Canadian respiratory journal · 2026
Survival Analysis of Risk Factors for Death in Patients With TB Based on Clinical and Imaging Characteristics.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Han Jing, Li Peng, Shi Lixia, Xie Yi, Liu Xiaolong, Yang Wanjie, Xing Zhiheng
Аннотация
BACKGROUND: This 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.
METHODS: We 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.
RESULTS: Male 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.
CONCLUSION: The 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.
METHODS: We 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.
RESULTS: Male 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.
CONCLUSION: The 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.