Analysis of diagnostic delay and its influencing factors in patients with chronic obstructive pulmonary disease: a cross-sectional study
Abstract To explore the status of diagnostic delay and to clarify its potentially influencing factors in patients with chronic obstructive pulmonary disease (COPD). A cross-sectional study was conducted in a Chinese tertiary hospital between July 2019 and February 2020. A total of 408 eligible outpa...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/014d90b3639043f395f604b53d5f8652 |
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| Sumario: | Abstract To explore the status of diagnostic delay and to clarify its potentially influencing factors in patients with chronic obstructive pulmonary disease (COPD). A cross-sectional study was conducted in a Chinese tertiary hospital between July 2019 and February 2020. A total of 408 eligible outpatients with COPD were recruited, and relevant data were collected in the form of questionnaires. Diagnostic delay was compared among different characteristics using the Wilcoxon test and Kruskal–Wallis H test. Multivariable linear regression analysis was performed to determine the factors related to diagnostic delay. The median (interquartile range [IQR]) duration of diagnostic delay was 230 (50–720) days. The proportions of COPD patients who chose tertiary, secondary, and first-level hospitals for the first visit were 53.7%, 29.9%, and 16.4%, respectively. Additionally, the proportions of patients who underwent pulmonary function tests for the first visit in tertiary, secondary, and first-level hospitals were 74.0%, 24.6%, and 1.5% (p < 0.001), respectively. In terms of characteristics related to diagnostic delay, there was a significant difference in residence, resident manner, COPD assessment test (CAT) score, modified Medical British Research Council (mMRC) dyspnea scale, age, forced expiratory volume in one second (FEV1) % predicted, and years of education (all p < 0.01). Linear regression analysis showed that significant predictors of diagnostic delay included FEV1% predicted (p < 0.05), resident manner (p < 0.001), and years of education (p < 0.01). Our study indicates that varying degrees of diagnostic delay may exist in patients with COPD. Measures are needed to intervene in the potential factors associated with diagnostic delay. |
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