Chaparro Alejandra, Monckeberg Maximiliano, Realini Ornella, Hernández Marcela, Param Fernanda, Albers Daniela, Ramírez Valeria, Kusanovic Juan Pedro, Romero Roberto, Rice Gregory, Illanes Sebastián E
Centre for Biomedical and Innovation Research, Department of Periodontology, Faculty of Dentistry, Universidad de Los Andes, Santiago 7620001, Chile.
Department of Obstetrics and Gynecology, Faculty of Medicine, Universidad de Los Andes, Santiago 7620001, Chile.
Diagnostics (Basel). 2021 Apr 7;11(4):661. doi: 10.3390/diagnostics11040661.
Early and innovative diagnostic strategies are required to predict the risk of developing pre-eclampsia (PE). The purpose of this study was to evaluate the performance of gingival crevicular fluid (GCF) placental alkaline phosphatase (PLAP) concentrations to correctly classify women at risk of PE. A prospectively collected, retrospectively stratified cohort study was conducted, with 412 pregnant women recruited at 11-14 weeks of gestation. Physical, obstetrical, and periodontal data were recorded. GCF and blood samples were collected for PLAP determination by ELISA assay. A multiple logistic regression classification model was developed, and the classification efficiency of the model was established. Within the study cohort, 4.3% of pregnancies developed PE. GCF-PLAP concentration was 3- to 6-fold higher than in plasma samples. GCF-PLAP concentrations and systolic blood pressure were greater in women who developed PE ( = 0.015 and < 0.001, respectively). The performance of the multiparametric model that combines GCF-PLAP concentration and the levels of systolic blood pressure (at 11-14 weeks gestation) showed an association of systolic blood pressure and GCF-PLAP concentrations with the likelihood of developing PE (OR:1.07; 95% CI 1.01-1.11; = 0.004 and OR:1.008, 95% CI 1.000-1.015; = 0.034, respectively). The model had a sensitivity of 83%, a specificity of 72%, and positive and negative predictive values of 12% and 99%, respectively. The area under the receiver operating characteristic (AUC-ROC) curve was 0.77 and correctly classified 72% of PE pregnancies. In conclusion, the multivariate classification model developed may be of utility as an aid in identifying pre-symptomatic women who subsequently develop PE.
需要早期且创新的诊断策略来预测发生先兆子痫（PE）的风险。本研究的目的是评估龈沟液（GCF）中胎盘碱性磷酸酶（PLAP）浓度对正确分类有PE风险女性的性能。进行了一项前瞻性收集、回顾性分层的队列研究，招募了412名妊娠11 - 14周的孕妇。记录了身体、产科和牙周数据。收集GCF和血液样本，通过酶联免疫吸附测定（ELISA）法测定PLAP。开发了一个多元逻辑回归分类模型，并确定了该模型的分类效率。在研究队列中，4.3%的妊娠发生了PE。GCF - PLAP浓度比血浆样本高3至6倍。发生PE的女性GCF - PLAP浓度和收缩压更高（分别为 = 0.015和 < 0.001）。结合GCF - PLAP浓度和收缩压水平（妊娠11 - 14周时）的多参数模型的性能显示，收缩压和GCF - PLAP浓度与发生PE的可能性相关（OR：1.07；95% CI 1.01 - 1.11； = 0.004和OR：1.008，95% CI 1.000 - 1.015； = 0.034）。该模型的敏感性为83%，特异性为72%，阳性和阴性预测值分别为12%和99%。受试者工作特征（AUC - ROC）曲线下面积为0.77，正确分类了72%的PE妊娠。总之，所开发的多变量分类模型可能有助于识别随后发生PE的无症状女性。
