Background Progressive decline in pulmonary oxygen reserve capacity (ORC) is a hallmark of infection-associated respiratory dysfunction. Current tools (PaO2/FiO2 ratio, cardiopulmonary exercise testing [CPET], computed tomography [CT]) are limited in dynamic monitoring due to delayed responsiveness, operational complexity, or radiation risks, and other constraints.

Methods The ORC testing methodology integrates the dynamic load-incrementation logic of cardiopulmonary exercise testing (CPET) with the oxygenation quantification framework of PaO2/FiO2. Its operational paradigm comprises three phases:

➀Testing Protocol

Conducted under ventilation-locked conditions, a stepwise FiO2 titration protocol is applied, with termination triggered when SpO2

➁Parameter Definition

The minimum FiO2 required to maintain SpO2 ≥90% (FiO2-MIN) is recorded, and the oxygen reserve capacity is calculated as ORC = 0.21 - FiO2-MIN.

➂Dynamic Modeling

Through continuous monitoring throughout the entire disease course, ORC time-series data are acquired. A time-ORC curve is then fitted, and based on differential calculus (β = ΔORC/Δt, γ = Δβ/Δt), they collectively establish a quantitative respiratory compensation dynamics model in conjunction with the time-ORC curve.

Results The ORC test provides a novel non-invasive tool for dynamic quantification of respiratory reserve. Early warning of ARDS transformation during acute infection and quantitative dynamic tracking of lung dysfunction of long-COVID syndrome are its potential application scenarios. Its clinical utility requires prospective validation through multicenter trials integrated with CPET and CT quantitative analysis.

The authors have declared no competing interest.

This study did not receive any funding

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