Analysis of factors influencing bronchiectasis patients with active pulmonary tuberculosis and development of a nomogram prediction model

列线图 支气管扩张 肺结核 医学 肺结核 内科学 病理
作者
Yi Yang,Lianfang Du,Weilong Ye,Weifeng Liao,Zhenzhen Zheng,Xiaoxi Lin,F. Chen,Jingjing Pan,Bainian Chen,Riken Chen,Weimin Yao
出处
期刊:Frontiers in Medicine [Frontiers Media]
卷期号:11
标识
DOI:10.3389/fmed.2024.1457048
摘要

Background To identify the risk factors for bronchiectasis patients with active pulmonary tuberculosis (APTB) and to develop a predictive nomogram model for estimating the risk of APTB in bronchiectasis patients. Methods A retrospective cohort study was conducted on 16,750 bronchiectasis patients hospitalized at the Affiliated Hospital of Guangdong Medical University and the Second Affiliated Hospital of Guangdong Medical University between January 2019 and December 2023. The 390 patients with APTB were classified as the case group, while 818 patients were randomly sampled by computer at a 1:20 ratio from the 16,360 patients with other infections to serve as the control group. Relevant indicators potentially leading to APTB in bronchiectasis patients were collected. Patients were categorized into APTB and inactive pulmonary tuberculosis (IPTB) groups based on the presence of tuberculosis. The general characteristics of both groups were compared. Variables were screened using the least absolute shrinkage and selection operator (LASSO) analysis, followed by multivariate logistic regression analysis. A nomogram model was established based on the analysis results. The model’s predictive performance was evaluated using calibration curves, C-index, and ROC curves, and internal validation was performed using the bootstrap method. Results LASSO analysis identified 28 potential risk factors. Multivariate analysis showed that age, gender, TC, ALB, MCV, FIB, PDW, LYM, hemoptysis, and hypertension are independent risk factors for bronchiectasis patients with APTB ( p < 0.05). The nomogram demonstrated strong calibration and discrimination, with a C-index of 0.745 (95% CI: 0.715–0.775) and an AUC of 0.744 for the ROC curve. Internal validation using the bootstrap method produced a C-index of 0.738, further confirming the model’s robustness. Conclusion The nomogram model, developed using common clinical serological characteristics, holds significant clinical value for assessing the risk of APTB in bronchiectasis patients.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
haowu发布了新的文献求助10
刚刚
orixero应助Zxc采纳,获得10
1秒前
英俊的铭应助good233采纳,获得10
1秒前
江屿发布了新的文献求助10
1秒前
Linzy发布了新的文献求助10
1秒前
2秒前
Strongly完成签到,获得积分10
2秒前
orixero应助zcc采纳,获得10
2秒前
吕吕发布了新的文献求助10
3秒前
4秒前
4秒前
zfy完成签到,获得积分20
4秒前
左丘幼旋1发布了新的文献求助10
5秒前
香蕉觅云应助冰菱采纳,获得10
5秒前
Meredith发布了新的文献求助10
5秒前
6秒前
6秒前
小蘑菇应助城九寒采纳,获得10
8秒前
8秒前
曲奇饼干发布了新的文献求助10
9秒前
9秒前
li完成签到,获得积分10
9秒前
10秒前
11秒前
11秒前
左丘幼旋1完成签到,获得积分10
11秒前
11秒前
科研通AI2S应助吕吕采纳,获得10
11秒前
12秒前
12秒前
13秒前
13秒前
67号发布了新的文献求助10
14秒前
SciGPT应助force采纳,获得10
14秒前
玩家X发布了新的文献求助10
15秒前
隐形曼青应助kingmantj采纳,获得10
16秒前
PACEPANG完成签到,获得积分10
16秒前
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Developing Genetic Editing Tools for Lysobacter 2000
卤化钙钛矿人工突触的研究 2000
Моделирование процессов самоорганизации в кристаллообразующих системах 1000
History of U.S. Space Surveillance and Satellite Cataloging 1000
Adhesion Science: Principles & Practice 800
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6522170
求助须知:如何正确求助?哪些是违规求助? 8315427
关于积分的说明 17789369
捐赠科研通 5624292
什么是DOI,文献DOI怎么找? 2927863
邀请新用户注册赠送积分活动 1904662
关于科研通互助平台的介绍 1764695