Title : A Multicentric Evaluation of Indian Population-Specific Tools for Antenatal Estimation of Gestational Age

Background

The GARBH-Ini program, initiated in 2015 by THSTI at Civil Hospital, Gurugram, Haryana, focuses on understanding adverse pregnancy outcomes and developing solutions. It has enrolled over 10,000 pregnant women, collecting detailed demographic, clinical, and ultrasound data. Accurate gestational age (GA) estimation is essential for effective obstetric care, including screening for fetal anomalies, monitoring growth, and ensuring accurate epidemiological data. Traditional GA estimation methods like LMP-based dating are often inaccurate, particularly in India, due to variations in fetal growth and late antenatal care initiation.

The program has developed three Indian population-specific GA estimation tools:

1. Garbhini-GA1: First-trimester CRL-based model.
2. Garbhini-GA2: Second and third-trimester biometry-based model, more accurate than Hadlock and INTERGROWTH-21st models.
3. GAUGE: Image-based tool using raw ultrasound images, achieving high accuracy across internal and external validations.

This study aims to validate these tools across multiple Indian sites, considering factors such as State of residence (a surrogate for ethnic differences) , Socioeconomic status, Maternal anthropometric characteristics, Manufacturer of ultrasound machines and probes Level of experience and training in ultrasonography

Objectives

1. Assess the accuracy and precision of the Garbhini-GA2 formula using longitudinal ultrasound data.
2. Validate the GAUGE tool by collecting fetal head ultrasound images and comparing its predictions with the ground truth.

Study Methods

• Design: Prospective cohort study with retrospective data collection at select sites (SAS).
• Population: First-trimester pregnant women (9–14 weeks).
• Sample Size: 4,000 participants (1,000 per region).
• Study Duration: 2 years.

Inclusion Criteria

• Pregnant women aged >18 years, confirmed in the first trimester (9–14 weeks).
• Consent to participate and willingness to attend follow-ups.

Exclusion Criteria:

• Multifetal gestation, extrauterine pregnancy, or molar pregnancy.

Data Collection

1. Prospective:

   • Four ultrasounds per participant (dating, 18–22 weeks, 32–36 weeks, and an additional scan customized for gestational distribution).
   • Data includes demographics, maternal/paternal anthropometrics, clinical history, and ultrasound data.

2. Retrospective:

   • Data extraction from existing research databases (applicable to SAS).

Analysis Plan

• First-trimester USG-based dating serves as the gold standard GA.
• Estimated GA from Garbhini-GA2 and GAUGE models will be compared against the gold standard.
• Metrics: Distribution of errors, Bland-Altman analysis for bias, Cohen’s kappa for agreement.
• Subgroup analyses based on BMI, socioeconomic status, parity, and fetal growth status (FGR/SGA).

The study will also benchmark Indian models against global ones to ensure robust performance.

This research aims to enhance GA estimation in Indian settings, enabling more accurate and equitable maternal-fetal healthcare delivery.