摘要
目的构建基于整合中医辨证分型与现代医学指标的蛛网膜下腔出血(SAH)预后风险评估模型,并验证其预测效能。方法回顾性收集SAH患者342例,按7∶3比例随机分为训练组(240例)和验证组(102例),并对两组患者进行中医辨证分型。根据90 d改良Rankin量表(MRS)评分将两组患者分为预后良好组(MRS评分≤2分)和预后不良组(MRS评分>2分)。采用回归分析确定预后独立危险因素,将差异有统计学意义(P<0.05)的因素纳入多因素Logistic回归分析确定预后独立危险因素,基于回归系数构建Logistic回归预测模型,利用受试者工作特征(ROC)曲线、校准曲线及Bootstrap法内部验证评估模型性能。结果Hunt-Hess分级(OR=2.763,95%CI:1.872,4.075,P<0.001)、格拉斯哥昏迷量表(GCS)评分(OR=0.782,95%CI:0.681,0.897,P=0.001)、动脉瘤大小(OR=1.253,95%CI:1.056,1.487,P=0.010)、痰热瘀阻证(OR=3.214,95%CI:1.764,5.856,P<0.001)及气虚血瘀证(OR=2.457,95%CI:1.349,4.478,P=0.003)为SAH患者预后不良的独立危险因素。基于上述因素构建的Logistic回归预测模型在训练组中表现优异[曲线下面积(AUC)=0.862,95%CI:0.813,0.911],验证组中亦显示良好预测能力(AUC=0.843,95%CI:0.769,0.917)。校准曲线显示模型预测与实际观察结果高度一致(Hosmer-Lemeshow检验,P=0.713)。结论本研究成功构建并验证了SAH预后风险Logistic回归预测模型,该模型具有良好的预测性能,可为SAH临床个体化干预提供理论依据。
Objective To construct a prognostic risk assessment model for subarachnoid hemorrhage(SAH)that integrates traditional Chinese medicine(TCM)syndrome differentiation and modern clinical indicators,and validate its predictive efficacy.Methods A total of 342 patients with SAH were retrospectively enrolled and randomly divided into a training group(n=240)and a validation group(n=102)in a ratio of 7:3.Based on the 90-day modified Rankin Scale(MRS)score,patients in the two groups were divided into a good prognosis group(MRS score≤2)and a poor prognosis group(MRS score>2).Regression analysis was used to identify independent prognostic risk factors.Factors with statistically significant dfferences(P<0.05)were included in a multivariate logistic regression analysis to determine independent prognostic risk factors.A logistic regression prediction model was constructed based on the regression coefficients.The model performance was evaluated using receiver operating characteristic(ROC)curves,calibration curves,and bootstrap method for internal validation.Results Hunt-Hess grade(OR=2.763,95%CI:1.872,4.075,P<0.001),Glasgow Coma Score(GCS)(0R=0.782,95%CI:0.681,0.897,P=0.001),aneurysm size(0R=1.253,95%CI:1.056,1.487,P=0.010),phlegm-heat and stasis obstruction syndrome(OR=3.214,95%CI:1.764,5.856,P<0.001),and qi deficiency and stasis obstruction syndrome(OR=2.457,95%CI:1.349,4.478,P=0.003)were independent risk factors for poor prognosis in patients with SAH.The logistic regression prediction model constructed based on the above factors performed well in the training group(AUC=0.862,95%CI:0.813,0.911),and also showed good predictive ability in the validation group(AUC=0.843,95%CI:0.769,0.917).The calibration curve showed that the model predictions were highly consistent with the actual observation results(Hosmer-Lemeshow test,P=0.713).Conclusion This study successfully constructed and validated the logistic regression prediction model for the prognosis risk of SAH.The model has good predictive performance and can provide a theoretical basis for individualized clinical intervention for SAH.
作者
向兴刚
马震
张燕
惠婷
顾晶亮
XIANG Xinggang;MA Zhen;ZHANG Yan;HUI Ting;GU Jingliang(Traditional Chinese Medical Hospital of Xinjiang Uygur Autonomous Region/The Fourth Affiliated Hospital of Xinjiang Medical University,Urumqi,830000;Faculty of Medicine,Taylor's University,Malaysia;The Fifth Affiliated Hospital of Xinjiang Medical University;Shanghai Hospital of Traditional Chinese Medicine)
出处
《中医杂志》
北大核心
2025年第18期1916-1924,共9页
Journal of Traditional Chinese Medicine
基金
新疆维吾尔自治区卫生健康青年科技人才专项科研项目(WJWY-202407)。
关键词
蛛网膜下腔出血
预后评估体系
风险评估模型
痰热瘀阻证
气虚血瘀证
动脉瘤
subarachnoid hemorrhage
prognosis assessment system
risk assessment model
phlegm-heat and stasis obstruction syndrome
qi deficiency and stasis obstruction syndrome
aneurysm
