ArticleJournal of intensive care2020
Early prediction of high flow nasal cannula therapy outcomes using a modified ROX index incorporating heart rate.
Article in Journal of intensive care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 4 of them syntheses that pooled it.
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Who cites it
61 citing papers in PubMed, 4 syntheses or guidelines pooled it, 108 citations in OpenAlex.
- Performance of the ROX index in predicting high flow nasal cannula failure in COVID-19 patients: a systematic review and meta-analysis.Critical care (London, England) · 2023Pooled it
- The ROX index as a predictor of high-flow nasal cannula outcome in pneumonia patients with acute hypoxemic respiratory failure: a systematic review and meta-analysis.BMC pulmonary medicine · 2022Pooled it
- The value of ROX index in predicting the outcome of high flow nasal cannula: a systematic review and meta-analysis.Respiratory research · 2022Pooled it
- Effectiveness of the use of a high-flow nasal cannula to treat COVID-19 patients and risk factors for failure: a meta-analysis.Therapeutic advances in respiratory diseasePooled it
- Edge Detection Algorithm-Based Lung Ultrasound in Evaluation of Efficacy of High-Flow Oxygen Therapy on Critical Lung Injury.Computational and mathematical methods in medicine · 2022Trial
- Development of a predictive model for high-flow nasal cannula treatment failure in emergency department patients with acute heart failure: a retrospective secondary data analysis.Journal of Korean biological nursing science · 2026Article
- Article
- Prediction of high-flow nasal cannula failure in critically ill patients: a narrative review.Journal of intensive care · 2026Review
- Inhaled L-Epinephrine As a Rescue Therapy in Critical Bronchiolitis.Critical care explorations · 2026Article
- High-Flow Nasal Cannula Oxygen Therapy in Perioperative Respiratory Care: Application and Prospects.Journal of multidisciplinary healthcare · 2026Review
- Evaluating the effect of heart and respiratory rate measurement errors on the ability to predict the outcome of high flow nasal cannula therapy: a multi-centre study.Critical care (London, England) · 2025Article
- Development and external validation of a machine learning model to predict high flow nasal cannula failure.BMJ open respiratory research · 2025Article
- Early Prediction of High-flow Nasal Cannula Failure Using Pediatric-modified HACOR Score in Children with Acute Hypoxemic Respiratory Distress: A Prospective Observational Study.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025Article
- Survival prediction model for hypoxemic patients receiving post-extubation oxygen therapy after invasive ventilation: based on the MIMIC database.Journal of thoracic disease · 2025Article
- Real-time prediction of HFNC treatment failure in acute hypoxemic respiratory failure using machine learning.Scientific reports · 2025Article
- Implementation of High-Flow Oxygen Therapy in a Surgical High-Dependency Unit: A Cohort Study.Cureus · 2025Article
- Comparison of ROX index with modified indices incorporating heart rate, flow rate, and PaOEuropean journal of medical research · 2025Article
- Machine learning models compared with current clinical indices to predict the outcome of high flow nasal cannula therapy in acute hypoxemic respiratory failure.Critical care (London, England) · 2025Article
- Patient-Self Inflicted Lung Injury (P-SILI): An Insight into the Pathophysiology of Lung Injury and Management.Journal of clinical medicine · 2025Review
- Tailored Predictive Indicators for Weaning Success from High-Flow Nasal Cannula in Postoperative Hypoxemic Patients.Life (Basel, Switzerland) · 2025Article
1 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe ROX index (ratio of pulse oximetry/FIO
methodsWe performed a prospective observational cohort study of 145 patients treated with HFNC. ROX-HR index was defined as the ratio of ROX index over HR (beats/min), multiplied by a factor of 100. Evaluation was performed using area under the receiving operating characteristic curve (AUROC) and cutoffs assessed for prediction of HFNC failure: defined as the need for mechanical ventilation.
resultsNinety-nine (68.3%) and 46 (31.7%) patients were initiated on HFNC for acute hypoxemic respiratory failure and following a planned extubation, respectively. The majority (86.9%) of patients had pneumonia as a primary diagnosis, and 85 (56.6%) patients were immunocompromised. Sixty-one (42.1%) patients required intubation (HFNC failure). Amongst patients on HFNC for acute respiratory failure, HFNC failure was associated with a lower ROX and ROX-HR index recorded at time points between 1 and 48 h. Within the first 12 h, both indices performed with the highest AUROC at 10 h as follows: 0.723 (95% CI 0.605-0.840) and 0.739 (95% CI 0.626-0.853) for the ROX and ROX-HR index respectively. A ROX-HR index of > 6.80 was significantly associated with a lower risk of HFNC failure (hazard ratio 0.301 (95% CI 0.143-0.663)) at 10 h. This association was also observed at 2, 6, 18, and 24h, even with correction for potential confounding factors. For HFNC initiated post-extubation, only the ROX-HR index remained significantly associated with HFNC failure at all recorded time points between 1 and 24 h. A ROX-HR > 8.00 at 10 h was significantly associated with a lower risk of HFNC failure (hazard ratio 0.176 (95% CI 0.051-0.604)).
conclusionWhile validation studies are required, the ROX-HR index appears to be a promising tool for early identification of treatment failure in patients initiated on HFNC for acute hypoxemic respiratory failure or as a preventative treatment after a planned extubation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.