Predicting Down syndrome and neural tube defects using basic risk factors

Area of Science:

• Medical Science
• Public Health
• Biostatistics

Background:

• Congenital anomalies are leading causes of infant and under-5 mortality.
• Down syndrome (trisomy 21) and neural tube defects are common congenital anomalies.
• Limited access to advanced prenatal screening in developing countries necessitates simpler risk assessment tools.

Purpose of the Study:

• To evaluate the practicality of using basic risk factors for initial prenatal risk assessment of trisomy 21 and neural tube defects.
• To develop logistic regression models for early identification of pregnancies at risk.
• To provide an accessible tool for risk stratification in resource-limited settings.

Main Methods:

• Utilized logistic regression analysis.
• Focused on basic, readily available risk factors for prediction.
• Developed models for initial risk assessment of T-21 and NTDs.

Main Results:

• Prediction models demonstrated a limited balanced classification rate.
• Models successfully identified and could eliminate at least 50% of cases with no or low risk.
• The approach offers a viable initial screening strategy.

Conclusions:

• Despite moderate accuracy, logistic regression models using basic risk factors are effective for initial prenatal risk assessment of T-21 and NTDs.
• These models can serve as a valuable preliminary screening tool, especially where advanced diagnostics are unavailable.
• The study highlights the potential for simple risk factor-based models to improve prenatal care accessibility.