ORIGINAL RESEARCH article
Front. Med.
Sec. Pulmonary Medicine
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1637007
Development and Validation of a Nomogram to Predict Atelectasis in Adult Lymph Node Fistula Tracheobronchial Tuberculosis Patients
Provisionally accepted
- Hunan Chest Hospital, Changsha, China
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Background: Lymph node fistula tracheobronchial tuberculosis (TBTB) is a severe respiratory condition that can result in complications such as airway stenosis and atelectasis, posing significant clinical challenges, particularly in adults. Currently, no standardized assessment tools are available to predict the risk of atelectasis in these patients, highlighting the need to develop an effective predictive model to guide early clinical intervention and personalized treatment.Methods: A retrospective study was conducted involving 547 adult patients diagnosed with lymph node fistula TBTB at our hospital between January 2017 and December 2023. Diagnoses were confirmed by chest CT, bronchoscopy, and combined etiological or pathological examinations. After applying the inclusion and exclusion criteria, 301 cases were included in the final analysis. Patients were randomly assigned to a development group (n = 211, 70%) and a validation group. Following univariate and multivariable logistic regression to identify significant predictors, we developed a nomogram. Model validation included assessment of discriminatory ability (ROC analysis), calibration accuracy, and clinical utility (DCA).Results: Among the 301 patients with lymph node fistula TBTB, the incidence of atelectasis was 60.13% (181/301). Of those, 72.93% (132/181) had right lung involvement, and 50.28% (91/181) specifically had atelectasis in the right middle lobe. Independent predictors identified by multivariable logistic regression included age, occupation as a farmer, mediastinal lymphadenopathy with ring enhancement, and right middle lobe bronchial involvement. A risk nomogram was developed using these predictors. The area under the curve (AUC) of the nomogram was 0.824 (95% CI: 0.685-0.806) in the development group and 0.857 (95% CI: 0.702-0.877) in the validation group.Calibration plots based on 500 bootstrap resamples showed good agreement between predicted and observed probabilities across both groups. DCA revealed that the model provided a net clinical benefit within threshold probability ranges of 0.2-0.9 for the development group and 0.15-0.85 for the validation group.The predictive model and associated nomogram developed in this study can accurately estimate the risk of atelectasis in adult patients with lymph node fistula TBTB. This tool may assist clinicians in developing individualized intervention strategies.
Keywords: Tuberculosis, Bronchial Diseases, lymph node fistula, Atelectasis, nomogram, Prediction model
Received: 29 May 2025; Accepted: 16 Jul 2025.
Copyright: © 2025 Yin, Ou, Zhou, Wen, Huang, Ling and Luo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Li Luo, Hunan Chest Hospital, Changsha, China
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