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产科患者输血量影响因素分析OA

Analysis on factors affecting blood transfusion volume of obstetric patients in a tertiary hospital in Beijing

中文摘要英文摘要

目的 基于国家健康建设战略,明确产科患者输血量影响因素,为临床输血管理与母婴安全保障提供依据.方法 回顾性选取本院 2013-2023 年 1 203 例产科输血患者为研究对象,收集临床资料并开展分析;选取年龄、BMI 指数、血红蛋白、凝血酶原时间、红细胞压积、血小板计数等 17 项指标作为研究变量,先进行描述性分析,通过散布图矩阵分析连续型变量与输血量的相关性,采用箱线图分析分类型变量及连续型变量与输血量的关联关系;依次构建线性回归模型、Logistic 回归模型、随机森林模型进行实证分析,对比 ROC 曲线及 AUC 值评估不同模型的统计学效能.结果 描述性分析显示产科输血量呈右偏分布,多项指标与输血量存在显著关联;线性回归分析提示年龄、BMI 指数、血红蛋白等 9 个变量与输血量存在显著相关;Logistic 回归证实 BMI 指数、血红蛋白等 7 个变量与大量输血发生概率显著相关;随机森林筛选出核心影响因素按重要性排序为:血红蛋白、凝血酶原时间、红细胞压积、BMI 指数、活化部分凝血酶原时间、血小板计数、年龄.模型对比结果显示,Logistic 回归 AUC=0.78,随机森林AUC=0.81,后者预测效能更优.结论 产前贫血、凝血功能异常、高龄、肥胖、妊娠高血压、胎盘异常及脏器异常会提升产科患者大量输血风险;随机森林模型在本研究中分析及预测能力更佳,研究结果可为产科精准输血、风险预判提供数据支撑.

Objective To explore the influencing factors of blood transfusion volume in obstetric patients based on the national health development strategy,and to provide evidence for clinical transfusion management and maternal and infant safety.Methods A total of 1 203 obstetric patients who received blood transfusion in a tertiary hospital in Beijing from 2013 to 2023 were enrolled retrospectively.Seventeen indicators including age,body mass index(BMI),hemoglobin and pro-thrombin time were selected as research variables.Descriptive analysis was conducted firstly.Scatter plot matrix was used to analyze the correlation between continuous variables and transfusion volume,and box plots were used to analyze the relation-ship between categorical variables and transfusion volume.Linear regression,logistic regression and random forest models were established for empirical analysis,and ROC curves and AUC values were compared to evaluate model performance.Re-sults Descriptive analysis showed that the distribution of obstetric blood transfusion volume was right-skewed,and multiple indicators were significantly correlated with transfusion volume.Linear regression indicated that 9 variables such as age,BMI and hemoglobin had linear correlation with transfusion volume.Logistic regression confirmed that 7 variables including BMI and hemoglobin were statistically correlated with the probability of massive blood transfusion.Random forest model screened the core influencing factors,which were ranked by importance:hemoglobin,prothrombin time,hematocrit,BMI,activated partial thromboplastin time,platelet count and age.The AUC values of logistic regression and random forest were 0.78 and 0.81 respectively,and the latter had better predictive performance.Conclusion Prenatal anemia,coagulation disorders,advanced age,obesity,gestational hypertension,placental abnormalities and organ damage can increase the risk of massive blood transfusion in obstetric patients.The random forest model has better analytical and predictive ability in this study.The results can provide reference for accurate blood transfusion and risk prediction in obstetrics.

付丽辉;马春娅;罗圆圆;关晓珍;台胜飞;师红梅;于洋

解放军总医院第一医学中心 输血医学科,北京 100853解放军总医院第一医学中心 输血医学科,北京 100853解放军总医院第一医学中心 输血医学科,北京 100853解放军总医院第一医学中心 输血医学科,北京 100853解放军总医院第一医学中心 输血医学科,北京 100853解放军总医院第一医学中心 输血医学科,北京 100853解放军总医院第一医学中心 输血医学科,北京 100853

医药卫生

产科患者输血量线性回归分析Logistic 回归分析随机森林

blood transfusion volume in obstetric patientslinear regression analysislogistic regression analysisran-dom forest

《中国输血杂志》 2026 (8)

1018-1025,8

10.13303/j.cjbt.issn.1004-549x.2026.08.004

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