Background and Aims
The goal of this study was to demonstrate the effects of factors related with time to developing pre‐eclampsia (PE) among pregnant women follow‐up service at Arerti Primary Hospital.
Methods
A survival analysis was employed on a pregnant women's follow‐up service from September 2018 to June 2019 at the Arerti Primary Hospital. A closed‐form sample size formula for estimating the effect of the time‐to‐event data was used. Both the descriptive method and Cox proportional hazards model were applied to compute the research survival data.
Results
Using the Kaplan–Meier estimation technique, the univariable analysis shows that the survival time median is 7 months and 3 weeks. The graph of Kaplan–Meier estimate of total survival functions indicates a decreasing pattern of survivorship function. We used the Kaplan–Meier estimates to investigate the effects of observed differences among different categories of the factors, we applied the Log‐rank test. The final survival model outcomes weight, marital status, age, history of PE, and multiplicity were related to a substantial hazard of evolving PE.
Conclusion
On the basis of our final survival model results, we recommended that all pregnant women having such risk factors should see a health care professional and control their medical condition before and during pregnancy. Advising women about proper body weight in each follow‐up period is supported. Finally, health experts should advise pregnant women about potential risk factors related to PE.
Background: Preeclampsia is a hypertensive disorder of pregnancy that affects 2-8% of pregnant women. It is the major cause of maternal and perinatal morbidity and mortality worldwide. The purpose of this study was to identify factors associated with hypertension measurements and time-to-onset of preeclampsia among pregnant women attending antenatal care service at Arerti Primary Hospital. Methodology: A retrospective longitudinal study design was employed on a total of 201 pregnant women attending the antenatal clinic of Arerti Primary Hospital between September 2018 and June 2019. A closed-form sample size formula for estimating the effect of the longitudinal data on time-to-event was used. To analyze our data we employed descriptive method, linear mixed effect model, Cox-PH model and joint models for longitudinal and survival outcomes.Relevantdemographicandclinicalcovariateswereincludedinsubmodels. Results: This study revealed that baseline age, visiting times, weight, diabetes, history of PE and parity had significantly associated with mean change in the BP measurements. From the Cox model result, age, weight, history of PE and marital status were associated with a significant hazard of developing preeclampsia. The univariate joint models reveal that the each longitudinal BP measurements are significantly associated with hazard of developing preeclampsia. Form the bi-ariate joint model; only DBP is significantly associated with risk of developing PE. Conclusion: As the result obtained in this study, we summarized that, age, weight, history of PE and marital status had a significant effect on time to developing preeclampsia. Furthermore, due to significance of association between the longitudinal BP measurements and time to onset of preeclampsia, joint model analysis was suggested as it incorporates all information simultaneously and provides valid and efficient inferences over separate models analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.