Bayesian Accelerated Failure Time Model and Its Application to Preeclampsia

DOI

10.2991/acsr.k.220202.029How to use a DOI?

Keywords

Delivery time; Gestational time; Survival regression model

Abstract

Preeclampsia (PE) often described as new-onset hypertension and proteinuria during the third trimester of pregnancy. PE, is one of the most feared complications of pregnancy because it can progress rapidly to serious complications, including death of both mother and fetus. It is important to get a better understanding about the factors that might affect the PE condition in pregnant women. Therefore, in this study, we tried to model the relationship between several factors and the time until deliveries under the PE condition. Data on 924 patients at obstetric and gynecology department in a hospital in Jakarta were used in the analysis. A survival regression model, Accelerated Failure Time (AFT) model, was proposed to model the delivery time under PE condition and important factors that influenced the time. Model parameters were estimated using Bayesian method. The results revealed some important factors in explaining the time of deliveries and we also produced the formulation for calculating the estimated probability of delivery given a specific gestational time and patient’s characteristics.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Dennis Alexander
AU  - Sarini Abdullah
PY  - 2022
DA  - 2022/02/08
TI  - Bayesian Accelerated Failure Time Model and Its Application to Preeclampsia
BT  - Proceedings of the  International Conference on Mathematics, Geometry, Statistics, and Computation (IC-MaGeStiC 2021)
PB  - Atlantis Press
SP  - 152
EP  - 155
SN  - 2352-538X
UR  - https://doi.org/10.2991/acsr.k.220202.029
DO  - 10.2991/acsr.k.220202.029
ID  - Alexander2022
ER  -