文章摘要
张艳.耐药结核患者营养风险调查及其预测模型的建立[J].安徽医药,待发表.
耐药结核患者营养风险调查及其预测模型的建立
投稿时间:2024-05-07  录用日期:2024-06-24
DOI:
中文关键词: 耐药结核  营养不良  多因素分析  列线图模型
英文关键词: 
基金项目:] 重庆市万州区科卫联合医学科研项目(WZSTC-KW2020028)
作者单位邮编
张艳* 重庆大学附属三峡医院 404000
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中文摘要:
      目的:调查耐药结核患者营养风险,并建立起预测模型。方法:选择2022年1月至2024年1月我院接诊的421例耐药结核患者进行研究。入组者以7:3比例分为模型组295例,验证组126例。收集可能影响耐药结核患者营养不良的相关因素,根据有无营养不良将患者分为2组,比较2组基本情况、疾病相关指标及实验室指标,以LASSO回归筛选出潜在影响因素后行多因素Logisitic回归,根据多因素分析结果建立列线图模型并进行内部与外部验证。结果:模型组295例耐药结核患者中有73例(24.75%)出现营养不良,LASSO回归基础上行多因素Logistic回归分析结果显示:年龄、BMI、合并肺外结核、耐药状况、贫血、血清尿素氮为耐药结核患者营养不良的独立性影响因素(P<0.05)。模型区分度行ROC分析结果显示:模型组预测耐药结核患者营养不良风险的AUC为0.806〔95%CI(0.747,0.864)〕,敏感度为80.6%,特异度为65.8%;验证组的AUC为0.785〔95%CI(0.723,0.847)〕,敏感度为80.2%,特异度为68.5%。模型准确度行校准曲线结果显示,模型组与验证组的预测曲线与标准曲线基本拟合。H-L拟合优度检验检验结果显示模型拟合度较好(P>0.05)。决策曲线分析结果显示:当列线图预测耐药结核患者营养不良风险概率阈值为0.10-0.85时,患者的净受益率大于0。结论:耐药结核患者营养不良主要受年龄、BMI、合并肺外结核等因素的影响,本研究建立的列线图模型用于预测耐药结核患者营养不良风险具有较高的准确度与区分度。
英文摘要:
      Objective: To investigate the nutritional risk of drug-resistant tuberculosis patients and develop a predictive model. Methods: 421 patients with drug-resistant tuberculosis seen in our hospital from January 2022 to January 2024 were selected for the study.The enrolled patients were divided into 295 cases in the model group and 126 cases in the validation group in the ratio of 7:3. Relevant factors that may affect malnutrition in patients with drug-resistant tuberculosis were collected, and the patients were divided into 2 groups according to the presence or absence of malnutrition, comparing the basic conditions, disease-related indexes and laboratory indexes of the 2 groups, and multi-factorial Logisitic regression was performed after screening out the potentially affecting factors by LASSO regression, and the Nomogram model was established according to the results of the multi-factorial analysis, and was verified both internally and externally.Results: 73 (24.75%) of 295 drug-resistant tuberculosis patients in the model group were malnourished, and the results of multifactorial logistic regression analysis on the basis of LASSO regression showed that age, BMI, coexisting extrapulmonary tuberculosis, drug-resistant status, anaemia, and serum urea nitrogen were independent influences on malnourishment in drug-resistant tuberculosis patients (P<0.05).ROC analysis of model differentiation showed that the AUC for predicting the risk of malnutrition in drug-resistant TB patients in the model group was 0.806 [95% CI (0.747, 0.864)], with a sensitivity of 80.6% and a specificity of 65.8%, while in the validation group the AUC was 0.785 [95% CI (0.723, 0.847)], with a sensitivity of 80.2% and a specificity of 68.5%. degree was 68.5%. The results of the model accuracy line calibration curve showed that the prediction curves of the model group and the validation group were basically fitted to the standard curve.The results of H-L goodness-of-fit test test showed a good model fit (P>0.05). Decision curve analysis showed that the net benefit to patients was greater than 0 when the nomogram predicted a probability threshold of 0.10-0.85 for the risk of malnutrition in patients with drug-resistant tuberculosis.Conclusion: Malnutrition in drug-resistant tuberculosis patients is mainly affected by age, BMI, and combined extrapulmonary tuberculosis, and the Nomogram model developed in this study for predicting the risk of malnutrition in drug-resistant tuberculosis patients has high accuracy and discrimination.
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