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Background <p>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.</p> Methods <p>We performed a Bayesian reanalysis of the COVID-HIGH trial (NCT, which randomised 364 patients with PaO₂/FiO₂ between 200–300&#xa0;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&#xa0;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.</p> Results <p>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 &gt; 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.</p> Conclusions <p>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.</p> Trial registration <p>The trial was prospectively registered in ClinicalTrials.gov on December 7, 2020 (NCT04655638).</p>

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High-flow nasal therapy vs conventional oxygen therapy in mild COVID-19 hypoxaemia: a Bayesian reanalysis of the COVID-HIGH Trial

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  • 发表日期：

    2026年2月21日

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  • 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,
  • 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

摘要

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).