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慢性阻塞性肺疾病合并诺卡菌感染患者的诊断模型:一项基于临床特征和危险因素的研究

Diagnostic model for COPD patients with nocardia infection: a study based on clinical features and risk factors.

作者信息

Zhang Kai, Yang Kangli, Wang Hongmin

机构信息

Department of Respiratory Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Department of Respiratory Medicine, The First Affiliated Hospital of Zhengzhou University, No. 1 Longhu Middle Ring Road, Zhengzhou 450000, China.

出版信息

Ther Adv Respir Dis. 2025 Jan-Dec;19:17534666251359139. doi: 10.1177/17534666251359139. Epub 2025 Jul 21.

Abstract

BACKGROUND

The escalating morbidity and mortality of chronic obstructive pulmonary disease (COPD) necessitates improved diagnostic approaches for comorbid infections. COPD patients exhibit heightened susceptibility to opportunistic pathogens like Nocardia species due to compromised airway defenses and frequent glucocorticoid/immuno-suppressant use. Despite its clinical significance, Nocardia infection remains diagnostically challenging due to nonspecific presentations and imaging features.

OBJECTIVES

To develop and validate a diagnostic model integrating clinical characteristics and risk factors for COPD complicated by Nocardia infection.

DESIGN

A retrospective analysis was conducted on clinical data from 586 patients diagnosed with COPD and Nocardia infection, including clinical symptoms, laboratory tests, imaging findings, and treatment outcomes. Patients were screened according to inclusion and exclusion criteria and divided into two groups: COPD with Nocardia infection group (infection group) and COPD-only group (control group).

METHODS

This retrospective study analyzed 586 COPD patients (2019-2024), stratified into Nocardia-infected ( = 289) and noninfected ( = 297) cohorts. Demographic, laboratory, pulmonary function, and imaging data were collected. Multivariate logistic regression identified independent predictors, which informed a nomogram model. Model performance was assessed via concordance index (C-index), calibration curves, and ROC analysis.

RESULTS

Independent risk factors included hemoptysis (OR = 1.99, 95% CI: 0.76-5.26), lymphocyte count (OR = 6.81, 95% CI: 4.06-11.42), hemoglobin (OR = 1.01, 95% CI: 0.99-1.03), and pulmonary function parameters (FEV₁/FVC ratio OR = 12.47, 95% CI: 1.25-124.16). The model demonstrated excellent discrimination (C-index: 0.895 infected, 0.829 noninfected) and calibration (mean absolute error: 0.127-0.170). ROC analysis revealed AUCs of 0.896 (95% CI: 0.90-0.97) and 0.830 (95% CI: 0.77-0.89) for infected and noninfected groups, respectively.

CONCLUSION

This validated nomogram provides a clinically actionable tool for early Nocardia detection in COPD patients, addressing a critical diagnostic gap. External validation is warranted to confirm generalizability.

摘要

背景

慢性阻塞性肺疾病(COPD)的发病率和死亡率不断攀升,因此需要改进对合并感染的诊断方法。由于气道防御功能受损以及频繁使用糖皮质激素/免疫抑制剂,COPD患者对诺卡菌属等机会性病原体的易感性增加。尽管诺卡菌感染具有临床意义,但由于其临床表现和影像学特征不具特异性,其诊断仍具有挑战性。

目的

建立并验证一个整合临床特征和危险因素的诊断模型,用于诊断合并诺卡菌感染的COPD。

设计

对586例诊断为COPD合并诺卡菌感染的患者的临床资料进行回顾性分析,包括临床症状、实验室检查、影像学检查结果及治疗结果。根据纳入和排除标准对患者进行筛选,并分为两组:COPD合并诺卡菌感染组(感染组)和单纯COPD组(对照组)。

方法

这项回顾性研究分析了586例COPD患者(2019 - 2024年),分为诺卡菌感染组(n = 289)和未感染组(n = 297)。收集了人口统计学、实验室、肺功能和影像学数据。多因素逻辑回归确定了独立预测因素,并据此构建了列线图模型。通过一致性指数(C指数)、校准曲线和ROC分析评估模型性能。

结果

独立危险因素包括咯血(OR = 1.99,95%CI:0.76 - 5.26)、淋巴细胞计数(OR = 6.81,95%CI:4.06 - 11.42)、血红蛋白(OR = 1.01,95%CI:0.99 - 1.03)和肺功能参数(FEV₁/FVC比值OR = 12.47,95%CI:1.25 - 124.16)。该模型显示出良好的区分度(感染组C指数:0.895,未感染组0.829)和校准度(平均绝对误差:0.127 - 0.170)。ROC分析显示,感染组和未感染组的AUC分别为0.896(95%CI:0.90 - 0.97)和0.830(95%CI:0.77 - 0.89)。

结论

这个经过验证的列线图为COPD患者早期检测诺卡菌提供了一个具有临床可操作性的工具,填补了关键的诊断空白。需要进行外部验证以确认其普遍性。

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