Oliveira N, Doyle L E, Atlas R O, Jenkins C B, Blitzer M G, Baschat A A
Department of Obstetrics, Gynecology and Reproductive Sciences, University of Maryland School of Medicine, Baltimore, MD, USA.
Ultrasound Obstet Gynecol. 2014 Sep;44(3):286-92. doi: 10.1002/uog.13433. Epub 2014 Aug 7.
To compare disease features in women with pre-eclampsia between those who are correctly identified (true positive) and those who are missed (false negative) when applying first-trimester prediction algorithms for pre-eclampsia to a prospectively enrolled population.
Six first-trimester early (requiring delivery < 34 weeks' gestation) pre-eclampsia algorithms were applied to a prospective cohort of singleton pregnancies enrolled at first-trimester screening. Maternal outcomes, neonatal outcomes and severity parameters for pre-eclampsia were compared between true-positive and false-negative predictions.
Twenty of 2446 (0.8%) women developed early pre-eclampsia, with 65% of these developing severe features and 20% HELLP syndrome. At enrollment, true-positive cases were more likely to be African-American and chronically hypertensive, while false-negative cases were more likely to be Caucasian. At delivery, true-positive cases were more likely to have pre-eclampsia superimposed on hypertension, severely elevated blood pressure and creatinine level > 1.1 mg/dL. False-negative cases were more likely to have HELLP syndrome (all P < 0.05).
In an urban population with a high prevalence of chronic hypertension, patients who are correctly identified by first-trimester screening models are more likely to develop pre-eclampsia superimposed on chronic hypertension with severely elevated blood pressure and evidence of renal failure. In contrast, patients who are missed by these algorithms are more likely to have HELLP syndrome. Further research is needed to confirm these findings and the algorithm adjustments that may be necessary to better predict pre-eclampsia phenotypes.
在一个前瞻性招募的人群中，应用早孕期子痫前期预测算法，比较子痫前期女性中被正确识别（真阳性）和被漏诊（假阴性）者的疾病特征。
将六种早孕期（要求在妊娠<34周分娩）子痫前期算法应用于早孕期筛查时前瞻性招募的单胎妊娠队列。比较真阳性和假阴性预测之间子痫前期的孕产妇结局、新生儿结局和严重程度参数。
2446名女性中有20名（0.8%）发生早发型子痫前期，其中65%出现严重特征，20%出现HELLP综合征。在入组时，真阳性病例更可能是非裔美国人且患有慢性高血压，而假阴性病例更可能是白种人。在分娩时，真阳性病例更可能子痫前期合并高血压、血压严重升高且肌酐水平>1.1mg/dL。假阴性病例更可能出现HELLP综合征（所有P<0.05）。
在慢性高血压患病率较高的城市人群中，通过早孕期筛查模型正确识别的患者更可能发生子痫前期合并慢性高血压，血压严重升高且有肾衰竭证据。相比之下，这些算法漏诊的患者更可能出现HELLP综合征。需要进一步研究来证实这些发现以及为更好地预测子痫前期表型可能需要进行的算法调整。
