Prediction of one-year post-discharge mortality in patients with acute exacerbation of chronic obstructive pulmonary disease based on clinical characteristics, blood gas indicators, and duration of non-invasive ventilation.

BACKGROUND: Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) receiving non-invasive ventilation (NIV) represent the most severe group with the poorest prognosis. This study aimed to develop a predictive model for the early identification of patients at high risk of post-discharge mortality, in order to improve patient outcomes.

METHODS: This study retrospectively included 148 AECOPD patients who underwent NIV and divided them into survival and death groups according to survival status within 1 year after discharge. Univariate analysis was conducted to compare baseline characteristics, blood gas indicators, and inflammatory markers between the two groups. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression were further used to screen factors significantly associated with mortality and construct a prediction model. Finally, interaction analysis and survival analysis of the prediction model were performed.

RESULTS: Compared with the survival group, patients in the death group had more severe respiratory dysfunction at admission, a higher comorbidity burden, more severe disease, more severe respiratory impairment and inflammatory response at both admission and discharge, and a longer duration of mechanical ventilation. Cox regression analysis showed that chronic kidney disease (CKD), higher modified Medical Research Council (mMRC) grade, higher Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage, and longer duration of mechanical ventilation were independent risk factors for mortality, while an increase in ΔPaO2 [partial pressure of arterial oxygen (PaO2) at discharge - PaO2 at admission] was a protective factor. The mortality prediction model constructed based on these factors demonstrated excellent performance. Interaction analysis revealed a significant synergistic effect between the prediction model and the Acute Physiology and Chronic Health Evaluation II (APACHE II) score. Survival analysis showed that patients with higher model scores had lower survival rates.

CONCLUSIONS: CKD, mMRC, GOLD, ΔPaO2, and duration of mechanical ventilation were significant predictors of one-year post-discharge mortality in AECOPD patients undergoing NIV. The prediction model demonstrated good predictive performance and showed a significant synergistic effect with the APACHE II score. This study provides a new reference for early identification of high-risk patients and improvement of prognosis in clinical practice.