(1) Background: Chronic obstructive pulmonary disease (COPD) is one of the most important respiratory diseases. It is characterised by a progressive course with individual differences in clinical presentation and prognosis. The use of multidimensional indices such as the BODE, eBODE, BODEX, CODEX, ADO, and Charlson Comorbidity Index has been proposed to predict the survival rate of COPD patients. However, there is limited research on the prognostic significance of these indices in predicting long-term survival rates in patients with COPD. The aim of this prospective cohort study was to investigate the prognostic value of the BODE, eBODE, BODEX, CODEX, ADO, COTE and Charlson Comorbidity Index in predicting 5- and 10-year survival in patients with COPD. (2) Methods: A total of 170 patients were included in the study and their clinical and functional characteristics of COPD progression, such as dyspnoea, body mass index and spirometry data, were evaluated. A Kaplan-Meier survival analysis was used to calculate 5- and 10-year survival rates. The predictive value of each index was assessed using Cox proportional hazards regression models. (3) Results: The 5-year survival rate was 62.35% and the 10-year survival rate was 34.70%. The BODE, eBODE, BODEX, CODEX, ADO, COTE and Charlson Comorbidity Index were all significantly associated with the 10-year survival rate of COPD patients ( < 0.05). The hazard ratios (HRs) for these indices were as follows: BODE (HR = 1.30, 95% confidence interval [CI] 1.21-1.39); eBODE (HR = 1.29, 95% CI 1.21-1.37); BODEX (HR = 1.48, 95% CI 1.35-1.63); CODEX (HR = 1.42, 95% CI 1.31-1.54); COTE (HR = 1.55, 95% CI 1.36-1.75); ADO (HR = 1.41, 95% CI 1.29-1.54); and Charlson Comorbidity Index (HR = 1.35, 95% CI 1.22-1.48). (4) Conclusions: The multidimensional indices are a useful clinical tool for assessing the course and prognosis of COPD. These indices can be used to identify patients at a high risk of mortality and guide the management of COPD patients.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10093710PMC
http://dx.doi.org/10.3390/diagnostics13071344DOI Listing

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