Clinical and Inflammatory Phenotypes During Exacerbations Predict In-Hospital Adverse Outcomes in Asthma-COPD Overlap.

BACKGROUND AND

OBJECTIVES

Exacerbations of asthma-chronic obstructive pulmonary disease overlap (EACO) are associated with high mortality, yet the acute-phase heterogeneity remains poorly characterized. This study aimed to identify distinct inflammatory phenotypes of EACO during hospitalization and evaluate their associations with clinical outcomes.

METHODS

A prospective two-centre cohort study enrolled 2444 EACO patients (training and validation cohort). Baseline inflammatory markers and clinical data were collected. Unsupervised k-means clustering identified inflammatory phenotypes, with sensitivity analysis excluding demographic variables. In-hospital clinical outcomes (ICU admission, invasive ventilation, in-hospital mortality) were assessed. Logistic regression and causal mediation analysis evaluated phenotype-outcome associations. A nomogram was developed and validated using receiver operating characteristic curves (AUC).

RESULTS

Three distinct phenotypes were identified: Cluster T1 (neutrophil-to-lymphocyte ratio [NLR]-elevated hypoeosinophilic systemic inflammatory), Cluster T2 (eosinophilic), and Cluster T3 (eosinophil-neutrophil balanced). Cluster T1 exhibited systemic hyperinflammation (elevated white blood cell count, neutrophils, NLR, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6)), and the highest composite adverse outcome rate (24.2%; p < 0.001). Logistic regression revealed absolute neutrophil count (β = 0.38, p < 0.001), D-dimer (β = 0.25, p < 0.001), and absolute lymphocyte count (β = -0.41, p < 0.001) as key outcome predictors, confirmed by causal mediation analysis. The nomogram showed robust predictive performance (AUC training = 0.775; validation = 0.766).

CONCLUSION

Inflammatory phenotypes during EACO predict differential in-hospital outcomes, with neutrophil-dominant phenotypes conferring the highest risk. Early phenotype-based risk stratification using simple blood biomarkers may guide individualized EACO management.