Subtyping strokes using blood‐based protein biomarkers: A high‐throughput proteomics and machine learning approach
Misra S, Singh P, Sengupta S, Kushwaha M, Rahman Z, Bhalla D, Talwar P, Nath M, Chakraborty R, Kumar P, Kumar A, Aggarwal P, Srivastava A, Pandit A, Mohania D, Prasad K, Mishra N, Vibha D. Subtyping strokes using blood‐based protein biomarkers: A high‐throughput proteomics and machine learning approach. European Journal Of Clinical Investigation 2024, e14372. PMID: 39655799, DOI: 10.1111/eci.14372.Peer-Reviewed Original ResearchHigh-throughput proteomicsExpressed proteinsSWATH-MSInteraction networkPathway analysisProteomicsProtein biomarkersBlood-based protein biomarkersIntracerebral haemorrhageDifferentiate ISIschemic strokeProteinApo C1Clinical variablesDiscovery phaseMMP-9Multivariate logistic regression analysisLogistic regression analysisCut-off pointCytoscapePrognostic biomarkers of intracerebral hemorrhage identified using targeted proteomics and machine learning algorithms
Misra S, Kawamura Y, Singh P, Sengupta S, Nath M, Rahman Z, Kumar P, Kumar A, Aggarwal P, Srivastava A, Pandit A, Mohania D, Prasad K, Mishra N, Vibha D. Prognostic biomarkers of intracerebral hemorrhage identified using targeted proteomics and machine learning algorithms. PLOS ONE 2024, 19: e0296616. PMID: 38829877, PMCID: PMC11146689, DOI: 10.1371/journal.pone.0296616.Peer-Reviewed Original ResearchConceptsIntracerebral hemorrhagePoor outcomePrognostic biomarker of ICHBiomarker of intracerebral hemorrhageHazard ratioOdds ratioShort-term poor outcomePrognostic of patient outcomeMMP-2Multivariate Cox regression modelICH prognosisInternal validation of prediction modelsModified Rankin Scale scoreIntracerebral hemorrhage patientsRankin Scale scoreUCH-L1Confidence intervalsCox regression modelsMultivariate logistic regressionProtein biomarkersIGFBP-3Regression modelsPrognostic outcomesSerum biomarkersClinical variables