Prediction of Low Birth Weight From Quadruple Screening in Sanpatong Hospital, Chiang Mai

Surachai ponglopisit

ผู้แต่ง

Surachai ponglopisit Sanpatong Hospital, Chiang Mai, Thailand

คำสำคัญ:

low birth weight, quadruple test, prediction model, alpha- fetoprotein, β-hCG

บทคัดย่อ

Objective This study aimed to develop a predictive model for low birth weight (LBW) using maternal history and the second trimester biochemical quadruple screening test in singleton pregnancies delivered at Sanpatong Hospital, Chiang Mai, Thailand.

Methods: This retrospective cohort study collected data from medical records of 873 singleton pregnancy women who underwent the quadruple test at 14-16 weeks of gestation and delivered at Sanpatong Hospital between October 1, 2016, and September 30, 2023. Data collected included maternal characteristics, quadruple test results, obstetric complications, and birth weight. Multivariable logistic regression was used to analyze associations between various factors and LBW. Model performance was evaluated using receiver operating characteristic (ROC) curve analysis.

Results: The incidence of LBW was 6.76% (59 out of 873 deliveries). Significant factors associated with LBW in multivariable analysis included maternal body mass index (BMI) (AOR = 0.924, p = 0.018), nulliparity (AOR = 0.524, p = 0.021), high-risk quadruple test for aneuploidy (AOR = 16.061, p = 0.006), preeclampsia (AOR = 3.573, p = 0.007), preterm labor (AOR = 36.526, p < 0.001), fetal growth restriction (AOR=45.726, p < 0.001), MoM of AFP (AOR = 2.598, p = 0.001), and MoM of -hCG (AOR = 1.352, p = 0.003). Four predictive models were developed: history-only (AUC = 0.673), biochemical-only (MoM of AFP and -hCG; AUC = 0.604), a combined model (history + biochemical; AUC = 0.707), and a full combined model (history + biochemical + complication; AUC = 0.902). The full combined model demonstrated superior performance in predicting LBW.

Conclusions: The full combined model incorporating clinical history and quadruple test biochemical markers (AFP and -hCG) effectively predicts LBW. These findings suggest the potential for early identification of at-risk pregnancies, enabling timely interventions to improve maternal and neonatal outcomes.

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