Establishment and assessment of a nomogram for predicting adverse outcomes of preterm preeclampsia. Issue 7 (July 2020)

• Record Type: Journal Article
• Authors: Chen, Rongxin; Han, Qing; Zheng, Lianghui; Jiang, Lingling; Yan, Jianying
• Is Part Of: Journal of international medical research. Volume 48:Issue 7(2020)
• Publication Date: 2020-07
• Subjects: Preeclampsia -- nomogram -- predict -- adverse outcomes -- prognostic factors -- Cox regression analysis; Medicine -- Periodicals; Pharmacology -- Periodicals; 610.5
• DOI: 10.1177/0300060520911828
• Languages: English
• ISSNs: 0300-0605

Abstract

Objective: This prospective study was designed to develop and internally validate an accurate prognostic nomogram model with which to predict the adverse outcomes of preterm preeclampsia. Methods: Pregnant women with preeclampsia were divided into the adverse outcome group and the no adverse outcome group. The Kaplan–Meier method, univariate Cox regression analysis, and calculation of the concordance index (C-index) were applied to predictive evaluation of the nomogram. Calibration curves were drawn to test the nomogram prediction and actual observation of the adverse outcome rate. Results: After 1000 internal validations of bootstrap resampling, the C-index of the nomogram for predicting adverse outcomes within 48 hours was 0.74 and the cut-off value was 0.53, with a sensitivity of 61.57% and a specificity of 76.93%. The C-index of the nomogram for predicting adverse outcomes within 7 days was 0.76 and the cut-off value was 0.37, with a sensitivity of 58.17% and a specificity of 84.82%. The calibration curves showed good concordance of incidence of adverse outcomes between nomogram prediction and actual observation. Conclusion: Cox regression has certain guiding significance in preventing and treating adverse outcomes, choosing the time of termination of pregnancy, and improving the prognosis of the mother and child.