Developing a Preterm Birth Prediction Model in Pregnant People With HIV Using a Population-Based Cohort

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.