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Published on: January 12, 2018
Developing a Preterm Birth Prediction Model in Pregnant People With HIV Using a Population-Based Cohort
Jeffrey Man Hay Wong1, Terry Lee2, Gal Av-Gay3
1Department of Obstetrics and Gynecology, University of British Columbia, Vancouver, Canada.
Insights
Preterm birth in pregnant people living with HIV (PLWH) is linked to substance use, Hepatitis C, and infections. A new model predicts preterm birth risk for PLWH, aiding targeted interventions.
Area of Science:
- Obstetrics and Gynecology
- Infectious Diseases
- Public Health
Background:
- Preterm birth is a significant concern in pregnancies complicated by HIV.
- Identifying risk factors is crucial for developing targeted interventions and improving outcomes for pregnant people living with HIV (PLWH).
Purpose of the Study:
- To identify independent risk modifiers for preterm birth in PLWH.
- To develop a predictive model for preterm birth in this population.
Main Methods:
- Analysis of singleton births from the British Columbia Perinatal HIV Surveillance Database (1997-2022).
- Univariate and multivariate logistic regression analyses were employed to identify risk factors.
- A prediction model was developed using stepwise regression with Akaike information criterion.
Main Results:
- Of 578 pregnancies, 19.2% resulted in preterm births.
- Independent risk factors identified include substance use (OR: 1.9), Hepatitis C (OR: 1.98), unsuppressed viral load (OR: 2.03), and STIBV (OR: 2.06).
- A prediction model incorporating these factors achieved an AUC of 0.73, with a 9% predicted probability of preterm birth for PLWH without identified risk factors.
Conclusions:
- Substance use, unsuppressed viral load, Hepatitis C co-infection, and STIBV are significant independent risk factors for preterm birth in PLWH.
- The developed prediction model can aid in identifying high-risk pregnancies for targeted management.
Objective:
To identify independent risk modifiers of and develop a prediction model for preterm births for pregnant people living with HIV (PLWH).
Methods:
We analyzed the British Columbia Perinatal HIV Surveillance Database for singleton births from January 1997 to December 2022. Risk modifiers for preterm birth (<37 weeks gestational age) were identified through univariate analyses. We then completed a multivariate logistic regression using clinically relevant risk factors and risk modifiers with P < 0.1 in the univariate analysis. Using stepwise regression with the Akaike information criterion, the prediction model was developed.
Results:
Of 578 singleton pregnancies in pregnant PLWH, 111 (19.2%) had preterm births. After adjusting for history of preterm births, CD4 count at delivery, and antiretroviral regimens, independent risk factors include substance use in pregnancy (odds ratio [OR]: 1.9; 95% CI: 1.03 to 3.50; and P = 0.041), hepatitis C in pregnancy (OR: 1.98; 95% CI: 1.02 to 3.83; and P = 0.043), unsuppressed viral load at delivery (OR: 2.03; 95% CI: 1.09 to 3.79; and P = 0.026), and sexually transmitted infections or bacterial vaginosis (STIBV) in pregnancy (OR: 2.06; 95% CI: 1.04 to 4.10; and P = 0.039). A prediction model with substance use, STIBV, hepatitis C in pregnancy, unsuppressed viral load, and low CD4 count was developed Area Under the Curve (AUC) = 0.73). For PLWH without any risk factors, the predicted probability of preterm birth is 9%.
Conclusions:
Independent risk factors associated with preterm births in pregnant PLWH include substance use in pregnancy, unsuppressed viral load, hepatitis C co-infection, and STIBV in pregnancy. Our simplified preterm birth prediction tool provides a personalized approach to caring for pregnant PLWH.
