Department of Radiology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Department of Radiation Oncology, School of Medicine, Chengdu Women's and Children's Central Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Abdom Radiol (NY). 2023 Oct;48(10):3195-3206. doi: 10.1007/s00261-023-03968-0. Epub 2023 Jun 26.
To construct a scoring model based on MRI signs to predict massive hemorrhage during dilatation and curettage in cesarean scar pregnancy (CSP) patients.
The MRIs of CSP patients admitted to a tertiary referral hospital between February 2020 and July 2022 were retrospectively reviewed. The included patients were randomly assigned to the training and validation cohorts. The univariate and multivariate logistic regression analyses were adopted to identify the independent risk factors for massive hemorrhage (the amount of bleeding ≥ 200 ml) during the dilatation and curettage. A scoring model predicting intraoperative massive hemorrhage was established where each positive independent risk factor was assigned 1 point, and the predictive power of this model was evaluated both in the training and validation cohorts via the receiver operating characteristic curve.
A total of 187 CSP patients were enrolled, who were divided into the training cohort (31 in 131 patients had massive hemorrhage) and validation cohort (10 in 56 patients had massive hemorrhage). The independent risk factors for intraoperative massive hemorrhage included cesarean section diverticulum area (OR = 6.957, 95% CI 1.993-21.887; P = 0.001), uterine scar thickness (OR = 5.113, 95% CI 2.086-23.829; P = 0.025) and gestational sac diameter (OR = 3.853, 95% CI 1.103-13.530; P = 0.025). A scoring model with a total point of 3 was developed and the CSP patients were divided into low-risk (Total points < 2) and high-risk groups (Total points ≥ 2) for intraoperative massive hemorrhage accordingly. This model possessed high prediction performance both in the training cohort (area under the curve [AUC] = 0.896, 95% CI 0.830-0.942) and validation cohort (AUC = 0.915, 95% CI 0.785-1.000).
We first constructed a MRI-based scoring model for predicting intraoperative massive hemorrhage in CSP patients, which could help the decision-making of the patients' therapy strategies. Low-risk patients can be cured by D&C alone to reduce the financial burden, while high-risk patients require more adequate preoperative preparation or consideration of changing surgical approaches to reduce bleeding risk.
构建基于 MRI 征象的评分模型，以预测剖宫产术后瘢痕妊娠（CSP）患者刮宫术中大出血的风险。
回顾性分析 2020 年 2 月至 2022 年 7 月在一家三级转诊医院就诊的 CSP 患者的 MRI 资料。纳入的患者被随机分配到训练集和验证集。采用单因素和多因素 logistic 回归分析确定刮宫术中大出血（出血量≥200ml）的独立危险因素。建立预测术中大出血的评分模型，每个阳性独立危险因素赋值 1 分，并通过训练集和验证集的受试者工作特征曲线评估该模型的预测效能。
共纳入 187 例 CSP 患者，其中训练集 131 例（31 例术中大出血），验证集 56 例（10 例术中大出血）。术中大出血的独立危险因素包括剖宫产憩室面积（OR=6.957，95%CI 1.993-21.887；P=0.001）、子宫瘢痕厚度（OR=5.113，95%CI 2.086-23.829；P=0.025）和孕囊直径（OR=3.853，95%CI 1.103-13.530；P=0.025）。建立了一个总分为 3 分的评分模型，根据术中大出血的总积分将 CSP 患者分为低危（总积分<2）和高危（总积分≥2）两组。该模型在训练集（曲线下面积[AUC]：0.896，95%CI 0.830-0.942）和验证集（AUC：0.915，95%CI 0.785-1.000）中均具有较高的预测性能。
我们首次构建了一种基于 MRI 的评分模型，用于预测 CSP 患者刮宫术中大出血的风险，有助于患者治疗策略的决策。低危患者可单独采用 D&C 治疗，以降低经济负担，而高危患者需要更充分的术前准备或考虑改变手术方式，以降低出血风险。
