
American journal of perinatology 医学-妇产科学
CiteScore
5.90
自引率
0.00%
发文量
302
审稿时长
4-8 weeks
期刊介绍: The American Journal of Perinatology is an international, peer-reviewed, and indexed journal publishing 14 issues a year dealing with original research and topical reviews. It is the definitive forum for specialists in obstetrics, neonatology, perinatology, and maternal/fetal medicine, with emphasis on bridging the different fields. The focus is primarily on clinical and translational research, clinical and technical advances in diagnosis, monitoring, and treatment as well as evidence-based reviews. Topics of interest include epidemiology, diagnosis, prevention, and management of maternal, fetal, and neonatal diseases. Manuscripts on new technology, NICU set-ups, and nursing topics are published to provide a broad survey of important issues in this field. All articles undergo rigorous peer review, with web-based submission, expedited turn-around, and availability of electronic publication. The American Journal of Perinatology is accompanied by AJP Reports - an Open Access journal for case reports in neonatology and maternal/fetal medicine.
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