2023
A randomized clinical trial assessing the effect of automated medication-targeted alerts on acute kidney injury outcomes
Wilson F, Yamamoto Y, Martin M, Coronel-Moreno C, Li F, Cheng C, Aklilu A, Ghazi L, Greenberg J, Latham S, Melchinger H, Mansour S, Moledina D, Parikh C, Partridge C, Testani J, Ugwuowo U. A randomized clinical trial assessing the effect of automated medication-targeted alerts on acute kidney injury outcomes. Nature Communications 2023, 14: 2826. PMID: 37198160, PMCID: PMC10192367, DOI: 10.1038/s41467-023-38532-3.Peer-Reviewed Original ResearchConceptsAcute kidney injuryUsual care groupKidney injuryCare groupAcute Kidney Injury OutcomesAlert groupNon-steroidal anti-inflammatory drugsComposite of progressionHours of randomizationMedications of interestAldosterone system inhibitorsClasses of medicationsProton pump inhibitorsRandomized clinical trialsAnti-inflammatory drugsClinical decision support systemNephrotoxic medicationsHospitalized adultsDiscontinuation ratesCertain medicationsPrimary outcomeSubstantial morbiditySystem inhibitorsPump inhibitorsParallel group
2020
Real-Time Prediction of Acute Kidney Injury in Hospitalized Adults: Implementation and Proof of Concept
Ugwuowo U, Yamamoto Y, Arora T, Saran I, Partridge C, Biswas A, Martin M, Moledina DG, Greenberg JH, Simonov M, Mansour SG, Vela R, Testani JM, Rao V, Rentfro K, Obeid W, Parikh CR, Wilson FP. Real-Time Prediction of Acute Kidney Injury in Hospitalized Adults: Implementation and Proof of Concept. American Journal Of Kidney Diseases 2020, 76: 806-814.e1. PMID: 32505812, PMCID: PMC8667815, DOI: 10.1053/j.ajkd.2020.05.003.Peer-Reviewed Original ResearchConceptsAKI alertsHospitalized adultsKidney injuryUrban tertiary care hospitalAcute kidney injurySerum creatinine levelsObservational cohort studyTertiary care hospitalSerum creatinine concentrationBeats/minElectronic health recordsAKI diagnosisCohort studyCreatinine levelsInpatient mortalitySystolic bloodFractional excretionCenter studyBlood biomarkersUnivariable associationsUrine microscopyCreatinine concentrationClinical careElevated riskUrea nitrogen
2019
A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: A descriptive modeling study
Simonov M, Ugwuowo U, Moreira E, Yamamoto Y, Biswas A, Martin M, Testani J, Wilson FP. A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: A descriptive modeling study. PLOS Medicine 2019, 16: e1002861. PMID: 31306408, PMCID: PMC6629054, DOI: 10.1371/journal.pmed.1002861.Peer-Reviewed Original ResearchMeSH KeywordsAcute Kidney InjuryAgedAged, 80 and overConnecticutDecision Support TechniquesElectronic Health RecordsFemaleHospital MortalityHumansInpatientsMaleMiddle AgedPatient AdmissionPredictive Value of TestsPrognosisRenal DialysisRetrospective StudiesRisk AssessmentRisk FactorsSeverity of Illness IndexTime FactorsConceptsAcute kidney injuryImminent acute kidney injuryElectronic health recordsKidney injuryHospital 1Prediction of AKIRenal replacement therapyOptimal treatment strategyLaboratory dataReceiver operator characteristic curveInternal validation setAKI occurrenceAKI severityHospitalized adultsMedical comorbiditiesOverall cohortAdverse eventsHospitalized patientsSurgical wardsSignificant morbidityReplacement therapyExternal validation data setsHospital 2Hospital 3Study hospital