Abstract
BACKGROUND: Inflammation and nutritional status are known to affect outcomes in patients with chronic obstructive pulmonary disease (COPD). However, their prognostic relevance in critically ill COPD patients remains unclear. This study investigated whether C-reactive protein (CRP), serum albumin, and the CRP/albumin ratio (CAR) were associated with in-hospital mortality in ICU patients with COPD. METHODS: We conducted a retrospective cohort study using data from the MIMIC-IV database. Adult ICU patients with a diagnosis of COPD were included. We analyzed CRP, albumin, CAR, glucose, lactate, and creatinine. The primary outcome was in-hospital mortality. Multivariable logistic regression was used to identify variables that were independently associated with in-hospital mortality. Subgroup analyses stratified by age and sex were performed. RESULTS: We included 1000 ICU patients with COPD. In-hospital mortality was 19.6%. In univariate analyses, glucose, creatinine, and lactate levels were significantly higher in non-survivors. In multivariable models, only elevated creatinine (OR 1.60, 95% CI 1.01-2.53) remained independently associated with mortality, while glucose was no longer statistically significant. CRP, albumin, and CAR were not significantly associated with in-hospital mortality. Subgroup analyses showed consistent results across age and sex strata. CONCLUSION: In critically ill COPD patients, glucose and creatinine levels upon ICU admission were independently associated with in-hospital mortality, whereas inflammation- and nutrition-related markers, such as CRP, albumin, and CAR, were not. However, given that albumin is heavily influenced by systemic inflammation, it cannot serve as a standalone nutritional marker in the ICU setting. Composite nutritional scores such as the Nutritional Risk Screening (NRS-2002) or the Global Leadership Initiative on Malnutrition (GLIM), which were not available in the MIMIC-IV database, may provide more accurate assessments. These findings highlight the need for integrated risk models incorporating metabolic and renal parameters for early prognostication.