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构建并验证用于识别肺结核空洞风险的列线图
Authors Song M, Zhang M, Han J, Fu W
Received 13 March 2024
Accepted for publication 18 June 2024
Published 5 July 2024 Volume 2024:17 Pages 2803—2813
DOI https://doi.org/10.2147/IDR.S459330
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 6
Editor who approved publication: Professor Sandip Patil
Mei Song, Meng Zhang, Jia Han, Wenjiang Fu
Department of Infectious Diseases, Jiashan County First People’s Hospital, Jiashan, Zhejiang, 314100, People’s Republic of China
Correspondence: Mei Song; Wenjiang Fu, Department of Infectious Diseases, Jiashan County First People’s Hospital, Jiashan, Zhejiang, 314100, People’s Republic of China, Email songmeiarticle@163.com; fwjtjh168@sina.com
Background: The present study aimed to construct and validate a nomogram based on clinical metrics to identify CPTB.
Patients and Methods: The present study retrospectively recruited pulmonary tuberculosis (PTB) patients admitted to Jiashan County First People’s Hospital in China from November 2018 to September 2023. PTB patients were classified into the CPTB group and the non-CPTB group based on chest computed tomography findings, and were randomly allocated to the training set (70%) and the validation cohort (30%). The training set and validation set were used to establish and validate nomogram, respectively. Multivariate logistic regression analysis (MLSA) was used to identify the independent risk factors for CPTB in patients with PTB. Statistically significant variables in the MLSA were then used to construct a nomogram predicting CPTB in patients with PTB. The receiver operating characteristic (ROC) curve, calibration curve analysis (CCA), and decision curve analysis (DCA) were used for the evaluation of the nomogram.
Results: A total of 293 PTB patients, including 208 in the training set (85 CPTB) and 85 in the validation set (33 CPTB), were included in this study. Stepwise MLSA showed that sputum smear (≥ 2+), smoking(yes), glycosylated hemoglobin A1c(HbA1c), hemoglobin (HB), and systemic inflammatory response index (SIRI) were independent risk factors for the development of cavitation in patients with PTB. The nomogram identifying the high-risk CPTB patients was successfully established and showed a strong predictive capacity, with area under the curves (AUCs) of 0.875 (95% CI:0.806– 0.909) and 0.848 (95% CI:0.751– 0.946) in the training set and validation set respectively. In addition, the CCA and DCA corroborated the nomogram’s high level of accuracy and clinical applicability within both the training and validation sets.
Conclusion: The constructed nomogram, consisting of sputum smear positivity, smoking, HbA1C, HB, and SIRI, serves as a practical and effective tool for early identification and personalized management of CPTB.
Keywords: pulmonary tuberculosis, cavitation, nomogram