Louise Ghesquière, Emmanuel Bujold, Eric Dubé, Nils Chaillet
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We calculated the detection rate (DR or sensitivity), the false positive rate (FPR or 1 - specificity), the positive (PPV) and negative (NPV) predictive values of each model for PE and for preterm PE using receiver operator characteristic (ROC) curves.</p><p><strong>Results: </strong> We used 130,939 deliveries including 4,635 (3.5%) cases of PE and 823 (0.6%) cases of preterm PE. The ACOG model had a DR of 43.6% for PE and 50.3% for preterm PE with FPR of 15.6%; the NICE model had a DR of 36.2% for PE and 41.3% for preterm PE with FPR of 12.8%; and the SOGC model had a DR of 49.1% for PE and 51.6% for preterm PE with FPR of 22.2%. The PPV for PE of the ACOG (9.3%) and NICE (9.4%) models were both superior than the SOGC model (7.6%; <i>p</i> < 0.001), with a similar trend for the PPV for preterm PE (1.9 vs. 1.9 vs. 1.4%, respectively; <i>p</i> < 0.01). The area under the ROC curves suggested that the ACOG model is superior to the NICE for the prediction of PE and preterm PE and superior to the SOGC models for the prediction of preterm PE (all with <i>p</i> < 0.001).</p><p><strong>Conclusion: </strong> The current ACOG factor-based model for the prediction of PE and preterm PE, without considering race, is superior to the NICE and SOGC models.</p><p><strong>Key points: </strong>· Clinical factor-based model can predict PE in approximately 44% of the cases for a 16% false positive.. · The ACOG model is superior to the NICE and SOGC models to predict PE.. · Clinical factor-based models are better to predict PE in parous than in nulliparous..</p>","PeriodicalId":7584,"journal":{"name":"American journal of perinatology","volume":" ","pages":"1930-1935"},"PeriodicalIF":1.5000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of National Factor-Based Models for Preeclampsia Screening.\",\"authors\":\"Louise Ghesquière, Emmanuel Bujold, Eric Dubé, Nils Chaillet\",\"doi\":\"10.1055/s-0044-1782676\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong> This study aimed to compare the predictive values of the American College of Obstetricians and Gynecologists (ACOG), the National Institute for Health and Care Excellence (NICE), and the Society of Obstetricians and Gynecologists of Canada (SOGC) factor-based models for preeclampsia (PE) screening.</p><p><strong>Study design: </strong> We conducted a secondary analysis of maternal and birth data from 32 hospitals. For each delivery, we calculated the risk of PE according to the ACOG, the NICE, and the SOGC models. Our primary outcomes were PE and preterm PE (PE combined with preterm birth) using the ACOG criteria. We calculated the detection rate (DR or sensitivity), the false positive rate (FPR or 1 - specificity), the positive (PPV) and negative (NPV) predictive values of each model for PE and for preterm PE using receiver operator characteristic (ROC) curves.</p><p><strong>Results: </strong> We used 130,939 deliveries including 4,635 (3.5%) cases of PE and 823 (0.6%) cases of preterm PE. The ACOG model had a DR of 43.6% for PE and 50.3% for preterm PE with FPR of 15.6%; the NICE model had a DR of 36.2% for PE and 41.3% for preterm PE with FPR of 12.8%; and the SOGC model had a DR of 49.1% for PE and 51.6% for preterm PE with FPR of 22.2%. 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引用次数: 0
摘要
研究目的本研究旨在比较美国妇产科医师学会 (ACOG)、美国国家健康与护理卓越研究所 (NICE) 和加拿大妇产科医师学会 (SOGC) 基于因素的子痫前期 (PE) 筛查模型的预测值：我们对 32 家医院的产妇和新生儿数据进行了二次分析。对于每次分娩，我们都根据 ACOG、NICE 和 SOGC 模型计算 PE 风险。根据 ACOG 标准，我们的主要结果是 PE 和早产 PE（PE 合并早产）。我们使用接收器操作员特征曲线（ROC）计算了每个模型对 PE 和早产 PE 的检出率（DR 或灵敏度）、假阳性率（FPR 或 1 - 特异性）、阳性预测值（PPV）和阴性预测值（NPV）：我们使用了 130,939 例分娩，其中包括 4,635 例 PE（3.5%）和 823 例早产 PE（0.6%）。ACOG 模型的 PE DR 为 43.6%，早产 PE DR 为 50.3%，FPR 为 15.6%；NICE 模型的 PE DR 为 36.2%，早产 PE DR 为 41.3%，FPR 为 12.8%；SOGC 模型的 PE DR 为 49.1%，早产 PE DR 为 51.6%，FPR 为 22.2%。ACOG 模型（9.3%）和 NICE 模型（9.4%）的 PE PPV 均优于 SOGC 模型（7.6%；p p p p 结论：在不考虑种族因素的情况下，目前基于 ACOG 因素的 PE 和早产儿 PE 预测模型优于 NICE 和 SOGC 模型：- 基于临床因素的模型可预测约 44% 的 PE 病例，假阳性率为 16%。- 在预测 PE 方面，ACOG 模型优于 NICE 和 SOGC 模型。- 基于临床因素的模型在预测准妈妈PE方面优于无痛分娩。
Comparison of National Factor-Based Models for Preeclampsia Screening.
Objective: This study aimed to compare the predictive values of the American College of Obstetricians and Gynecologists (ACOG), the National Institute for Health and Care Excellence (NICE), and the Society of Obstetricians and Gynecologists of Canada (SOGC) factor-based models for preeclampsia (PE) screening.
Study design: We conducted a secondary analysis of maternal and birth data from 32 hospitals. For each delivery, we calculated the risk of PE according to the ACOG, the NICE, and the SOGC models. Our primary outcomes were PE and preterm PE (PE combined with preterm birth) using the ACOG criteria. We calculated the detection rate (DR or sensitivity), the false positive rate (FPR or 1 - specificity), the positive (PPV) and negative (NPV) predictive values of each model for PE and for preterm PE using receiver operator characteristic (ROC) curves.
Results: We used 130,939 deliveries including 4,635 (3.5%) cases of PE and 823 (0.6%) cases of preterm PE. The ACOG model had a DR of 43.6% for PE and 50.3% for preterm PE with FPR of 15.6%; the NICE model had a DR of 36.2% for PE and 41.3% for preterm PE with FPR of 12.8%; and the SOGC model had a DR of 49.1% for PE and 51.6% for preterm PE with FPR of 22.2%. The PPV for PE of the ACOG (9.3%) and NICE (9.4%) models were both superior than the SOGC model (7.6%; p < 0.001), with a similar trend for the PPV for preterm PE (1.9 vs. 1.9 vs. 1.4%, respectively; p < 0.01). The area under the ROC curves suggested that the ACOG model is superior to the NICE for the prediction of PE and preterm PE and superior to the SOGC models for the prediction of preterm PE (all with p < 0.001).
Conclusion: The current ACOG factor-based model for the prediction of PE and preterm PE, without considering race, is superior to the NICE and SOGC models.
Key points: · Clinical factor-based model can predict PE in approximately 44% of the cases for a 16% false positive.. · The ACOG model is superior to the NICE and SOGC models to predict PE.. · Clinical factor-based models are better to predict PE in parous than in nulliparous..
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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