2017
Approaches to Predicting Outcomes in Patients with Acute Kidney Injury
Saly D, Yang A, Triebwasser C, Oh J, Sun Q, Testani J, Parikh CR, Bia J, Biswas A, Stetson C, Chaisanguanthum K, Wilson FP. Approaches to Predicting Outcomes in Patients with Acute Kidney Injury. PLOS ONE 2017, 12: e0169305. PMID: 28122032, PMCID: PMC5266278, DOI: 10.1371/journal.pone.0169305.Peer-Reviewed Original ResearchConceptsAcute kidney injuryLength of stayKidney injuryReceiver operator characteristic curveOutcomes of interestOperator characteristic curveValidation cohortClinical eventsAccurate prognosticationOutcome eventsPredicting OutcomePrognostic modelDeath predictionLab valuesCharacteristic curveGood discrimination abilityPatientsStayInjuryDialysisModel discriminationOutcomesDaysMedicationsMorbidity
2016
Provider acceptance of an automated electronic alert for acute kidney injury
Oh J, Bia JR, Ubaid-Ullah M, Testani JM, Wilson FP. Provider acceptance of an automated electronic alert for acute kidney injury. Clinical Kidney Journal 2016, 9: 567-571. PMID: 27478598, PMCID: PMC4957729, DOI: 10.1093/ckj/sfw054.Peer-Reviewed Original ResearchAcute kidney injuryElectronic alertsAKI alertsKidney injuryPatient careAKI alert systemElectronic AKI alertsNon-physician providersPercent of respondersHealthcare provider opinionsElectronic medical recordsClinical decision support systemMedical recordsSingle hospitalProviders' opinionsProvider acceptanceTrial durationPaucity of informationPatient-specific informationTrialsSignificant differencesAlert trialsInjuryApprovalCare