Department of Critical Care Medicine,Ruijin Hospital,Shanghai Jiao Tong University School of Medicine
Shanghai, Shanghai Municipality, 200025, China
NCT Number: NCT07366541
This prospective, single-center, two-stage translational study develops and validates a physiology-informed dual-domain model for ultra-early (30-minute) prediction of high-flow nasal oxygen (HFNO) failure in patients with acute hypoxemic respiratory failure. The study includes a physiological validation cohort (n=24) to anchor the EIT-derived Flow Index (EFI) as a marker of inspiratory effort, followed by a temporally separated clinical derivation cohort (n=57) and independent validation cohort (n=58). Candidate predictors are screened from 1,328 clinical features. The final dual-domain model integrates persistent physiological burden (baseline PaCO₂ and 30-minute EFI) with short-term dynamic adaptation (ΔRR and ΔSpO₂ over 30 minutes). The model's discrimination is tested prospectively without refitting.
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Notify Me18 year–90 year
All sexes
Observational
Shanghai, Shanghai Municipality, 200025, China
Detailed Description
This was a single-center, prospective, two-stage translational study conducted at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. The study comprised three integrated components:
Patient-level analyses were performed to identify two prespecified domains of early HFNO failure:
Persistent abnormality (physiological burden that remained abnormal after accounting for baseline): evaluated by analysis of covariance (ANCOVA) for 30-minute variables adjusted for baseline values.
Divergent short-term response trajectory (different evolution between success and failure groups): evaluated by generalized estimating equations (GEE) with time-by-group interactions across baseline and 30 minutes.
A multivariable logistic regression model was constructed in the derivation cohort incorporating baseline PaCO₂, 30-minute EFI, ΔRR (change in respiratory rate), and ΔSpO₂ (change in peripheral oxygen saturation). An exploratory reference model using ΔPaO₂ instead of ΔSpO₂ was also evaluated.
Total enrollment: 164 participants (24 physiological validation + 115 clinical HFNO participants [derivation 57 + validation 58] + 25 screened but excluded as detailed in the study flow diagram).
The study was approved by the Ruijin Hospital Ethics Committee (Reference Nos. [2025]30 and [2025]232). All participants provided written informed consent.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
(must meet all):
Exclusion criteria
Patients received pressure support ventilation at three sequentially adjusted levels (PSmin, PSbase, PSmax). Breathing parameters were continuously monitored using an electrical impedance tomography (EIT) device, and inspiratory effort was invasively measured via an esophageal pressure catheter.
PulmoVista 500 EIT device (Dräger Medical, Lübeck, Germany) was used for continuous real-time monitoring of regional lung ventilation.
Patients received HFNO as part of standard clinical care for acute hypoxemic respiratory failure. The treatment was titrated by the clinical team based on physiological parameters (SpO₂, RR, ABG), aiming to maintain SpO₂ ≥ 92% and reduce signs of respiratory distress.
Patients received standard-of-care HFNO for AHRF. Additionally, a PulmoVista 500 EIT device was used to monitor lung ventilation and derive the EFI at baseline and 30 minutes.
Time frame: within 30 minutes after HFNO initiation (with monitoring of outcomes up to hospital discharge)
HFNO failure was defined as escalation to noninvasive ventilation (NIV) or endotracheal intubation due to refractory hypoxemia, progressive respiratory acidosis, severe respiratory distress, or hemodynamic instability. Within-tier adjustments (increasing flow or FiO₂ without changing support modality) were NOT considered failure.
Time frame: During physiological measurements in mechanically ventilated patients (performed before the clinical HFNO cohort; within 48 hours of ICU admission)
EFI was compared with esophageal pressure swing (ΔPes) and pressure-time product per minute (PTP/min) across pressure support levels using regression analysis and repeated within-subject comparisons.Unit of Measure No unit for R² (dimensionless ratio); Arbitrary units (a.u.) for EFI; cm H₂O for ΔPes; cm H₂O·s/min for PTP/min.
Time frame: within 30 minutes after HFNO initiation
ANCOVA-adjusted 30-minute values of EFI, PaCO₂, heart rate, respiratory rate, pH, PaO₂ were compared between HFNO success and failure groups to identify persistent physiological burden.Unit of Measure EFI: arbitrary units (a.u.); PaCO₂ and PaO₂: mmHg; Heart rate: beats/min; Respiratory rate: breaths/min; pH: dimensionless (pH units);
Time frame: Baseline to 30 minutes after HFNO initiation
Generalized estimating equations (GEE) evaluated time-by-group interactions for EFI, respiratory rate, PaO₂, PaCO₂, pH, heart rate, ROX, to identify divergent early response trajectories.Measure of Central Tendency / Measure of Dispersion Time-by-group interaction P values; Estimated marginal means at baseline and 30 minutes for each group; Within-patient change scores (Δ values) between the two time points for each variable Unit of Measure EFI: arbitrary units (a.u.); Heart rate: beats/min; Respiratory rate: breaths/min; pH: dimensionless (pH units); PaCO₂ and PaO₂: mm Hg; ROX: dimensionless index.
Ruijin Hospital
Other
Acronym: EFI-HFNO
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