Time-dependent predictive value of the HACOR score for non-invasive ventilation failure in the emergency department: a prospective cohort study

BACKGROUND: Early recognition of non-invasive ventilation failure in patients with acute respiratory failure in the emergency department is essential to prevent delayed intubation and its associated adverse outcomes. The HACOR score is a pragmatic bedside tool developed to predict non-invasive ventilation failure, most prior investigations have been conducted in intensive care settings and have predominantly relied on single time-point measurements or simple change analyses. In this study, we aimed to evaluate predictive value of early change in the HACOR score for non-invasive ventilation failure in emergency department patients with acute respiratory failure and to examine the temporal nature of this association using Generalized Estimating Equations models. METHODS: This prospective observational cohort study included 106 adult patients. HACOR, National Early Warning Score, National Early Warning Score 2, and Modified Early Warning Score were calculated immediately before and at 1 h after non-invasive ventilation initiation. ΔHACOR was defined as the difference between 1-hour and baseline HACOR scores. The primary outcome was non-invasive ventilation failure. Discriminative performance was assessed using ROC analysis. Logistic regression was used to evaluate the independent association between ΔHACOR and non-invasive ventilation failure. Generalized estimating equations models were constructed to analyze the time-dependent relationship between HACOR and non-invasive ventilation failure. RESULTS: Non-invasive ventilation failure occurred in 50.9% of patients. Baseline clinical variables and scores did not significantly discriminate between success and failure groups. In contrast, 1-hour HACOR (AUC = 0.760, 95% CI 0.667-0.854) and ΔHACOR (AUC = 0.798, 95% CI 0.711-0.885) demonstrated significant predictive performance. Patients with ΔHACOR ≥ 0 exhibited a substantially higher failure rate (74.4%) compared to those with ΔHACOR < 0 (34.9%). Each one-point increase in ΔHACOR was independently associated with failure (OR 1.63, 95% CI 1.31-2.03; p < 0.001). In Generalized Estimating Equations analysis, the HACOR × time interaction remained statistically significant across adjusted models, supporting the prognostic value of serial HACOR assessment. CONCLUSIONS: In emergency department patients receiving non-invasive ventilation, early dynamic changes in HACOR provide superior prognostic information compared with baseline measurements alone. Serial HACOR assessment demonstrated through Generalized Estimating Equations modeling supports potential value of response-guided risk stratification and highlights importance of early reassessment in emergency non-invasive ventilation management.