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Observational study finds strong correlations between IL-8, CRP levels, and lung function in patients with COPD, indicating potential clinical implications.
The aim of the study – to observe the relationship between serum levels of interleukin 8 (IL-8), C-reactive protein (CRP) and lung function in patients with chronic obstructive pulmonary disease (COPD). Materials and methods. The prospective study involved 122 patients with an established diagnosis of COPD (main group) and 20 patients without this disease and other pulmonary and severe somatic diseases (control group). The selection of patients in the polyclinic was carried out during spontaneous routine or scheduled visits. Selected study participants completed COPD questionnaires (Chronic Airways Diseases, A Guide for Primary Care Physicians, 2005; COPD Assessment Test) and underwent a complete examination, after which they were diagnosed with COPD. Spirometry was performed using a portable ultrasonic spirometer. The level of IL-8 in the blood was determined by ELISA, CRP - immunoturbidimetric method. Results. The average age of patients with COPD was 55.9±4.4 years, men accounted for 59.0%, women – 41.0%, smokers – 57.4%. The indices of FEV1, FVC and FEV1/FVC in patients with COPD were lower than the control values by 55.72% (p=0.001), 43.23% (p=0.001), and 35.28% (p=0.036), respectively. The concentration of CRP and IL-8 exceeded the control by 66.30% (p=0.015) and 35.33% (p=0.001), respectively. CRP correlated with FEV1 mean feedback (r=-0.699, p<0.01), FVC (r=-0.702, p<0.01) and FEV1/FVC (r=-0.756, p<0.01) strong connection. IL-8 correlated strongly with all parameters of lung function: with FEV1 – r=-0.801 (p<0.001); with FVC – r=-0.711 (p<0.01); with FEV1/FVC – r=-0.730 (p<0.01). Conclusion. The results obtained confirmed elevated levels of inflammatory markers and the presence of a statistically significant strong inverse correlation between these markers and lung function parameters. Further studies are needed to confirm the results and make recommendations for identifying clinical phenotypes.
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İskanderova et al. (2024) studied this question.
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