Purpose: To develop a nomogram to predict the probability of cesarean hysterectomy (CH) in placenta accreta spectrum disorders (PASD) patients.
Methods: Data from 520 patients who underwent surgery with a preliminary diagnosis of PASD at a tertiary center in southeast Turkey between 2013 and 2023 were collected, and 302 patients were included in the study. A predictive model based on clinical and ultrasonographic variables was developed using penalized maximum likelihood estimation (PMLE) regression analysis.
Results: Maternal age (aOR = 1.22, 95% CI 1.08-1.44, p = 0.001) and prior uterine surgeries (aOR = 3.18, 95% CI 1.57-8.29, p = 0.001) were identified as demographic factors with an increased likelihood of CH in the nomogram, and advanced gestational weeks demonstrated a negative correlation (aOR: 0.78, 95% CI 0.56-1.02, p = 0.07). Regarding the ultrasonographic findings, the presence of the "multiple lacunae within the placenta" (aOR = 48.53, 95% CI 18.42-257.40, p < 0.001) and the "anterior placental location" (aOR = 9.60, 95% CI 2.96-50.76, p < 0.001) significantly increased the probability of CH. In addition, "hypervascularization on Doppler flow with irregularity in the line between the bladder and uterine serosa" (aOR = 7.90, 95% CI 2.66-35.12, p < 0.001) and the "retroplacental myometrial thickness of < 1 mm" (aOR = 2.49, 95% CI 0.89-8.27, p = 0.08) were related to the probability of CH. Harrell's C-index was 0.974, and the kappa value was 0.819 for the prediction model's performance evaluation.
Conclusion: We developed a nomogram to predict the probability of cesarean hysterectomy in patients with PASD, incorporating maternal age, gestational weeks, prior uterine surgeries, ultrasound findings, and placental location. The most closely associated findings with CH in patients with PASD were the presence of multiple placental lacunae and the anterior location of the placenta.
Keywords: Cesarean hysterectomy; Nomogram; Placenta accreta spectrum disorders; Prediction model; Ultrasonography.
© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.