Abstract
This study aims to evaluate risk factors for readmission within 6 months after acute exacerbation of chronic obstructive pulmonary disease (COPD) and to develop a multifactorial predictive model. A total of 151 patients with acute exacerbation of COPD, admitted to our hospital from October 2021 to December 2023, were included in this retrospective analysis. Data on baseline characteristics, medical history, lung function, lifestyle, comorbidities, inflammatory markers, and treatment adherence were obtained from electronic medical records to identify risk factors associated with readmission. Univariate and multivariate logistic regression analyses were used to identify independent risk factors, construct a predictive model, and assess its predictive efficacy using the receiver operating characteristic (ROC) curve. Patients in the readmission group were older (69.8 ± 9.5 years vs 65.2 ± 8.4 years, P = .048), had a higher proportion of males (76.4% vs 59.5%, P = .032), higher body mass index (25.3 ± 3.8 kg/m2 vs 23.1 ± 3.2 kg/m2, P = .018), more frequent exacerbations (3.2 ± 1.0 episodes vs 1.5 ± 0.8 episodes, P = .009), longer disease duration (12.1 ± 7.3 years vs 8.4 ± 5.7 years, P = .043), and higher GOLD classification (70% in stages III-IV vs 50%, P = .043) and BODE index (5.1 ± 1.4 vs 3.8 ± 1.2, P = .022). Additionally, they had a higher prevalence of cardiovascular comorbidities (55.6% vs 31.6%, P = .015), lower FEV1 levels (45.3 ± 10.1% vs 52.7 ± 8.5%, P = .033), higher levels of C-reactive protein (CRP) (15.2 ± 6.5 mg/L vs 10.4 ± 4.9 mg/L, P = .005), fractional exhaled nitric oxide (FeNO) (32.5 ± 10.4 ppb vs 26.7 ± 8.9 ppb, P = .03), and end-tidal carbon dioxide partial pressure (PetCO2) (40.1 ± 6.3 mm Hg vs 36.2 ± 5.7 mm Hg, P = .028), all of which were significant independent risk factors for readmission. The area under the ROC curve for the multivariate regression model was 0.801, indicating good predictive efficacy. This study evaluates multiple factors affecting readmission risk after acute exacerbation of COPD, highlighting the importance of early identification of high-risk patients and constructing an effective predictive model. Further large-sample, multi-center studies are needed to validate these findings and explore personalized interventions to reduce readmission rates and improve the quality of life for COPD patients.