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Background <p>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.</p> Methods <p>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&#xa0;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.</p> Results <p>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 &lt; 0 (34.9%). Each one-point increase in ΔHACOR was independently associated with failure (OR 1.63, 95% CI 1.31–2.03; <i>p</i> &lt; 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.</p> Conclusions <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月28日

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  • B. Doğan,
  • M. Yazla,
  • B. Kaya,
  • E. Çelikel,
  • A. Kablan,
  • A. B. Erdem

摘要

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.