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HIV感染/AIDS患者结核感染风险预测模型的建立
Establishment of a risk prediction for tuberculosis infection model in HIV-infected/AIDS patients
- 陆军军医大学学报 2023年45卷第17期 页码：1869-1876
- 作者机构：
404000 重庆 万州，重庆大学附属三峡医院感染科
- 作者简介：
[蒋红, E-mail: 1982860828@qq.comJIANG Hong, E-mail: 1982860828@qq.com
- 基金信息：重庆市万州区科卫联合医学科研项目(WZSTC-KW2020028)
DOI：10.16016/j.2097-0927.202301110
中图分类号： R181.32;R512.91;R52收稿：2023-01-28，
修回：2023-05-03，
纸质出版：2023-09-15
- 稿件说明：
移动端阅览
陈倩立, 郑小燕, 陈瑞华, 等. HIV感染/AIDS患者结核感染风险预测模型的建立[J]. 陆军军医大学学报, 2023,45(17):1869-1876.
Qianli CHEN, Xiaoyan ZHENG, Ruihua CHEN, et al. Establishment of a risk prediction for tuberculosis infection model in HIV-infected/AIDS patients[J]. Journal of Army Medical University, 2023, 45(17): 1869-1876.
陈倩立, 郑小燕, 陈瑞华, 等. HIV感染/AIDS患者结核感染风险预测模型的建立[J]. 陆军军医大学学报, 2023,45(17):1869-1876. DOI： 10.16016/j.2097-0927.202301110.
Qianli CHEN, Xiaoyan ZHENG, Ruihua CHEN, et al. Establishment of a risk prediction for tuberculosis infection model in HIV-infected/AIDS patients[J]. Journal of Army Medical University, 2023, 45(17): 1869-1876. DOI： 10.16016/j.2097-0927.202301110.
摘要
目的
2
调查人类免疫缺陷病毒(human immunodeficiency virus，HIV)感染/艾滋病(acquired immune deficiency syndrome，AIDS)患者结核分枝杆菌(tuberculosis，TB)感染情况，并建立其预测模型。
方法
2
选择2017年1月至2022年8月在我院建档治疗的HIV感染/AIDS患者816例进行回顾性队列研究。采用信封法将以7 ∶3分为模型组571例与验证组245例。收集可能引起HIV感染/AIDS患者TB感染的相关指标，根据有无TB感染将患者分为结核组与非结核组，比较2组各因素，以LASSO筛选变量后行多因素Logistic回归分析，根据多因素分析结果建立列线图模型并进行验证。
结果
2
本研究模型组571例HIV感染/AIDS患者中59例(10.33%)确诊为TB感染。经LASSO回归筛基础上行多因素Logistic回归分析，结果显示: 年龄、吸毒史、卡介苗接种史、近期CD4
+
T细胞水平、结核病接触史、近1年咳嗽史是HIV感染/AIDS患者肺结核的独立影响因素(
P
＜0.05)。基于上述影响因素构建HIV感染/AIDS患者TB感染风险预测的列线图模型，ROC分析结果显示模型组构建HIV感染/AIDS患者TB感染风险预测值的曲线下面积(area under the curve，AUC)为0.823，95%
CI
为0.761~0.884；敏感度为77.97%
特异度为96.48%
阳性预测值为71.88%，阴性预测预测值为97.44%。验证组ROC分析AUC为0.817，95%
CI
为0.723~0.912；敏感度为76.92%
特异度为96.35%
阳性预测值为71.43%，阴性预测预测值为97.24%。校准曲线结果显示，模型组与验证组预测模型与理想模型基本拟合，提示模型准确度较好。
结论
2
HIV感染/AIDS患者TB感染主要受年龄、吸毒史、卡介苗接种史、近期CD4
+
T细胞水平、结核病接触史、近1年咳嗽史的影响，基于上述因素建立的预测模型预测HIV感染/AIDS患者TB感染风险具有较高的准确度与区分度。
Abstract
Objective
2
To investigate the infectious status of
Mycobacterium tuberculosis
(TB) in human immunodeficiency virus (HIV)-infected/acquired immune deficiency syndrome (AIDS) patients
and to establish
a prediction model for infection risk.
Methods
2
A retrospective cohort study was conducted on 816 HIV-infected/AIDS patients who were registered in our hospital from January 2017 to August 2022. Then with the aid of envelopes
571 cases were assigned into a testing group and 245 cases into a validation group at a ratio of 7 ∶3. Relevant indicators that may cause TB infection were collected in these patients. The patients were also divided into tuberculosis group and non-tuberculosis group. The relevant factors were compared between the 2 groups. After screening variables with LASSO
multivariate logistic regression analysis was performed and the obtained factors were used to establish a nomogram model
which was further verified.
Results
2
Among the 571 HIV-infected/AIDS patients in the model group
59 (10.33%) were diagnosed as TB infection. Multivariate logistic regression analysis showed that age
drug abuse history
BCG vaccination history
recent CD4
+
T cell level
tuberculosis contact history
and cough history in recent 1 year were independent influencing factors of TB infection in the patients (
P
<
0.05). Then a nomograph model for predicting the risk of TB infection was constructed in the HIV-infected/AIDS patients. ROC curve analysis indicated that the area under the curve (AUC) of the predictive value of TB infection risk in HIV infected/AIDS patients was 0.823
and the 95%
CI
was 0.761~0.884; the sensitivity was 77.97%
the specificity was 96.48%
the positive predictive value was 71.88%
and the negative predictive value was 97.44% in the model group. The AUC value of the validation group was 0.817
the 95%
CI
was 0.723~0.912
the sensitivity was 76.92%
the specificity was 96.35%
the positive predictive value was 71.43%
and the negative predictive value was 97.24%. The calibration curve results suggested that the prediction models of the model group and the validation group were
basically matched with the ideal model
indicating that the model accuracy is good.
Conclusion
2
TB infection of HIV-infected/AIDS patients is mainly affected by age
drug abuse history
BCG vaccination history
recent CD4
+
T cell level
tuberculosis contact history and cough history in the past 1 year. Our prediction model established based on the above factors has high accuracy and discrimination in predicting TB infection risk of these patients.
关键词
Keywords
references
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