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Chronic obstructive pulmonary disease phenotypes in Turkey: the COPET study--a national, multicenter cross-sectional observational study.
- Source :
- Turkish Journal of Medical Sciences; 2022, Vol. 52 Issue 4, p1130-1138, 9p
- Publication Year :
- 2022
-
Abstract
- Background/aim: While mortality rates decrease in many chronic diseases, it continues to increase in COPD. This situation has led to the need to develop new approaches such as phenotypes in the management of COPD. We aimed to investigate the distribution, characteristics and treatment preference of COPD phenotypes in Turkey. Materials and methods: The study was designed as a national, multicenter, observational and cross-sectional. A total of 1141 stable COPD patients were included in the analysis. Results: The phenotype distribution was as follows: 55.7% nonexacerbators (NON-AE), 25.6% frequent exacerbators without chronic bronchitis (AE NON-CB), 13.9% frequent exacerbators with chronic bronchitis (AE-CB), and 4.8% with asthma and COPD overlap (ACO). The FEV1 values were significantly higher in the ACO and NON-AE than in the AE-CB and AE NON-CB (p < 0.001). The symptom scores, ADO (age, dyspnoea and FEV1) index and the rates of exacerbations were significantly higher in the AE-CB and AE NON-CB phenotypes than in the ACO and NON-AE phenotypes (p < 0.001). Treatment preference in patients with COPD was statistically different among the phenotypes (p < 0.001). Subgroup analysis was performed in terms of emphysema, chronic bronchitis and ACO phenotypes of 1107 patients who had thoracic computed tomography. A total of 202 patients had more than one phenotypic trait, and 149 patients showed no features of a specific phenotype. Conclusion: Most of the phenotype models have tried to classify the patient into a certain phenotype so far. However, we observed that some of the patients with COPD had two or more phenotypes together. Therefore, rather than determining which phenotype the patients are classified in, searching for the phenotypic traits of each patient may enable more effective and individualized treatment. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13000144
- Volume :
- 52
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Turkish Journal of Medical Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 158686587
- Full Text :
- https://doi.org/10.55730/1300-0144.5416