Abstract Pediatric thoracic critical illnesses like severe pneumonia, sepsis, and pediatric acute respiratory distress syndrome challenge intensive care units worldwide, with high prevalence and mortality. Although many clinical biomarkers are available to monitor the disease course, delayed recognition and heterogeneous phenotypes demand better biomarkers. Metabolomics, via nuclear magnetic resonance (NMR, reproducible, nondestructive, and detects 30–100 metabolites) and liquid chromatography-mass spectrometry (LC-MS, high-sensitivity, detects more than 1000 metabolites), profiles dynamic changes in various body fluids including plasma, bronchoalveolar lavage fluid, and breath condensate. NMR excels at quantifying high-concentration metabolites like lactate and amino acids via simple preparation and tools such as NMRProcFlow and Chenomx, while LC-MS targets trace-level compounds including lipids and acylcarnitines using electrospray ionization, MS/MS fragmentation, and MS-Dial processing. Unified workflows with MetaboAnalyst, Kyoto Encyclopedia of Genes and Genomes, and human metabolome database then enable principal component analysis/partial least squares-discriminant analysis modeling, as well as pathway enrichment analysis, to generate robust metabolomics insights. In pediatric critical care, metabolomics biomarkers may surpass C-reactive protein and procalcitonin in prognostic accuracy for predicting ventilation needs and multi-organ failure risk. Integrating NMR and LC-MS enables noninvasive monitoring via breath condensate, urine, or plasma, while elucidating key mechanisms like mitochondrial dysfunction in pediatric thoracic critical illnesses. These biomarkers outperform traditional markers in prognostic modeling. However, future multicenter trials should validate multi-omics panels and develop artificial intelligence-hybrid platforms for point-of-care assays, enabling precision ventilation and adjunct therapies to transform pediatric thoracic critical care.
Takaba et al. (Thu,) studied this question.
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