2023
Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19
Menez S, Coca S, Moledina D, Wen Y, Chan L, Thiessen-Philbrook H, Obeid W, Garibaldi B, Azeloglu E, Ugwuowo U, Sperati C, Arend L, Rosenberg A, Kaushal M, Jain S, Wilson F, Parikh C, Consortium T, Deng J, Atta M, Bagnasco S, Ko A, Iwasaki A, Farhadian S, Nelson A, Casanovas-Massana A, White E, Schulz W, Coppi A, Young P, Nunez A, Shepard D, Matos I, Strong Y, Anastasio K, Brower K, Kuang M, Chiorazzi M, Bermejo S, Vijayakumar P, Geng B, Fournier J, Minasyan M, Muenker M, Moore A, Nadkarni G. Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19. American Journal Of Kidney Diseases 2023, 82: 322-332.e1. PMID: 37263570, PMCID: PMC10229201, DOI: 10.1053/j.ajkd.2023.03.010.Peer-Reviewed Original ResearchConceptsSoluble tumor necrosis factor receptor 1Major adverse kidney eventsAdverse kidney eventsAdverse kidney outcomesAcute kidney injuryKidney eventsTumor necrosis factor receptor 1Necrosis factor receptor 1Plasma biomarkersKidney outcomesC-indexFactor receptor 1Hospitalized patientsCOVID-19KDIGO stage 3 acute kidney injuryDialysis-requiring acute kidney injuryStage 3 acute kidney injuryLong-term adverse health outcomesReceptor 1Long-term kidney dysfunctionAvailable blood samplesIdentification of patientsProportional hazards regressionAdverse health outcomesCOVID-19 hospitalization
2018
Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study
Huang C, Murugiah K, Mahajan S, Li SX, Dhruva SS, Haimovich JS, Wang Y, Schulz WL, Testani JM, Wilson FP, Mena CI, Masoudi FA, Rumsfeld JS, Spertus JA, Mortazavi BJ, Krumholz HM. Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study. PLOS Medicine 2018, 15: e1002703. PMID: 30481186, PMCID: PMC6258473, DOI: 10.1371/journal.pmed.1002703.Peer-Reviewed Original ResearchMeSH KeywordsAcute Kidney InjuryAgedClinical Decision-MakingData MiningDecision Support TechniquesFemaleHumansMachine LearningMaleMiddle AgedPercutaneous Coronary InterventionProtective FactorsRegistriesReproducibility of ResultsRetrospective StudiesRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeConceptsPercutaneous coronary interventionNational Cardiovascular Data RegistryRisk prediction modelAKI eventsAKI riskCoronary interventionAKI modelMean ageCardiology-National Cardiovascular Data RegistryAcute kidney injury riskAKI risk predictionRetrospective cohort studyIdentification of patientsCandidate variablesAvailable candidate variablesCohort studyPCI proceduresPoint of careBrier scoreAmerican CollegeData registryPatientsCalibration slopeInjury riskSame cohort