Development and Internal Validation of a Nutrition-Related Indicator-Based Prediction Model for in-Hospital Mortality in Hospitalized Patients with AECOPD.

PURPOSE: To investigate the predictive value of routinely available nutrition-related laboratory indicators for in-hospital mortality in hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and to develop and internally validate a clinically applicable prediction model.

PATIENTS AND METHODS: A retrospective cohort study included 2167 patients hospitalized for AECOPD at the Second People's Hospital of Wuhu between January 1, 2016 and October 21, 2025. Candidate predictors were prespecified based on clinical relevance and previous evidence. Univariable and multivariable logistic regression analyses were performed to identify independent predictors of in-hospital mortality. A prediction model was developed and internally validated using receiver operating characteristic (ROC) analysis, calibration curves with bootstrap resampling, the Hosmer-Lemeshow goodness-of-fit test, and decision curve analysis (DCA).

RESULTS: Among the 2167 patients, 109 (5.0%) died during hospitalization. Multivariable analysis identified five independent predictors of in-hospital mortality: older age (OR = 1.234, 95% CI: 1.077-1.422), lower hemoglobin (OR = 1.095, 95% CI: 1.036-1.152), lower albumin (OR = 1.135, 95% CI: 1.083-1.192), respiratory failure at admission (OR = 6.002, 95% CI: 3.936-9.234), and a history of lung cancer (OR = 4.430, 95% CI: 1.815-9.855). The prediction model achieved good discrimination, with an area under the receiver operating characteristic curve (AUC) of 0.811. The calibration curve demonstrated good agreement between predicted and observed outcomes, and the Hosmer-Lemeshow test indicated good model fit (P = 0.196). Decision curve analysis showed that the model provided greater net benefit than both the treat-all and treat-none strategies across a threshold probability range of approximately 5%-50%.

CONCLUSION: We developed and internally validated a simple prediction model incorporating routinely available nutrition-related laboratory indicators and key clinical characteristics for predicting in-hospital mortality in hospitalized patients with AECOPD. The model demonstrated good discrimination and calibration and may serve as a practical bedside tool for early risk stratification and individualized clinical decision-making. External validation in independent multicenter cohorts is warranted before widespread clinical implementation.