# Metabolomic Biomarkers Predict Long-term Physical Function in Survivors of Acute Respiratory Failure

## TL;DR

This study shows that metabolomic biomarkers in ARF patients can predict long-term physical function after ICU discharge.

## Contribution

First study to use metabolite-based machine learning to predict ARF survivors' physical recovery outcomes.

## Key findings

- Poor physical function was linked to dysregulated bioenergetic and metabolic pathways.
- Metabolites at discharge predicted SPPB scores with high accuracy (AUROC of 0.88).
- Nutritional interventions like β-alanine supplementation may improve recovery.

## Abstract

Acute respiratory failure (ARF) often leads to post-intensive care syndrome, including persistent physical impairments after ICU discharge. Emerging evidence suggests that mitochondrial bioenergetic dysfunction, detectable through metabolomic profiling, may contribute to poor recovery.

We performed a retrospective study comprising of untargeted metabolomic profiling using ultrahigh performance liquid chromatography–mass spectrometry (UHPLC-MS) on serial serum samples from 70 ARF patients taken at ICU admission, during hospitalization and at discharge. Physical function was assessed post-discharge using the Short Physical Performance Battery (SPPB). Correlation and logistic regression analyses were performed to identify metabolomic predictors of six-month physical function outcomes.

Patients with poor SPPB scores exhibited dysregulation in bioenergetic metabolite levels, as well as fatty acid oxidation, glycerophospholipid metabolism, bile acid biosynthesis and amino acid metabolism. These metabolic changes were not explained by initial disease severity (APACHE III scores) or comorbidities. In contrast, several metabolites measured at discharge were predictive of SPPB scores with an AUROC of 0.88 after cross validation.

Our findings highlight persistent metabolic dysfunction at discharge, particularly in pathways related to bioenergetics. To our knowledge, this is the first study to employ a metabolite-based machine learning model to predict ARF survivors physical function outcomes using serum metabolites measured at discharge. Further insights on dysregulated pathways suggest that nutritional interventions targeting these metabolic pathways, such as supplementation with β-alanine, could potentially improve post-ICU recovery outcomes.