Gadekar Veerendra P, Damaraju Nikhita, Xavier Ashley, Thakur Shambo Basu, Vijayram Ramya, Desiraju Bapu Koundinya, Misra Sumit, Wadhwa Nitya, Khurana Ashok, Rathore Swati, Abraham Anuja, Rengaswamy Raghunathan, Benjamin Santosh, Cherian Anne George, Bhatnagar Shinjini, Thiruvengadam Ramachandran, Sinha Himanshu
Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.
Centre for Integrative Biology and Systems medicinE, Indian Institute of Technology Madras, Chennai, India.
Lancet Reg Health Southeast Asia. 2024 Feb 25;25:100362. doi: 10.1016/j.lansea.2024.100362. eCollection 2024 Jun.
A large proportion of pregnant women in lower and middle-income countries (LMIC) seek their first antenatal care after 14 weeks of gestation. While the last menstrual period (LMP) is still the most prevalent method of determining gestational age (GA), ultrasound-based foetal biometry is considered more accurate in the second and third trimesters. In LMIC settings, the Hadlock formula, originally developed using data from a small Caucasian population, is widely used for estimating GA and foetal weight worldwide as the pre-programmed formula in ultrasound machines. This approach can lead to inaccuracies when estimating GA in a diverse population. Therefore, this study aimed to develop a population-specific model for estimating GA in the late trimesters that was as accurate as the GA estimation in the first trimester, using data from GARBH-Ini, a pregnancy cohort in a North Indian district hospital, and subsequently validate the model in an independent cohort in South India.
Data obtained by longitudinal ultrasonography across all trimesters of pregnancy was used to develop and validate GA models for the second and third trimesters. The gold standard for GA estimation in the first trimester was determined using ultrasonography. The Garbhini-GA2, a polynomial regression model, was developed using the genetic algorithm-based method, showcasing the best performance among the models considered. This model incorporated three of the five routinely measured ultrasonographic parameters during the second and third trimesters. To assess its performance, the Garbhini-GA2 model was compared against the Hadlock and INTERGROWTH-21st models using both the TEST set (N = 1493) from the GARBH-Ini cohort and an independent VALIDATION dataset (N = 948) from the Christian Medical College (CMC), Vellore cohort. Evaluation metrics, including root-mean-squared error, bias, and preterm birth (PTB) rates, were utilised to comprehensively assess the model's accuracy and reliability.
With first trimester GA dating as the baseline, Garbhini-GA2 reduced the GA estimation median error by more than three times compared to the Hadlock formula. Further, the PTB rate estimated using Garbhini-GA2 was more accurate when compared to the INTERGROWTH-21st and Hadlock formulae, which overestimated the rate by 22.47% and 58.91%, respectively.
The Garbhini-GA2 is the first late-trimester GA estimation model to be developed and validated using Indian population data. Its higher accuracy in GA estimation, comparable to GA estimation in the first trimester and PTB classification, underscores the significance of deploying population-specific GA formulae to enhance antenatal care.
The GARBH-Ini cohort study was funded by the Department of Biotechnology, Government of India (BT/PR9983/MED/97/194/2013). The ultrasound repository was partly supported by the Grand Challenges India-All Children Thriving Program, Biotechnology Industry Research Assistance Council, Department of Biotechnology, Government of India (BIRAC/GCI/0115/03/14-ACT). The research reported in this publication was made possible by a grant (BT/kiData0394/06/18) from the Grand Challenges India at Biotechnology Industry Research Assistance Council (BIRAC), an operating division jointly supported by DBT-BMGF-BIRAC. The external validation study at CMC Vellore was partly supported by a grant (BT/kiData0394/06/18) from the Grand Challenges India at Biotechnology Industry Research Assistance Council (BIRAC), an operating division jointly supported by DBT-BMGF-BIRAC and by Exploratory Research Grant (SB/20-21/0602/BT/RBCX/008481) from Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras. An alum endowment from Prakash Arunachalam (BIO/18-19/304/ALUM/KARH) partly funded this study at the Centre for Integrative Biology and Systems Medicine, IIT Madras.
在低收入和中等收入国家（LMIC），很大一部分孕妇在妊娠14周后才首次进行产前检查。虽然末次月经日期（LMP）仍是确定孕周（GA）最常用的方法，但在孕中期和孕晚期，基于超声的胎儿生物测量法被认为更为准确。在LMIC环境中，最初使用一小部分白种人数据开发的Hadlock公式，作为超声机器中的预编程公式，在全球范围内被广泛用于估计孕周和胎儿体重。在不同人群中估计孕周时，这种方法可能导致不准确。因此，本研究旨在利用印度北部地区医院的一个妊娠队列GARBH-Ini的数据，开发一个孕晚期孕周估计的特定人群模型，其准确性与孕早期的孕周估计相当，随后在印度南部的一个独立队列中对该模型进行验证。
通过对妊娠各阶段进行纵向超声检查获得的数据，用于开发和验证孕中期和孕晚期的孕周模型。孕早期孕周估计的金标准通过超声检查确定。使用基于遗传算法的方法开发了多项式回归模型Garbhini-GA2，在考虑的模型中表现最佳。该模型纳入了孕中期和孕晚期常规测量的五个超声参数中的三个。为了评估其性能，使用GARBH-Ini队列的测试集（N = 1493）和基督教医学院（CMC）韦洛尔队列的独立验证数据集（N = 948），将Garbhini-GA2模型与Hadlock模型和INTERGROWTH-21st模型进行比较。利用包括均方根误差、偏差和早产（PTB）率在内的评估指标，全面评估模型的准确性和可靠性。
以孕早期孕周测定为基线，与Hadlock公式相比，Garbhini-GA2将孕周估计的中位数误差降低了三倍多。此外，与INTERGROWTH-21st和Hadlock公式相比，使用Garbhini-GA2估计的PTB率更准确，后两者分别高估了22.47%和58.91%。
Garbhini-GA2是第一个使用印度人群数据开发和验证的孕晚期孕周估计模型。其在孕周估计方面的更高准确性，与孕早期孕周估计和PTB分类相当，凸显了采用特定人群孕周公式以加强产前护理的重要性。
GARBH-Ini队列研究由印度政府生物技术部资助（BT/PR9983/MED/97/194/2013）。超声数据库部分得到了印度政府生物技术部生物技术产业研究援助理事会的印度大挑战 - 所有儿童茁壮成长计划的支持（BIRAC/GCI/0115/03/14 - ACT）。本出版物中报道的研究得到了生物技术产业研究援助理事会（BIRAC）的印度大挑战项目的资助（BT/kiData0394/06/18），BIRAC是一个由DBT - BMGF - BIRAC联合支持的运营部门。CMC韦洛尔的外部验证研究部分得到了生物技术产业研究援助理事会（BIRAC）的印度大挑战项目的资助（BT/kiData0394/06/18），BIRAC是一个由DBT - BMGF - BIRAC联合支持的运营部门，以及印度理工学院马德拉斯分校罗伯特博世数据科学与人工智能中心（RBCDSAI）的探索性研究资助（SB/20 - 21/0602/BT/RBCX/008481）。普拉卡什·阿鲁纳恰拉姆的校友捐赠（BIO/18 - 19/304/ALUM/KARH）部分资助了印度理工学院马德拉斯分校综合生物学与系统医学中心的这项研究。
