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Background  To build a novel and simple model to predict iatrogenic preterm birth in pregnant women with scarred uteri.    Methods  In this retrospective, observational, single-centre cohort study, data from 2315 patients with scarred uteri were collected. Multiple logistic regression analysis and mathematical modelling were used to develop a risk evaluation tool for iatrogenic preterm birth. After modelling, the calibration and discrimination of the model along with decision curve analysis were checked and performed to ensure clinical applicability.    Results  Among the 2315 patients, 417 (18.0%) had iatrogenic preterm births. The following variables were included in the model: interpregnancy interval (0 to < 12 months, OR 5.33 (95% Cl 1.79–15.91),  P  = 0.003; 13 to < 24 months (reference), 25 to < 60 months, OR 1.80 (95% CI 0.96–3.40),  P  = 0.068; ≥ 60 months, OR 1.60 (95% Cl 0.86–2.97),  P  = 0.14), height (OR 0.95, (95% CI 0.92–0.98),  P  = 0.003), parity (parity ≤1 (reference), parity = 2, OR 2.92 (95% CI 1.71–4.96),  P  < 0.0001; parity ≥3, OR 8.26, (95% CI 2.29–29.76),  P  = 0.001), number of vaginal bleeding (OR 1.81, (95% Cl 1.36–2.41),  P  < 0.0001), hypertension in pregnancy (OR 9.52 (95% CI 6.46–14.03),  P  < 0.0001), and placenta previa (OR 4.21, (95% CI 2.85–6.22),  P  < 0.0001). Finally, a nomogram was developed.    Conclusions  In this study, we built a model to predict iatrogenic preterm birth for pregnant women with scarred uteri. The nomogram we created can assist doctors in evaluating the risk of iatrogenic preterm birth and help in making referrals; thus, better medical care can be given to improve the prognosis of patients and foetuses.

Prediction of iatrogenic preterm birth in patients with scarred uterus: a retrospective cohort study in Northeast China