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Background: Patients with chronic obstructive pulmonary disease (COPD) who are hospitalized multiple times for exacerbations face substantially worse clinical outcomes, including higher mortality, faster lung function decline, and reduced quality of life. Identifying these high-risk individuals is essential for early intervention and improved disease management. However, existing predictive models often lack specificity for this population, particularly in inpatient settings. This study aimed to develop a clinically applicable model-based on routinely available inpatient data-to identify patients at risk of exacerbation-related readmission within 12 months following an index hospitalization.
Methods: This retrospective cohort study included patients hospitalized for acute exacerbations of COPD (AECOPD) at a tertiary hospital in China between January 2021 and December 2023. The primary outcome was defined as an AECOPD-related readmission within 12 months following the index hospitalization. Candidate predictors were selected from demographic, clinical, physiological, and laboratory data. A multivariate logistic regression model was constructed and internally validated using bootstrap resampling. Class imbalance was addressed using oversampling, undersampling, and class-weighting techniques. The study was approved by the hospital's ethics committee (Approval No: 2022-058-01).
Results: A total of 1559 inpatients with AECOPD were initially screened. After excluding 272 patients due to incomplete medical records, 1287 patients were included in the final analysis. Seven independent predictors were incorporated into the final model: sex, smoking status, diabetes, coronary artery disease, hemoglobin (Hb) level, forced expiratory volume in one second (FEV1)% predicted, and length of hospital stay (LOHS). The model demonstrated good discriminative ability, with an area under the curve (AUC) of 0.79 (95% CI 0.75-0.83), sensitivity of 76.3%, specificity of 70.2%, and satisfactory calibration. A nomogram and online calculator were developed to facilitate individualized bedside application.
Conclusions: We developed a clinically applicable prediction model to identify hospitalized COPD patients at risk of exacerbation-related readmission within 12 months. The model incorporates routinely available clinical and physiological variables and demonstrated good internal performance. It may support early risk stratification and inform individualized post-discharge management. However, due to the single-center retrospective design and absence of external validation, further studies are needed to confirm its generalizability and real-world clinical utility.
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http://dx.doi.org/10.1186/s40001-025-03042-z | DOI Listing |
Eur J Med Res
August 2025
Department of Respiratory and Critical Care Medicine, Jingzhou Hospital Affiliated to Yangtze University, Jingzhou, Hubei, China.
Background: Patients with chronic obstructive pulmonary disease (COPD) who are hospitalized multiple times for exacerbations face substantially worse clinical outcomes, including higher mortality, faster lung function decline, and reduced quality of life. Identifying these high-risk individuals is essential for early intervention and improved disease management. However, existing predictive models often lack specificity for this population, particularly in inpatient settings.
View Article and Find Full Text PDFInt J Med Sci
April 2025
Department of Pulmonary and Critical Care Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Treatable traits (TTs)" is a precision medicine strategy for the management of chronic airway diseases. However, data on TTs in hospitalized AECOPD patients are limited. This study aimed to determine the prevalence of TTs in Chinese patients hospitalized with AECOPD and which traits predict future exacerbation risk, and to develop an exacerbation prediction model.
View Article and Find Full Text PDF[This corrects the article DOI: 10.1183/23120541.00838-2023.
View Article and Find Full Text PDFERJ Open Res
January 2024
Department of Research and Development, Ciro, Horn, the Netherlands.
Respir Med
December 2023
REVAL - Rehabilitation Research Center, BIOMED - Biomedical Research Institute, Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium. Electronic address:
Objective: Severe acute exacerbations of chronic obstructive pulmonary disease (AECOPD) can have a negative impact on functional capacity, symptoms and health-related quality of life (HRQOL). This study aimed to i) investigate the recovery of muscle strength, functional capacity, symptoms, and HRQOL in patients after a severe AECOPD; ii) compare with matched patients with stable COPD (SCOPD); and iii) assess whether these assessments at hospital discharge could discriminate patients' risk for future events.
Methods: This observational study assessed patients with AECOPD during hospital discharge (T1) and one month after discharge (T2).