{"doi":"10.3390/children8020151","title":"The Feasibility of Studying Metabolites in PICU Multi-Organ Dysfunction Syndrome Patients over an 8-Day Course Using an Untargeted Approach","abstract":"Metabolites are generated from critical biological functions and metabolism. This pediatric study reviewed plasma metabolites in patients suffering from multi-organ dysfunction syndrome (MODS) in the pediatric intensive care unit (PICU) using an untargeted metabolomics approach. Patients meeting the criteria for MODS were screened for eligibility and consented (n = 24), and blood samples were collected at baseline, 72 h, and 8 days; control patients (n = 4) presented for routine sedation in an outpatient setting. A subset of MODS patients (n = 8) required additional support with veno-atrial extracorporeal membrane oxygenation (VA-ECMO) therapy. Metabolites from thawed blood plasma were determined from ion pairing reversed-phase liquid chromatography–mass spectrometry (LC-MS) analysis. Chromatographic peak alignment, identification, relative quantitation, and statistical and bioinformatics evaluation were performed using MAVEN and MetaboAnalyst 4.0. Metabolite analysis revealed 115 peaks per sample. From the partial least squares-discriminant analysis (PLS-DA) with variance of importance (VIP) scores above ≥2.0, 7 dynamic metabolites emerged over the three time points: tauro-chenodeoxycholic acid (TCDCA), hexose, p-hydroxybenzoate, hydroxyphenylacetic acid (HPLA), 2_3-dihydroxybenzoic acid, 2-keto-isovalerate, and deoxyribose phosphate. After Bonferroni adjustment for repeated measures, hexose and p-hydroxybenzoate were significant at one time point or more. Kendall’s tau-b test was used for internal validation of creatinine. Metabolites may be benign or significant in describing a patient’s pathophysiology and require operator interpretation.","journal":"Children","year":2021,"id":209339,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7965,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":578077,"name":"Danny Gil","orcid":null,"position":1,"is_corresponding":false},{"id":796937,"name":"Andrew Kampfschulte","orcid":"0000-0001-9368-690X","position":2,"is_corresponding":false},{"id":578079,"name":"Claire Krohn","orcid":null,"position":3,"is_corresponding":false},{"id":577371,"name":"Elizabeth Prentice","orcid":"0000-0002-0468-5401","position":4,"is_corresponding":false},{"id":578080,"name":"Dominic Sanfilippo","orcid":null,"position":5,"is_corresponding":false},{"id":394893,"name":"Jeremy W. Prokop","orcid":"0000-0002-1818-9695","position":6,"is_corresponding":false},{"id":339191,"name":"Todd A. Lydic","orcid":"0000-0003-3830-7406","position":7,"is_corresponding":false},{"id":394895,"name":"Surender Rajasekaran","orcid":"0000-0002-4430-006X","position":8,"is_corresponding":false},{"id":394888,"name":"Mara L. Leimanis","orcid":"0000-0003-0595-4578","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-18T23:52:05.171356Z","pmid":"33670443","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}