AUTHOR=Li Dan , Tang Si-Yuan , Lei Sheng , Xie He-Bin , Li Lin-Qi 

TITLE=A nomogram for predicting mortality of patients initially diagnosed with primary pulmonary tuberculosis in Hunan province, China: a retrospective study

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2023.1179369

DOI=10.3389/fcimb.2023.1179369

ISSN=2235-2988

ABSTRACT=Objective: This study aims to construct a nomogram prognostic model to quickly recognize the death-related risk factors for patients initially diagnosed with primary pulmonary tuberculosis (PTB) to intervene and treat the high-risk patients as early as possible in the clinic to reduce mortality.
Methods: A retrospective method was adopted to analyze the clinical data of 1,809 in-hospital patients initially diagnosed with primary PTB in Hunan Chest Hospital from January 1, 2019, to December 31, 2019. Binary logistic regression analysis was used to screen out the risk factors. Nomogram prognostic model for mortality prediction was constructed with the help of R software. Constructed nomogram prognostic model was validated through a validation set. 
Results: The univariate and multivariate logistic regression analyses showed that drinking, hepatitis B virus (HBV), body mass index (BMI), age, albumin (ALB), and Hemoglobin (Hb) were the six independent predictors of death for in-hospital patients initially diagnosed with primary PTB. Based on these predictors, the nomogram prognostic model was established with high prediction accuracy, of which the area under the curve (AUC) was 0.881 [95% confidence interval (Cl): 0.777-0.847], the sensitivity was 84.7%, and the specificity was 77.7%. Both internal and external validations confirmed that the constructed model fitted the real situation well.
Conclusion: The constructed nomogram prognostic model can recognize the risk factors and accurately predict the mortality of patients initially diagnosed with primary PTB. It is expected to guide early clinical intervention and treatment for high-risk patients.