In order to accurately ascertain the age of a foetus in a pregnant woman throughout the second and third trimesters, Indian experts have created a model tailored to their nation.
Currently, the age of a foetus (called gestational age, or GA) is calculated using a formula that was created for Western countries. Because the growth of the foetus varies among Indian tribes, this formula is likely to be inaccurate when employed later in pregnancy.
The age of a foetus for the Indian population may now be reliably estimated thanks to the recently established Garbhini-GA2 formula, which reduces error by nearly three times. The Science and Technology Ministry stated today that accurate GA is essential for deciding on exact delivery dates and for providing pregnant women with the proper treatment.
The methodology for calculating the GA in pregnant women throughout the second and third trimesters was developed by researchers from the Indian Institute of Technology, Madras, and the Biotechnology Research and Innovation Council’s Translational Health Science and Technology Institute (THSTI) in Faridabad.
The first late-trimester GA estimation model to be created and first verified with data from the Indian population is called Garbhini-GA2. GARBH-Ini cohort data recorded at Gurugram Civil Hospital, Haryana, was used to produce Garbhini-GA2, which employs three commonly measured fetal ultrasound markers. It was first verified in an independent cohort in South India.
The researchers employed genetic algorithm-based techniques to create Garbhini-GA2, which was more accurate than the models already in use when applied in the second and third trimesters of pregnancy (the results were published in the Lancet Regional Health Southeast Asia on February 13, 2024).
The gold standard for identifying GA in the early stages of pregnancy is ultrasound dating. Nonetheless, most Indian women get their first ultrasound performed in the second or third trimester of their pregnancy. Applying more accurate GA formulas tailored to the Indian population may benefit these women’s prenatal care. The precision of epidemiological estimates for pregnancy outcomes in the nation will also be improved by this precise date.
The data science lead for the new model, Himanshu Sinha of IIT Madras, stated that “we use advanced data science and AI/ML techniques to build tools to predict unfavourable birth outcomes.” The first step in achieving this is to create precise GA models that outperform the models in use today, which were created using populations from the West.”
