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