A risk prediction model of spontaneous miscarriage in women with threatened miscarriage: a prospective cohort study

This study aims to develop a holistic risk prediction triage tool for women with threatened miscarriage by integrating clinical, biochemical, and radiological factors. Additionally, we aim to assess the performance of various models incorporating different factor combinations, adaptable for diverse resource settings.

This prospective cohort study included 1,080 women with single intrauterine pregnancies at 5-12 weeks' gestation presenting with threatened miscarriage at KK Women's and Children's Hospital, Singapore between October 2017 and May 2023. Multivariable logistic regression and risk-score models were developed using maternal age, nausea, prior miscarriages, serum progesterone, gestational age, and fetal heart activity. Model performance was assessed via Area Under Receiver Operating Characteristic (AUROC) curve with 10-fold cross-validation. The primary outcome was miscarriage by 16 weeks.

The miscarriage rate was 17.3%. Low serum progesterone (< 35 nmol/L) was the strongest predictor [odds ratio (OR) 26.3; 95% confidence interval (CI): 16.6-41.5], followed by absent fetal heart detection (OR 4.05; CI: 2.37-6.92) and increasing maternal age (OR 1.05; CI: 1.00-1.11). Higher gestational age decreased miscarriage risk (OR 0.57; CI: 0.45-0.73). The integrated model demonstrated high predictive accuracy (AUROC 0.90; CI: 0.87-0.93). The risk-score model achieved AUROC 0.82, with 80% sensitivity and 84% specificity at cut-off of 2.

This clinically practical holistic prediction tool enables early identification of women at high risk of miscarriage following threatened miscarriage. It may guide personalized counseling and targeted interventions in both high- and low-resource settings.