Predictors of non-invasive ventilation failure in emergency department patients with acute respiratory distress

In the emergency department (ED), non-invasive ventilation (NIV) is an essential therapeutic intervention, especially when treating acute respiratory failure in cases of exacerbations of chronic obstructive pulmonary disease (COPD) and acute cardiogenic pulmonary edema. NIV eliminates the need for costly and invasive mechanical ventilation by lowering respiratory effort and improving gas exchange. However, its success is dependent on several factors, including clinical, blood gas, radiographic, and treatment response predictors. Because clinicians require informed decisions related to the continuation or escalation of NIV, it is necessary to identify these early predictors. This can inform ED clinicians in the early identification and timely intervention for NIV failure through a comprehensive NIV Failure Risk score that integrates these factors. In this review, we examine the predictors for NIV failure, its implications on early decision making, and the potential application of such prediction models in clinical practice, e.g., the HACOR score. A comprehensive literature search was conducted using specific keywords, including "NIV failure," "predictors," and" emergency department." The selection criteria emphasized practical clinical applications and validated prediction tools, integrating evidence to provide clear clinical guidance on NIV failure prediction. The strength of the evidence was evaluated using established clinical practice guidelines. The review process included phases of initial screening, full-text review, and data extraction. It was found that using these predictive tools, clinicians can optimize patient care through acute respiratory distress by improving NIV management and minimizing intubation delays.

Authors

Publication Details

Journal
International Journal of Medicine in Developing Countries
Published
2025-01-01
DOI
https://doi.org/10.24911/ijmdc.51-1741559228
Primary Topic
Respiratory Support and Mechanisms
Type
article
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article

Predictors of non-invasive ventilation failure in emergency department patients with acute respiratory distress

Abdullah Basnawi, Ali Alyami, Ahmed Alzahrani, Abdulaziz Alanazi et al.
International Journal of Medicine in Developing Countries
Respiratory Support and Mechanisms
article

Predictors of non-invasive ventilation failure in emergency department patients with acute respiratory distress

Abdullah Basnawi, Ali Alyami, Ahmed Alzahrani, Abdulaziz Alanazi, Abdulfattah Yahya Alhazmi, Rawan Alomhammed, Hassan Albagshi, Abdulrahman Alquwaynim, Lojain Burejailah
article en

Abstract

In the emergency department (ED), non-invasive ventilation (NIV) is an essential therapeutic intervention, especially when treating acute respiratory failure in cases of exacerbations of chronic obstructive pulmonary disease (COPD) and acute cardiogenic pulmonary edema. NIV eliminates the need for costly and invasive mechanical ventilation by lowering respiratory effort and improving gas exchange. However, its success is dependent on several factors, including clinical, blood gas, radiographic, and treatment response predictors. Because clinicians require informed decisions related to the continuation or escalation of NIV, it is necessary to identify these early predictors. This can inform ED clinicians in the early identification and timely intervention for NIV failure through a comprehensive NIV Failure Risk score that integrates these factors. In this review, we examine the predictors for NIV failure, its implications on early decision making, and the potential application of such prediction models in clinical practice, e.g., the HACOR score. A comprehensive literature search was conducted using specific keywords, including "NIV failure," "predictors," and" emergency department." The selection criteria emphasized practical clinical applications and validated prediction tools, integrating evidence to provide clear clinical guidance on NIV failure prediction. The strength of the evidence was evaluated using established clinical practice guidelines. The review process included phases of initial screening, full-text review, and data extraction. It was found that using these predictive tools, clinicians can optimize patient care through acute respiratory distress by improving NIV management and minimizing intubation delays.

International Journal of Medicine in Developing Countries
Openalex Percentile: Top 88%
Respiratory Support and Mechanisms
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