Dear Editor, High-flow nasal cannula (HFNC) therapy is a form of non-invasive respiratory support that delivers heated, humidified gas at flow rates exceeding 20 L/min [1]. The technical feasibility of delivering different HFNC flow rates during inspiration and expiration (bi-flow HFNC) was recently demonstrated in a proof-of-concept study in healthy volunteers [2]. Here, we aimed to investigate whether the use of bi-flow HFNC could potentially produce clinically relevant benefits in patients suffering from acute hypoxemic respiratory failure (AHRF) or sepsis. To do this, we used detailed physiological data from three previous studies that administered HFNC to patients at multiple flow rates [3–5]. Based on these data, we used a high-fidelity computational simulator of the cardiopulmonary system to create digital twins of 13 AHRF patients and 17 sepsis patients. Global optimisation algorithms were used to match the outputs of each digital twin to arterial blood gases ( PaO2 and PaCO2), esophageal pressure swing (ΔPes), and tidal volume (VT) measured in each patient at two different flow rates (see SM for full details). Comparisons of digital twin outputs with patient measurements are shown in Figs. S4 and

Digital twins of acute hypoxemic respiratory failure and sepsis patients suggest potential benefits of bi-level high flow nasal cannula therapy

Spadaro S
Membro del Collaboration Group
2026

Abstract

Dear Editor, High-flow nasal cannula (HFNC) therapy is a form of non-invasive respiratory support that delivers heated, humidified gas at flow rates exceeding 20 L/min [1]. The technical feasibility of delivering different HFNC flow rates during inspiration and expiration (bi-flow HFNC) was recently demonstrated in a proof-of-concept study in healthy volunteers [2]. Here, we aimed to investigate whether the use of bi-flow HFNC could potentially produce clinically relevant benefits in patients suffering from acute hypoxemic respiratory failure (AHRF) or sepsis. To do this, we used detailed physiological data from three previous studies that administered HFNC to patients at multiple flow rates [3–5]. Based on these data, we used a high-fidelity computational simulator of the cardiopulmonary system to create digital twins of 13 AHRF patients and 17 sepsis patients. Global optimisation algorithms were used to match the outputs of each digital twin to arterial blood gases ( PaO2 and PaCO2), esophageal pressure swing (ΔPes), and tidal volume (VT) measured in each patient at two different flow rates (see SM for full details). Comparisons of digital twin outputs with patient measurements are shown in Figs. S4 and
2026
Shamohammadi, H; Mauri, T; Bates, Dg; HFNC-BiFlow study, Group; Spadaro, S
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2613894
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