High-flow nasal therapy vs conventional oxygen therapy in mild COVID-19 hypoxaemia: a Bayesian reanalysis of the COVID-HIGH Trial
Year: 2026
Type: article
Abstract: BACKGROUND: Clinical effectiveness of high-flow nasal therapy (HFNT) over conventional oxygen therapy (COT) in patients with mild COVID-19-related acute hypoxaemic respiratory failure (AHRF) remains uncertain. The COVID-HIGH trial did not demonstrate statistically significant benefits of HFNT over COT. However, the trial was slightly underpowered, and the event rate lower-than-expected. Bayesian methods provide deeper insight by incorporating prior knowledge and quantifying uncertainty intuitively. This analysis aimed to quantify the probability of benefit or harm associated with HFNT, adopting a Bayesian approach. METHODS: We performed a Bayesian reanalysis of the COVID-HIGH trial (NCT, which randomised 364 patients with PaO₂/FiO₂ between 200-300 mmHg to receive HFNT or COT. The primary outcome was escalation of respiratory support (continuous positive airway pressure, noninvasive ventilation or invasive mechanical ventilation) within 28 days. A key secondary outcome was clinical recovery at day 14. Bayesian logistic models with noninformative and informative priors were used to estimate the posterior probability of treatment effects. RESULTS: Escalation of respiratory support occurred in 23.6% (HFNT) versus 30.2% (COT) (risk difference - 6.6%, 95% CI - 15.1 to 2.1; p = 0.14). Across a wide range of priors, the posterior probability mass on the beneficial side remained high, generally > 70%, while the proportion on the harm side remained consistently low at ≤ 6% for all models, underscoring a favourable benefit-risk profile. The acute respiratory failure meta-analysis model (OR 0.76, 95% CrI 0.60-0.97), the COVID-19 randomised evidence model (OR 0.76, 95% CrI 0.60-0.97), the COVID-19 observational evidence model (OR 0.60, 95% CrI 0.45-0.80), and the COVID-19 Bayesian meta-analysis mixed evidence model (OR 0.66, 95% CrI 0.52-0.86) showed posterior probability mass on the beneficial side of 70%-94%. Clinical recovery at day 14 occurred in 61.5% (HFNT) versus 53.3% (COT), with 61-73% of posterior probability mass on the clinical benefit side. CONCLUSIONS: This Bayesian re-analysis of the COVID-HIGH trial suggests that HFNT likely reduces escalation of respiratory support and improves clinical recovery in patients with COVID-19 pneumonia and mild hypoxaemia, although the magnitude of benefit remains uncertain and sensitive to prior assumptions. TRIAL REGISTRATION: The trial was prospectively registered in ClinicalTrials.gov on December 7, 2020 (NCT04655638).
Authors: Claudia Crimi, Salvatore Sardo, Alberto Noto, Fabiana Madotto, Mariachiara Ippolito, Santi Nolasco, Raffaele Campisi, Giuseppe Fiorentino, Ioannis Pantazopoulos, Athanasios Chalkias, Alessio Mattei, Raffaele Scala, Enrico Clini, Begum Ergan, Manel Lujan, João Carlos Winck, Antonino Giarratano, Annalisa Carlucci, Cesare Gregoretti, Paolo Groff, Andrea Cortegiani, COVID-HIGH Investigators, Stefano De Vuono, Sokol Berisha, Patrizia Pierini, Maria Rita Taliani, Francesco Balducci, Pasquale Cianci, Alessandra Lignani, Pasquale Imitazione, Angela Mirizzi, Anna Annunziata, Antonietta Coppola, Francesca Simioli, Antonella Marotta, Konstantinos Gourgoulianis, Athanasios Pagonis, Konstantinos Tourlakopoulos, Larissa Greece, Eleni Laou, Alessandro Libra, Ada Vancheri, Nicola Ciancio, Pietro Impellizzeri, Rossella Intravaia, Ernesto Crisafulli, Giulia Sartori, Valentina Musella, Leonello Fuso, Luciana Paladini, Gabriele Valli, José Pedro Boléo-Tomé, Énia Ornelas, Miguel Filipe Guia, Chiara Chiappero, Marco Bardessono, Mauro Mangiapia, Margherita Marelli, Cinzia Gambarini, Dania Mazzola, Alberto Perboni, Sara Demichelis, Massimo Comune, Giulia Rovere, Luca Guidelli, Giacomo Ghinassi, Nicoletta Golfi, Antonella Spacone, Antonietta Esposito, Giorgia Rapacchiale, Antonio Voza, Carlo Fedeli, Sara Sauro, Gianfilippo Gangitano, Ilaria Gessaroli, Davide Francia, Valentina Pinelli, Stefania Artioli, Massimiliano Meazza, Donato Lacedonia, Giulia Scioscia, Marcello Stomaci, Silvia Marani, Mara Bozzoli, Mehmet Nuri Yakar, Elisiana Carpagnano, Valentina Di Lecce, Erika Zanardi, Monica Trentin, Szymon Skoczyński, Aleksandra Oraczewska, Marco Contoli, Brunilda Marku, Paola Noto, Eugenia Di Fazio, Pierachille Santus, Dejan Radovanovic, Luigi Marino
Institutions: University of Catania, Policlinico Universitario di Catania, Azienda Ospedaliero Universitaria Policlinico "G.Rodolico - San Marco", University of Cagliari, University of Messina, Azienda Ospedaliera Universitaria Policlinico "G. Martino", Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Azienda Ospedaliera Universitaria Policlinico "Paolo Giaccone" di Palermo, University of Palermo, University of Thessaly, Tzaneion General Hospital, University of Pennsylvania, Azienda Sanitaria Ospedaliera S.Croce e Carle Cuneo, Ospedale San Donato, University of Modena and Reggio Emilia, Azienda Ospedaliero-Universitaria di Modena, Dokuz Eylül University, Universitat Autònoma de Barcelona, Corporació Sanitària Parc Taulí, Institute of Research and Innovation Parc Tauli, Universidade do Porto, Instituo CUF Porto, Unidade de Investigação e Desenvolvimento Cardiovascular, University of Salento, Ospedale Vito Fazzi, Saint Camillus International University of Health and Medical Sciences, Fondazione Istituto G. Giglio di Cefalù, Azienda Ospedaliera di Perugia
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,079
Funders: University of Pennsylvania, Institute for Translational Medicine and Therapeutics, Università degli Studi di Cagliari, Centres de Recerca de Catalunya, Università di Catania, Università degli Studi di Palermo, Dokuz Eylül Üniversitesi, Universidade do Porto, Università degli Studi di Messina, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Thessaly, Universitat Autònoma de Barcelona, Perelman School of Medicine, University of Pennsylvania
OpenAlex ID: W7130870011