2024
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
2013
J. T. P. Liggins et al.
Liggins JT, Yoo AJ, Mishra NK, Wheeler HM, Straka M, Leslie‐Mazwi T, Chaudhry ZA, Kemp S, Mlynash M, Bammer R, Albers GW, Lansberg MG, Investigators D. J. T. P. Liggins et al. International Journal Of Stroke 2013, 10: 705-709. PMID: 24207136, PMCID: PMC4048330, DOI: 10.1111/ijs.12207.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAgingBrain IschemiaCohort StudiesDatabases, FactualDiffusion Magnetic Resonance ImagingFemaleFibrinolytic AgentsHumansLogistic ModelsMaleMiddle AgedMulticenter Studies as TopicOutcome Assessment, Health CareSeverity of Illness IndexStrokeTissue Plasminogen ActivatorTreatment OutcomeConceptsPoor functional outcomeDiffusion-weighted imaging scoreFunctional outcomeImaging scoresTherapy scoreClinical responseDiffusion-weighted imaging volumeModified Rankin Scale scoreAcute stroke interventionAcute ischemic strokePercentage of patientsPredictive scoring systemRankin Scale scorePredictors of outcomeCharacteristic curveDiffusion-Weighted ImagingIschemic strokeEndovascular therapyIndependent predictorsPatient ageStroke interventionEndovascular treatmentValidation cohortClinical variablesLesion volume