摘要
目的:构建和验证慢性心力衰竭气虚血瘀证临床预测模型,以期辅助临床辨证,为慢性心力衰竭的个体化诊疗提供工具与方法。方法:回顾收集2022年1月至2024年1月于北京中医药大学东直门医院就诊的慢性心力衰竭患者的临床资料,按7∶3的比例将患者随机分为训练组和验证组。使用最小绝对收缩和选择算子(LASSO)回归分析对影响慢性心衰气虚血瘀证诊断的预测因素进行初步筛选,并采用Logistic回归的方法对预测因素进一步分析。纳入多因素Logistic回归结果中P<0.05的变量,并根据回归系数构建模型,绘制出列线图。通过R软件,绘制出模型的受试者工作特征(ROC)曲线、校准曲线和决策曲线(DCA),分别从区分度、校准度和临床适用性3个方面对模型进行评价。计算出模型的准确度、特异度、灵敏度、阳性预测值和阴性预测值,对模型进行更为全面的评估。结果:共得到训练组168例,验证组71例,两组间基线资料比较差异无统计学意义。经过LASSO-多因素Logistic回归筛选出暗红舌、吸烟史、心肌钙蛋白I(cTnI)和N末端B型利钠肽前体(NT-pro-BNP)是影响患者被诊断为慢性心衰气虚血瘀证的影响因素。所构建的模型在训练组中曲线下面积(AUC)为0.812,验证组中AUC为0.719。校准曲线显示模型的预测曲线与实际观测曲线较为接近。DCA显示,模型在0.2~0.9的决策阈值下能够为患者提供临床收益。结论:本研究所构建的慢性心力衰竭气虚血瘀证临床预测模型性能较好,在临床实践中有一定的应用价值。
Objective:To construct and validate a clinical prediction model for Qi deficiency and blood stasis syndrome in chronic heart failure(CHF),aiming to assist clinical diagnosis and provide tools and methods for individualized treatment of CHF.Methods:The clinical data of patients with chronic heart failure treated at Dongzhimen Hospital of Beijing University of Chinese Medicine from January 2022 to January 2024 were retrospectively collected.The patients were randomly divided into a training group and a validation group with a ratio of 7∶3.First,the least absolute shrinkage and selection operator(LASSO)regression analysis was used to preliminarily screen the predictive factors affecting the diagnosis of Qi deficiency and blood stasis syndrome in CHF.Subsequently,the Logistic regression method was applied to conduct a more in-depth and detailed analysis of these factors.Variables with P<0.05 in the results of the multi-factor Logistic regression were carefully selected and included.Based on the regression coefficients obtained from this analysis,a model was constructed,and a nomogram was accurately drawn.Using R software,the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DCA)were precisely drawn.These analyses were used to comprehensively evaluate the model from three crucial aspects:discrimination,calibration,and clinical applicability.Additionally,the accuracy,specificity,sensitivity,positive predictive value,and negative predictive value of the model were meticulously calculated to conduct a more all-round and comprehensive assessment.Results:In total,168 cases were successfully obtained in the training group,and 71 cases were included in the validation group.After a thorough comparison,it was found that there were no statistically significant differences in the baseline data between the two groups.After being rigorously screened by the LASSO-multivariate logistic regression method,dark red tongue,smoking history,cardiac troponin I,and N-terminal pro-B-type natriuretic peptide(NT-ProBNP)were identified as the influencing factors for diagnosing patients with the Qi deficiency and blood stasis syndrome in CHF.The constructed model demonstrated an area under the curve(AUC)of 0.812 in the training group and 0.719 in the validation group.The calibration curve showed that the predicted curve of the model was close to the actual observed curve.DCA indicated that the model could provide substantial clinical benefits for patients at the decision thresholds ranging from 0.2 to 0.9.Conclusion:The clinical prediction model for Qi deficiency and blood stasis syndrome in chronic heart failure constructed in this study shows good performance.It has certain application value in clinical practice,which may contribute to the improvement of the diagnosis and treatment of CHF patients with this syndrome.
作者
姜童
樊晓丹
王诗佳
林丰夏
曾志聪
尤良震
商洪才
JIANG Tong;FAN Xiaodan;WANG Shijia;LIN Fengxia;ZENG Zhicong;YOU Liangzhen;SHANG Hongcai(Binzhou Medical University,Yantai 264000,China;Key Laboratory of Chinese Internal Medicine of Ministry of Education,Beijing University of Chinese Medicine,Beijing 100700,China;Dongzhimen Hospital,Beijing University of Chinese Medicine,Beijing 100700,China;The Seventh Clinical College of Guangzhou University of Chinese Medicine(Shenzhen Bao'an Hospital of Traditional Chinese Medicine),Shenzhen 518101,China;Dongfang Hospital,Beijing University of Chinese Medicine,Beijing 100078,China)
出处
《中国实验方剂学杂志》
北大核心
2025年第6期154-163,共10页
Chinese Journal of Experimental Traditional Medical Formulae
基金
国家自然科学基金项目(82305056)
北京中医药大学东直门医院青年骨干人才培养计划项目(DZMG-QNGG003)
中央高校基本科研业务费专项(2024-JYB-KYPT-01)
宝安区中医药临床专项基金(2023ZYYLCZX-6)
深圳市医疗卫生三名工程项目(SZZYSM202206001)。
关键词
慢性心力衰竭
气虚血瘀证
列线图
临床预测模型
chronic heart failure
Qi deficiency and blood stasis syndrome
nomogram
clinical prediction model
