A nomogram-based prediction model for dysphagia in patients with chronic obstructive pulmonary disease: A cross-sectional study.

Abstract

AIM AND OBJECTIVES:

To investigate the prevalence of dysphagia in patients with COPD, identify the risk factors for dysphagia, develop a visual clinical prediction model and quantitatively predict the probability of developing dysphagia.

BACKGROUND:

Patients with COPD are at high risk of dysphagia, which is strongly linked to the acute exacerbation of their condition. The use of effective tools to predict its risk may contribute to the early identification and treatment of dysphagia in patients with COPD.

DESIGN:

A cross-sectional design.

METHODS:

From July 2021 to April 2023, we enrolled 405 patients with COPD for this study. The clinical prediction model was constructed according to the results of a univariate analysis and a logistic regression analysis, evaluated by discrimination, calibration and decision curve analysis and visualized by a nomogram. This study was reported using the TRIPOD checklist.

RESULTS:

In total, 405 patients with COPD experienced dysphagia with a prevalence of 59.01%. A visual prediction model was constructed based on age, whether combined with cerebrovascular disease, chronic pulmonary heart disease, acute exacerbation of COPD, home noninvasive positive pressure ventilation, dyspnoea level and xerostomia level. The model exhibited excellent discrimination at an AUC of .879. Calibration curve analysis indicated a good agreement between experimental and predicted values, and the decision curve analysis showed a high clinical utility.

CONCLUSION:

The model we devised may be used in clinical settings to predict the occurrence of dysphagia in patients with COPD at an early stage.

RELEVANCE TO CLINICAL PRACTICE:

The model can help nursing staff to calculate the risk probability of dysphagia in patients with COPD, formulate personalized preventive care measures for high-risk groups as soon as possible to achieve early prevention or delay of dysphagia and its related complications and improve the prognosis.

PATIENT OR PUBLIC CONTRIBUTION:

No patient or public contribution.

• Authors: Ying Fan, Yuxin Shi, Yunyun Wu, Fang Yang, Chao Zhang, Mengjun Gu, Pengchao Hu, Wenjie Duan, Hongli Wang, Yumei Zhou
• Journal: Journal of clinical nursing (J Clin Nurs) (May 19 2024) ISSN: 1365-2702 [Electronic] England
• PMID: 38764243 (Publication Type: Journal Article)
• Copyright: © 2024 John Wiley & Sons Ltd.