# Development and validation of a nomogram model for predicting postoperative complications of cesarean scar pregnancy based on clinical data

**Authors:** Peiya Cai, Xiaolan Huang, Peiru Zhang

PMC · DOI: 10.3389/fmed.2025.1652022 · Frontiers in Medicine · 2026-01-12

## TL;DR

This study creates a clinical tool to predict postoperative complications in cesarean scar pregnancies, improving patient care and outcomes.

## Contribution

A novel nomogram model is developed and validated for predicting postoperative complications in cesarean scar pregnancy patients.

## Key findings

- Four independent predictors were identified: gestational age, interval since last cesarean, residual myometrial thickness, and intraoperative blood loss.
- The nomogram achieved high discrimination with AUCs of 0.868 and 0.865 in training and validation cohorts.
- The model demonstrated good calibration and clinical utility for guiding treatment strategies.

## Abstract

Cesarean scar pregnancy (CSP) is a rare but increasingly prevalent form of ectopic pregnancy, often associated with severe postoperative complications. Current research lacks robust tools to predict these complications. This study aimed to develop and validate a clinical nomogram to assess the risk of postoperative complications in CSP patients using multidimensional clinical data.

A retrospective cohort of 917 patients diagnosed with CSP between December 2015 and March 2024 was analyzed. Patients were randomly assigned to a training set (n = 689) and a validation set (n = 228). Multivariate logistic regression identified independent risk factors, which were used to construct a predictive nomogram. Model performance was evaluated by ROC curves, calibration plots, decision curve analysis, and clinical impact curves.

Four independent predictors of postoperative complications were identified: gestational age, interval since last cesarean section, residual myometrial thickness at the scar site, and intraoperative blood loss. The nomogram showed excellent discrimination with AUCs of 0.868 and 0.865 in the training and validation cohorts, respectively. Calibration and decision curve analyses confirmed good predictive accuracy and clinical utility.

The developed nomogram effectively predicts postoperative complications in CSP patients and can guide early clinical interventions and personalized treatment strategies, enhancing patient safety and outcomes.

## Linked entities

- **Diseases:** ectopic pregnancy (MONDO:0000755)

## Full-text entities

- **Diseases:** ectopic pregnancy (MESH:D011271), blood loss (MESH:D016063), CSP (MESH:D011254)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12832991/full.md

## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12832991/full.md

## References

38 references — full list in the complete paper: https://tomesphere.com/paper/PMC12832991/full.md

---
Source: https://tomesphere.com/paper/PMC12832991