Abstract:

Objective: To establish and verify a nomogram model for predicting frailty risk in elderly patients with pulmonary tuberculosis. Methods: Of 448 elderly patients with pulmonary tuberculosis admitted to the Pulmonary Department of Shenzhen Third People’s Hospital from June 1, 2022 to October 28, 2022 were selected as the modeling set, and of 129 elderly patients with pulmonary tuberculosis admitted from December 1, 2022 to February 28, 2023 were selected as the validation set. General data questionnaire, FRAIL Scale, Barthel Index, Self-management scale for elderly patients with pulmonary tuberculosis, tuberculosis-related stigma Scale, patient health questionnaire-9, Perceived social support scale and Charlson Comorbidity Index were used to investigate. According to the FRAIL scale score, the patients in the modeling set were divided into frail group and non-frail group, and the indexes of patients in the two groups were compared,and the risk prediction model was established according to the results of binary logistic regression analysis. R software was used to draw the nomogram for the assessment of frailty risk in elderly patients with pulmonary tuberculosis. 1000 times Bootstrap self-sampling method and validation set data were used to conduct internal and external validation of the nomogram model. Results: The incidence of frailty in elderly patients with pulmonary tuberculosis was 50.78% (293/577). Binary logistic regression analysis showed that: age (OR=1.054, 95%CI:1.020-1.089), course of disease (OR=1.092, 95%CI:1.013-1.177), sputum status (OR=1.916, 95%CI:1.136-3.229), white blood cell count (OR=1.129,95%CI:1.031-1.235), hs-CRP (OR=1.007,95%CI:1.002-1.011), activities of daily living (ADL)(OR=0.970, 95%CI:0.958-0.982), depression (OR=1.110, 95%CI:1.064-1.159), self-management (OR=0.944, 95%CI:0.903-0.986) and Charlson Comorbidity Index (OR=1.477, 95%CI: 1.180-1.849) were independent factors of frailty in elderly patients with pulmonary tuberculosis. The AUC of the modeling set and validation set were 0.842 (95%CI: 0.807-0.876) and 0.859 (95%CI: 0.797-0.921). Conclusion: The incidence of frailty in elderly patients with pulmonary tuberculosis is higher, and the risk of frailty can be reduced by enhancing the ability of ADL and self-management. The risk of frailty increases with age, disease course, inflammatory markers, comorbidities, and depression scores, as well as sputum positive.The nomogram model based on the above factors can be used to predict the frailty of the elderly patients with pulmonary tuberculosis.

Key words: Elderly, Tuberculosis, pulmonary, Frailty, Forecasting, Models, statistical