The development and validation of a diagnostic scoring system to differentiate pulmonary tuberculosis from non-tuberculosis pulmonary infections in HIV-infected patients with severe immune suppression

医学 肺结核 接收机工作特性 内科学 逻辑回归 回顾性队列研究 胸腔积液 单变量分析 队列 多元分析 病理
作者
Jing Ouyang,Jing Yuan,Yaling Chen,Yanming Zeng,Vijay Harypursat,Yanqiu Lu,Hui Chen,Yao-Kai Chen
出处
期刊:BMC Infectious Diseases [Springer Nature]
卷期号:21 (1)
标识
DOI:10.1186/s12879-021-06552-3
摘要

Abstract Background It remains challenging to differentiate tuberculosis (TB) from non-TB pulmonary infections in HIV-infected patients. Herein, we developed a scoring system aimed to rapidly determine the likelihood of TB or non-TB pathology in HIV-infected patients presenting with pulmonary infections. Methods We collected and collated data of hospitalized HIV-infected patients with pulmonary infections, followed by univariate and multivariate data analyses to determine risk variables that were significantly different between HIV/TB patients and HIV/non-TB patients. Subsequently, a regression coefficient was calculated for each variable, and a score was assigned to each variable in line with its regression coefficient. The sum of the scores for each variable in our scoring model was used to predict the likelihood of TB or non-TB pulmonary infection in each patient. Finally, we tested the diagnostic accuracy of the scoring system in our retrospective cohort, as well as in a prospective cohort. Results A total of 598 HIV-infected patients were enrolled in our retrospective cohort, among whom 288 had TB and 310 had non-TB pulmonary infections. Eight variables, including fever, highest body temperature, erythrocyte sedimentation rate (ESR), cervical lymphadenopathy, hilar and/or mediastinum lymphadenopathy, pulmonary cavitation, pleural effusion, and miliary nodules, were found to be mathematically significantly different via univariate analysis and multivariate logistic regression analysis. After regression coefficient calculation followed by score assignment, a receiver operating characteristic (ROC) curve was plotted, and the area under the curve (AUC) was calculated to be 0.902. When the total score for a patient is > 12, the sensitivity and specificity for TB prediction using our scoring system were 76.4% and 87.7% respectively in the retrospective cohort, and its diagnostic accuracy was 82.7% in the prospective cohort. Conclusions Our results demonstrate that our proposed diagnostic scoring system could be helpful in differentiating pulmonary TB from non-TB pulmonary infections in HIV-infected patients.
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