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1.重庆医科大学/重庆市人民医院妇产科,重庆 401146
2.陆军军医大学预防医学系卫生统计学教研室,重庆 400038
杜 霞,Email:1181041222@gg.com,
陈 诚,Email:chencheng961@126.com。
收稿:2025-01-24,
修回:2025-04-12,
录用:2025-05-17,
纸质出版:2025-10-28
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杜霞,吴琦,李佳芮,等.多次剖宫产术后再次妊娠严重产后出血列线图预测模型的构建[J].重庆医科大学学报,2025,50(10):1426-1433.
Du Xia,Wu Qi,Li Jiarui,et al.Establishment of a nomogram prediction model for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections[J].Journal of Chongqing Medical University,2025,50(10):1426-1433.
杜霞,吴琦,李佳芮,等.多次剖宫产术后再次妊娠严重产后出血列线图预测模型的构建[J].重庆医科大学学报,2025,50(10):1426-1433. DOI: 10.13406/j.cnki.cyxb.003923.
Du Xia,Wu Qi,Li Jiarui,et al.Establishment of a nomogram prediction model for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections[J].Journal of Chongqing Medical University,2025,50(10):1426-1433. DOI: 10.13406/j.cnki.cyxb.003923.
目的
2
构建多次剖宫产术后再次妊娠严重产后出血的列线图预测模型。
方法
2
本研究采用回顾性队列研究设计,纳入2021年1月至2023年12月住院分娩的395例多次剖宫产孕产妇的临床资料和影像学检查结果,采用单因素分析和多因素logistic回归分析筛选多次剖宫产术后再次妊娠并发严重产后出血的独立危险因素;基于回归分析结果构建列线图预测模型,验证模型的特异性、准确性和临床决策效用。
结果
2
395例多次剖宫产孕妇中,严重出血131例,占33.16%。单因素分析结果显示:孕次、顺产产次、既往手术医院等级、本次产检次数、妊娠高血压疾病、妊娠期糖尿病、合并前置胎盘、胎盘位置、胎盘与子宫关系和急诊剖宫产等因素是多次剖宫产术后再次妊娠严重产后出血的危险因素(
P
<
0.05)。多因素logistic回归分析结果显示:孕次、产检次数、妊娠期糖尿病、胎盘位置和急诊剖宫产是多次剖宫产后再次妊娠严重产后出血的独立危险因素(
P
<
0.05)。以独立危险因素建立列线图模型,ROC曲线下面积为0.783(95%CI=0.732~0.834);预测概率曲线与观测频率曲线间均具有较好一致性;列线图模型预测严重产后出血的概率在15%~100%时,模型具有较好的临床决策价值。
结论
2
定期产检,控制妊娠并发症,降低急诊剖宫产率和分娩次数,有助于降低该类人群严重产后出血的发生率。该列线图模型可为临床医师提供个体化的风险评估工具,有助于早期识别高危患者并实施针对性干预,具有重要的临床应用价值。
Objective
2
To establish a nomogram prediction model for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections.
Methods
2
A retrospective analysis was performed for the clinical and imaging data of 395 pregnant and parturient women with multiple cesarean section who were hospitalized for delivery from January 2021 to December 2023. Univariate analysis and multivariate logistic regression analysis were used to investigate the risk factors for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections. A nomogram prediction model was established and validated in terms of specificity,accuracy,and clinical decision-making utility.
Results
2
Among the 395 patients,131 experienced severe postpartum hemorrhage,accounting for 33.16%. The univariate analysis showed that times of pregnancy,times of vaginal delivery,grade of hospitals for previous surgeries,number of prenatal checkups during this time of pregnancy,pregnancy-induced hypertension,gestational diabetes,placenta previa,location of placenta,association between placenta and uterus,and whether emergency cesarean section was performed were risk factors for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections(
P
<
0.05). The multivariate logistic regression analysis showed that times of pregnancy,number of prenatal checkups,gestational diabetes,position of placenta,and whether emergency cesarean section was performed were independent risk factors for severe postpartum hemorrhage in subsequent pregnancies after multiple cesarean sections(
P
<
0.05). A nomogram prediction model was established based on these independent risk factors,which had an area under the ROC curve of 0.783(95%CI=0.732-0.834),and there was a good consistency between the predicted probability curve and th
e observed frequency curve. When the probability of severe postpartum hemorrhage predicted by the nomogram model was within the range of 0.15-1.0,the model has a good value of clinical decision-making.
Conclusion
2
The incidence rate of severe postpartum hemorrhage in this population can be reduced by attending regular prenatal checkups,controlling pregnancy complications,and reducing the rate of emergency cesarean section and the number of deliveries. The nomogram prediction model established in this study has certain clinical application prospects.
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