Ophthalmic artery Doppler for pre-eclampsia prediction at the first trimester: a Bayesian survival-time model

Raden Aditya Kusuma, Detty Siti Nurdiati, Adly Nanda Al Fattah, Didi Danukusumo, Sarini Abdullah, Ivan Sini

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To develop a Bayesian survival-time model for the prediction of pre-eclampsia (PE) at the first trimester using a combination of established biomarkers including maternal characteristics and history, mean arterial pressure (MAP), uterine artery Doppler pulsatility index (UtA-PI), and Placental Growth Factor (PlGF)) with an ophthalmic artery Doppler peak ratio (PR) analysis. Methods: The receiving operator curve (ROC) analysis was used to determine the area under the curve (AUC), detection rate (DR), and positive screening cut-off value of the model in predicting the occurrence of early-onset PE (< 34 weeks’ gestation) and preterm PE (< 37 weeks’ gestation). Results: Of the 946 eligible participants, 71 (7.49%) subjects were affected by PE. The incidences of early-onset and preterm PE were 1% and 2.2%, respectively. At a 10% false-positive rate, using the high-risk cut-off 1:49, with AUC 0.981 and 95%CI 0.965–0.998, this model had an 100% of DR in predicting early-onset PE. The DR of this model in predicting preterm PE is 71% when using 1:13 as the cut-off, with AUC 0.919 and 95%CI 0.875–0.963. Conclusion: Combination ophthalmic artery Doppler PR with the previously established biomarkers could improve the accuracy of early and preterm PE prediction at the first trimester screening.

Original languageEnglish
JournalJournal of Ultrasound
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Bayesian
  • Ophthalmic artery
  • Pre-eclampsia
  • Survival model

Fingerprint

Dive into the research topics of 'Ophthalmic artery Doppler for pre-eclampsia prediction at the first trimester: a Bayesian survival-time model'. Together they form a unique fingerprint.

Cite this