Cohort profile: the Cohort for Risk Prediction Model Evaluation (CORE) for external validation of models identifying high-risk pregnant women in the early second trimester, North India

Purpose: The Cohort for Risk Prediction Model Evaluation (CORE) was established to externally validate prediction models that identify high-risk pregnancies in the early second trimester. Such models are often developed on small, single-source datasets and seldom tested elsewhere. Recent evidence shows that only about 6-10% models are ever externally validated which raises concerns about whether they perform reliably in new and diverse populations. In the maternal perinatal space, CORE addresses this gap by providing an Indian second-trimester cohort with harmonised imaging and outcome data on which existing risk prediction models can be validated. Participants. CORE includes 964 pregnant women aged over 18 years, enrolled at the Hamdard Institute of Medical Sciences and Research (HIMSR), New Delhi, between August 2021 and March 2023. Women were recruited before 20 weeks of gestation and followed up at 18-22 weeks for an ultrasound scan and at delivery. At all time points, a structured set of sociodemographic, clinical, and obstetric data was captured, together with ultrasound images at 18-20 weeks from which fetal biometry and cervical length were measured. Findings to date: The median maternal age was 27.6 years; 51% had a normal body-mass index (BMI) and 30% were overweight. There were almost equal number of Nulliparous (480, 50%) and multiparous (484, 50%). About 41% prevalence of history of prior preterm in multiparous women. Outcomes were available for 750 participants (23 abortions, 3 stillbirths, 724 singleton live births). Among the 724 live births, 80/724 (11%) were preterm, 190/716 (26.5%) were small for gestational age (SGA) and 40/716 (5.6%) were large for gestational age (LGA) by INTERGROWTH-21st standards and 260/716 (35.6%) of newborns were categorized into small vulnerable newborn (SVN). Future plans. CORE will be used to externally validate and, in aggregate with similar cohorts, help improve risk-prediction models for pregnant women in India and comparable settings. We invite collaborators to use this resource; clinical and imaging data are available under a controlled-access model on reasonable request. Strengths and limitations of this study Prospective cohort with data-collection and ultrasound protocols harmonised with the GARBH-Ini and AMANHI cohorts, enabling like-for-like pooled and cross-cohort analyses. A two-tier ultrasound quality-assurance process, with retention of both clean (unannotated) and caliper-annotated images, supports validation of image-based prediction models. Sample size informed by precision-based guidance for the external validation of prediction models, providing adequate power to assess model discrimination for the principal outcomes. Single-site, hospital-based recruitment from a limited geographical catchment, which constrains direct generalisability and makes the cohort most valuable when pooled with comparable cohorts. No continuous follow-up between 20 weeks of gestation and delivery, limiting the assessment of temporal change and longer-term outcomes.