ArticleCanadian respiratory journal2026
Survival Analysis of Risk Factors for Death in Patients With TB Based on Clinical and Imaging Characteristics.
Article in Canadian respiratory journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Survival Analysis of Risk Factors for Death in Patients With TB Based on Clinical and Imaging Characteristics.Canadian respiratory journal · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundThis study was performed to explore the predictive factors for mortality among patients with tuberculosis undergoing directly observed treatment, short-course (DOTS) therapy and to develop a clinically applicable visualization tool for mortality risk prediction.
methodsWe conducted a retrospective cohort study of 9270 patients (8884 survivors and 386 deaths, yielding a mortality rate of 4.16%) from 2014 to 2024, utilizing data from the tuberculosis management information system in Tianjin. Cox proportional hazards regression was used to identify independent risk factors, a nomogram model was constructed, and model performance was evaluated using cross-validation and ROC curves.
resultsMale sex, advanced age, human immunodeficiency virus-positive status, pulmonary cavities, initial sputum positivity, pericardial effusion, and miliary nodules emerged as independent risk factors for DOTS mortality. The nomogram demonstrated an area under the curve of 0.81 for predictions at 2, 6, and 12 months; calibration curves revealed high concordance between predicted and actual risk (with average absolute errors of 0.001, 0.001, and 0.004, respectively); receiver operating characteristic curves confirmed robust discriminative ability of the model.
conclusionThe nomogram developed in this study successfully integrates multiple mortality predictive factors and exhibits exhibiting excellent discriminatory power and calibration performance, thereby providing quantitative decision support for early identification and personalized intervention strategies in high-risk patients with tuberculosis receiving DOTS therapy.
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