Evaluation of Physical Capacity and Energy Requirements in Patients With Hypoxemic Acute Respiratory Failure

Non-invasive ventilation (NIV) is widely used in patients with acute hypoxemic respiratory failure (AHRF), particularly those with community-acquired pneumonia (CAP), as a strategy to avoid intubation and invasive mechanical ventilation. However, predicting NIV failure remains a significant clinical challenge, and the existing tools, such as the HACOR index, are limited in accuracy and do not take into account crucial aspects like energy expenditure, muscle integrity, or other patient's physiological parameters.

NIVAR01 addresses this gap through a comprehensive, stepwise research plan aimed at understanding and anticipating NIV failure by integrating metabolic, physiological, imaging, and biomolecular data. The ultimate goal is to define patient subphenotypes that enable the personalization of therapy and improve clinical outcomes.

Objectives

The main objective of NIVAR 01 is to develop and validate a multimodal strategy to predict NIV failure in patients with AHRF and CAP, enabling the design of personalized therapeutic interventions. Specifically, the project aims to:

• Validate the use of indirect calorimetry during NIV and its correlation with BIA.
• Identify physiological and molecular phenotypes associated with NIV failure.
• Develop and test targeted nutritional and functional interventions based on patient subtypes.

Planning

The project is structured in five sequential phases, each building upon the results of the previous one. The approach moves from methodological validation to biological characterization and finally to clinical intervention. It will integrate sex-specific analysis into predictive models and intervention strategies.

• Phase 1: Correlation between BIA and IC in sedated patients

The project begins by evaluating the correlation between metabolic rate data obtained from BIA and from indirect calorimetry in sedated, invasively ventilated ICU patients. Since IC is a robust validated method in this setting, it will serve as the reference method. The correlation obtained will validate the accuracy of BIA and support its use in future phases.

• Phase 2: Validation of IC in patients under NIV

Using the reference from Phase 1, IC will be adapted for use in patients under NIV. This includes addressing the challenges posed by air leaks through integration of correction factors provided by ventilator device and its monitoring software, and potentially the development of specific circuit adaptors if required. The metabolic data collected via IC will be compared with BIA estimates to confirm feasibility and reliability in the NIV setting.

• Phase 3: Multimodal cohort study and patient phenotyping

In a prospective observational study, a cohort of patients with AHRF and CAP under NIV will undergo multimodal evaluation. This includes IC, BIA (with segmental analysis of the different body compartments both at the anatomic and physiological level), muscle and diaphragm ultrasound, and blood sampling for biomarkers of mitochondrial dysfunction (cf-mtDNA, FGF-21, GDF-15, HSP60/10), endothelial injury (e-Selectin, sICAM-1, vCAM-1, Syndecan-1), oxidative stress, and immune paralysis (HLA-DR expression, TNFα response to LPS). Data will be analyzed using machine learning to identify patient subphenotypes.

• Phase 4: Design of personalized interventions

Based on the phenotypes identified, targeted interventions will be developed. These include nutritional strategies informed by metabolic requirements and muscle function assessments, as well as physiotherapy protocols that may involve early mobilization and respiratory muscle stimulation (e.g., phrenic nerve). Strategies will be adapted to sex-specific physiological patterns and the patient's compartmental body composition.

• Phase 5: Randomized controlled trials

In the final phase, the proposed interventions will be tested in randomized clinical trials (RCTs). Patients will be stratified by phenotype and randomized to receive standard care or personalized therapy. Primary outcomes will include NIV failure (need for intubation), ICU/hospital length of stay, mortality, and functional recovery.

Expected Outcomes

NIVAR 01 is expected to generate:

• A validated protocol for using IC during NIV, including leak correction methods.
• Evidence supporting the use of BIA as a practical bedside tool to estimate metabolic rate and assess muscle and fluid status.
• Identification of subphenotypes among AHRF patients under NIV, based on multimodal data integration.
• Personalized intervention protocols tailored to patient profiles, with demonstrated clinical benefit in RCTs.
• New predictive models that outperform traditional tools like the HACOR index.
• Practical contributions to gender-informed critical care.

This integrated model will help clinicians anticipate NIV failure earlier, adapt treatment proactively, and improve patient outcomes through individualized care strategies.

Conclusion

NIVAR01 aims to develop a new standard in the management of patients with acute respiratory failure under non-invasive ventilation. By combining validated physiological measurements, molecular biomarkers, and clinical decision tools, the project introduces a precision medicine approach to intensive care. Through systematic validation, rigorous phenotyping, and targeted interventions, NIVAR 01 aims to reduce NIV failure, shorten ICU stays, and improve survival and recovery in this patient population.