Development and external validation of a machine learning model to predict high flow nasal cannula failure
In this study, we developed and externally validated a novel machine learning algorithm that outperforms the ROX Index in predicting failure of HFNC in patients with acute hypoxic respiratory failure. This model could augment clinical decision-making when treating patients with this morbid condition.
Authors
- Dana P. Edelson
- Nirav Shah (ORCID: https://orcid.org/0000-0002-9107-7788)
- Majid Afshar (ORCID: https://orcid.org/0000-0002-6368-4652)
- Christopher Winslow
- Kyle A. Carey (ORCID: https://orcid.org/0000-0002-5038-6074)
- Alexandra B. Spicer (ORCID: https://orcid.org/0000-0001-9195-2143)
- Matthew M. Churpek (ORCID: https://orcid.org/0000-0002-4030-5250)
- Brandon Temte (ORCID: https://orcid.org/0009-0001-0501-3463)
- Emily Gilbert
Institutions
- University of Wisconsin System (US)
- NorthShore University HealthSystem (US)
- University of Wisconsin–Madison (US)
- Loyola University Chicago (US)
- University of Chicago (US)
Publication Details
- Journal
- BMJ Open Respiratory Research
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1136/bmjresp-2025-003355
- Primary Topic
- Respiratory Support and Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Leids Universitair Medisch Centrum