Clinical and Imaging Data-Based Model for Predicting Reversible Posterior Leukoencephalopathy Syndrome (RPLS) in Pregnant Women With Severe Preeclampsia or Eclampsia and Analysis of Perinatal Outcomes.

Abstract

Objective This study aimed to investigate the risk factors of reversible posterior leukoencephalopathy syndrome (RPLS) in pregnant women with severe preeclampsia or eclampsia (SPE/E) based on a predicting model and to analyze the perinatal outcomes. Methods From January 2015 to March 2020, 78 pregnant women data diagnosed with severe preeclampsia or eclampsia with cranial magnetic resonance imaging (MRI) and transcranial Doppler (TCD) screening in Xiangyang No. 1 People's Hospital and Jiangsu Province Hospital of Chinese Medicine were analyzed retrospectively. They were divided into the RPLS group (n = 33) and non-RPLS group (n = 45) based on the MRI results. The general clinical data (blood pressure, BMI, symptoms, and so forth), laboratory examination, TCD results, and perinatal outcomes in the two groups were compared. The risk factors of severe preeclampsia or eclampsia complicated with RPLS were analyzed by multivariate logistic regression. The prediction model and decision curve (DCA) were established according to the clinical-imaging data. Results The univariate analysis showed that poor placental perfusion, hypertension emergency, use of two or more oral antihypertensive drugs, headache, white blood cell (WBC) count, platelet (PLT) count, lactate dehydrogenase (LDH), alanine aminotransferase (ALT), uric acid (UA), serum albumin (ALB), average flow velocity, and resistance index of the posterior cerebral and basilar arteries were significantly different in the RPLS group compared with the non-RPLS group (all P < 0.05). The multivariate logistic regression analysis showed that hypertensive emergency, headache, WBC, PLT, ALT, and average flow velocity of the basilar artery (BAAFV) were the risk factors in the RPLS group. The aforementioned clinical-imaging data modeling (general data model, laboratory examination model, TCD model, and combined model) showed that the combined model predicted RPLS better. DCA also confirmed that the net benefit of the combined model was higher. In addition, the incidence of postpartum hemorrhage, stillbirth, and preterm infants was higher in the RPLS group than in the non-RPLS group (all P < 0.05). Conclusions More postpartum complications were detected in pregnant women with severe preeclampsia or eclampsia complicated with RPLS. Hypertensive emergency, headache, WBC, PLT, ALT, and BAAFV were the important risk factors for RPLS. The combined model had a better effect in predicting RPLS.