A three-axis serum biomarker model integrating airway neutrophilic inflammation (IL-8, MMP-9), immune exhaustion (PD-1), and subclinical myocardial injury (hs-cTnI) for predicting 90-day cardiopulmonary events

Abstract

Background
Acute Exacerbations of Chronic Obstructive Pulmonary Disease (AECOPD) trigger systemic inflammation and immune dysregulation, posing a significant risk for subsequent cardiopulmonary events. Current risk stratification tools lack biological granularity. We hypothesized that integrating biomarkers of airway inflammation, immune exhaustion, and subclinical cardiac injury would improve prognostication.


Methods
In this prospective cohort study, 228 AECOPD patients and 80 healthy controls were enrolled. Serum IL-8, MMP-9, PD-1, and hs-cTnI were serially measured at admission (T1), pre-discharge (T2), and 90-day follow-up (T3). A mechanistic three-axis composite score was developed: Axis 1 (Airway Injury) elevated IL-8 and MMP-9; Axis 2 (Immune Exhaustion) elevated PD-1; Axis 3 (Cardiac Stress) elevated hs-cTnI. The primary endpoint was 90-day Major Adverse Cardiopulmonary Events (MACCE).


Results

Patients experiencing MACCE (
n
 = 46, 20.2%) exhibited sustained elevation of IL-8, PD-1, and hs-cTnI at T3 (all
P
 < 0.001). The three-axis model demonstrated superior discrimination compared to clinical-only models (AUC 0.82 vs. 0.63,
P
 < 0.01) and outperformed the best single biomarker (hs-cTnI AUC 0.74). Risk stratification revealed a graded increase in 90-day MACCE incidence: low-risk (score 0) 10.8%, intermediate-risk (score 1) 21.1%, and high-risk (score ≥ 2) 31.7% (
P
 = 0.009). High-risk patients had a 3.00-fold increased risk of events (95% CI 1.23–7.32).



Conclusions
Mechanistically, the integration of these specific pathophysiological axes provides a superior predictive framework for early prediction of 90-day cardiopulmonary outcomes in AECOPD. This scoring system offers a mechanistically grounded tool for identifying high-risk phenotypes.