AORI-HAP：喘息増悪における院内有害事象を予測するための多次元リスク指数

Despite therapeutic advancements, asthma exacerbations (AEs) remain a major clinical challenge, with immune-inflammatory patterns incompletely characterized. Current guidelines lack robust multidimensional tools for predicting in-hospital adverse outcomes.

To develop and validate the Asthma Outcome Risk Index for Hospitalized Patients (AORI-HAP), integrating multidimensional predictors, and investigate immune-inflammatory mechanisms underlying adverse outcomes.

This real-world cohort study enrolled hospitalized AE patients. Univariate analyses identified associations between multidimensional biomarkers and composite outcome (death, ICU admission, invasive ventilation). LASSO logistic regression derived the AORI-HAP, stratifying patients into risk categories. Mediation analysis elucidated mechanistic contributions to adverse outcomes.

The AORI-HAP identified five independent predictors of adverse outcomes: elevated neutrophil-to-lymphocyte ratio (NLR > 8.3, OR = 9.26, p < 0.001), increased AST/ALT ratio (>1.41, OR = 3.73, p < 0.001), smoking history ≥10 pack-years (OR = 3.54, p = 0.005), D-Dimer levels ≥5 mg/L (OR = 3.25, p = 0.002), and fasting glucose ≥7 mmol/L (OR = 3.20, p = 0.001). Each 3-point increment in the AORI-HAP score corresponded to an additional hospital day (β = 0.997, 95% CI: 0.78-1.21, p < 0.001), with the model demonstrating strong predictive performance (AUC 0.91, 95% CI 0.86-0.95; sensitivity 90.5%, specificity 69.6%). Mediation analysis revealed that NLR accounted for 26.7% of the total effect linking high-risk status to composite adverse outcome, underscoring its mechanistic relevance.

AORI-HAP facilitates early risk stratification at admission and personalized management in hospitalized asthma patients. NLR's mediating role underscores its utility as a predictive biomarker and potential therapeutic target.