Zhou Bohui, Lian Junfang, Wang Yanping, Yang Yanling, Bai Hua, Wu Suhui
Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
Adv Clin Exp Med. 2025 Jul;34(7):1145-1153. doi: 10.17219/acem/191828.
Placenta previa, occurring when the placenta covers the cervical opening after 28 weeks, can lead to severe postpartum bleeding, especially when coupled with placenta accreta spectrum (PAS), posing risks of organ damage and necessitating hysterectomy. Accurate preoperative diagnosis of PAS in women with placenta previa is crucial to reduce adverse outcomes.
This study aimed to develop a risk prediction model for PAS in women with placenta previa.
A total of 437 patients with placenta previa, delivering babies between January 2012 and December 2018, were included. Data collected encompassed clinical records, neutrophil-to-lymphocyte ratio (NLR) and sonographic findings. Utilizing univariate and multivariate logistic regression analyses, the study identified key factors correlated with PAS in expectant mothers with placenta previa. A risk prediction model was formulated and evaluated through receiver operating characteristic (ROC) analysis. External validation was performed using additional patients diagnosed with placenta previa.
Independent risk factors for PAS in placenta previa included NLR, timing of cesarean section and miscarriage, placenta previa type, presence of placental lacunae, and uterovesical hypervascularity. The predictive model was established using specific coefficients. The ROC curve indicated an area under the curve (AUC) of 0.821, with a sensitivity of 80.6% and specificity of 68.9%. External validation demonstrated a diagnosis coincidence rate of 75%, and the model exhibited good calibration according to the Hosmer-Lemeshow test (p = 0.3742, >0.05).
The developed model showed effective potential in predicting PAS among women with placenta previa. Its application could significantly contribute to the early detection and subsequent management of PAS.
前置胎盘是指胎盘在孕28周后覆盖宫颈内口,可导致严重产后出血,尤其是合并胎盘植入谱系疾病(PAS)时,存在器官损伤风险并需要行子宫切除术。准确术前诊断前置胎盘孕妇的PAS对于降低不良结局至关重要。
本研究旨在建立前置胎盘孕妇PAS的风险预测模型。
纳入2012年1月至2018年12月间分娩的437例前置胎盘患者。收集的数据包括临床记录、中性粒细胞与淋巴细胞比值(NLR)及超声检查结果。通过单因素和多因素逻辑回归分析,本研究确定了前置胎盘孕妇中与PAS相关的关键因素。通过受试者工作特征(ROC)分析制定并评估风险预测模型。使用另外诊断为前置胎盘的患者进行外部验证。
前置胎盘患者发生PAS的独立危险因素包括NLR、剖宫产及流产时间、前置胎盘类型、胎盘湖的存在及子宫膀胱血管增多。使用特定系数建立预测模型。ROC曲线显示曲线下面积(AUC)为0.821,灵敏度为80.6%,特异度为68.9%。外部验证显示诊断符合率为75%,根据Hosmer-Lemeshow检验,该模型显示出良好的校准(p = 0.3742,>0.05)。
所建立的模型在预测前置胎盘孕妇的PAS方面显示出有效的潜力。其应用可显著有助于PAS的早期检测及后续管理。