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India IIT Madras Developed a Model Accurately Determine Foetal Age in Pregnant Women

Researchers from BRIC-THSTI Faridabad and IIT Madras have achieved a significant breakthrough by devising an India-specific model to precisely determine the age of a foetus during the second and third trimesters of pregnancy. The development of this model, named Garbhini-GA2, marks a crucial advancement in maternal healthcare, addressing the inaccuracies prevalent in existing formulas designed for Western populations.

Currently, the determination of foetal age, known as gestational age (GA), relies on formulas tailored for Western demographics, leading to potential errors when applied to Indian women. The newly formulated Garbhini-GA2 model has demonstrated remarkable accuracy, reducing estimation errors by nearly threefold. Such precision is imperative for ensuring optimal care for pregnant women and establishing accurate delivery dates.

This pioneering research, conducted by the Biotechnology Research and Innovation Council – Translational Health Science and Technology Institute (THSTI) in Faridabad and the Indian Institute of Technology Madras (IIT Madras), is part of the Interdisciplinary Group for Advanced Research on Birth Outcomes under the DBT India Initiative (GARBH-Ini) program. By leveraging data from Indian populations, the Garbhini-GA2 model was meticulously developed and validated, culminating in its publication in the Lancet Regional Health Southeast Asia on February 13, 2024.

Utilizing genetic algorithm-based techniques, researchers harnessed three routinely measured foetal ultrasound parameters to devise Garbhini-GA2, surpassing the accuracy of existing models, such as Hadlock. This breakthrough promises to revolutionize pregnancy care in India, particularly for women who undergo their first ultrasound in the later stages of pregnancy.

Dr. Shinjini Bhatnagar, the principal investigator of the GARBH-Ini program, emphasized the collaborative nature of the study, underscoring the integration of clinical expertise and data science prowess. This synergy ensured the development of solutions that are not only technically robust but also clinically pertinent, facilitating seamless integration into healthcare protocols.

Dr. Himanshu Sinha from IIT Madras highlighted the institution’s commitment to addressing healthcare challenges through advanced data science and artificial intelligence (AI) techniques. By focusing on enhancing public health at the grassroots level, the research endeavors to predict adverse birth outcomes more accurately, starting with the development of precise GA models.

Dr. Rajesh Gokhale, Secretary of the Department of Biotechnology (DBT), lauded the Garbh-Ini program as a flagship initiative. He affirmed the ongoing validation of the population-specific models across India, underscoring their potential to transform maternal and infant healthcare outcomes nationwide.

The development of Garbhini-GA2 represents a significant stride towards personalized maternal care, with implications extending beyond clinical settings. As this model undergoes further validation and deployment in healthcare facilities nationwide, it holds the promise of mitigating maternal and infant mortality rates, thereby ushering in a new era of maternal wellness in India.

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