In an unprecedented research collaboration, scholars from the esteemed Indian Institute of Technology Madras (IIT Madras) and Translational Health Science and Technology Institute (THSTI) have unveiled an innovative artificial intelligence (ai) model, named Garbhini-GA2, designed specifically for India to accurately estimate the age of a fetus in pregnant women during their second and third trimesters. This noteworthy research, which is part of the ‘Interdisciplinary Group for Advanced Research on Birth Outcomes – DBT India Initiative’ (GARBH-Ini) program, aims to tackle the difficulties encountered when precisely determining gestational age (GA) in the Indian context.
The Significance of Accurate Gestational Age Estimation
Accurately estimating GA is vital for delivering optimal healthcare to pregnant women, monitoring fetal health, and managing pregnancy complications. However, late initiation of antenatal care in India poses a formidable challenge, with many women seeking care as late as 14 weeks after conception. This delay complicates traditional methods such as the last menstrual period (LMP) due to uncertainties surrounding LMP recall and inconsistent menstrual cycles.
India’s Ethnic Diversity and Complexities in Gestational Age Estimation
The ethnic diversity of India further complicates GA estimation, as variations in fetal growth patterns and biometric measurements not accounted for in Western-centric models necessitate population-specific models to ensure accurate GA assessments. Factors such as maternal nutrition, health conditions, and genetic factors significantly influence fetal growth patterns in India. Thus, a model tailored to the Indian population is essential for precise GA estimation.
Introducing Garbhini-GA2: A Model Tailored for India
To address these challenges, researchers from IIT Madras and THSTI created the Garbhini-GA2 model using data from the GARBH-Ini cohort study, a comprehensive evaluation of clinical data from Indian pregnant women. This extensive analysis allowed researchers to determine influential parameters impacting GA estimation during the late trimesters. The Garbhini-GA2 model integrates unique fetal biometry and growth patterns observed among the Indian population, ensuring more accurate GA predictions.
Comparative Evaluations and Superior Accuracy
Comparative evaluations of the Garbhini-GA2 model against existing formulas, such as Hadlock and InterGrowth-21st, have demonstrated its superior accuracy. Key performance indicators including root-mean-squared error, bias, and pre-term birth rates revealed that Garbhini-GA2 significantly reduced the median error in GA estimation by more than three times compared to the Hadlock formula, highlighting its exceptional suitability for the Indian population.
Revolutionizing Prenatal Care in India
Dr. Rajesh Gokhale, Secretary of the Department of Biotechnology, Government of India, commended the development of population-specific models within the GARBH-Ini initiative. He noted that these models are currently undergoing validation across India. Once validated, Garbhini-GA2 has the potential to revolutionize prenatal care by enabling obstetricians and neonatologists to deliver enhanced healthcare services. This could lead to a reduction in maternal and infant mortality rates.
Future Prospects and Impact on Healthcare
This groundbreaking research, led by Dr. Himanshu Sinha of IIT Madras and Dr. Shinjini Bhatnagar, Principal Investigator of GARBH-Ini at THSTI, holds the potential to transform prenatal care. Accurate GA estimation plays a crucial role in managing complications such as gestational diabetes and preeclampsia, allowing for targeted monitoring and treatment based on the stage of pregnancy. Additionally, it ensures reliable data for research into outcomes like stillbirth, preterm birth, and fetal growth restriction.
The creation and potential deployment of the Garbhini-GA2 model represent a significant leap forward in addressing the unique challenges of GA estimation in India. This ai-driven innovation promises to enhance healthcare outcomes for mothers and infants, offering a precise and tailored approach to gestational age determination as it undergoes validation and implementation in clinics nationwide. This advancement could mark the dawn of a new era for maternal and neonatal care in India, solidifying its position at the forefront of innovative healthcare solutions.
