2024
External Validation of an Electronic Health Record-Based Diagnostic Model for Histological Acute Tubulointerstitial Nephritis.
Moledina D, Shelton K, Menez S, Aklilu A, Yamamoto Y, Kadhim B, Shaw M, Kent C, Makhijani A, Hu D, Simonov M, O'Connor K, Bitzel J, Thiessen-Philbrook H, Wilson F, Parikh C. External Validation of an Electronic Health Record-Based Diagnostic Model for Histological Acute Tubulointerstitial Nephritis. Journal Of The American Society Of Nephrology 2024 PMID: 39500309, DOI: 10.1681/asn.0000000556.Peer-Reviewed Original ResearchJohns Hopkins HospitalAcute tubulointerstitial nephritisValidation cohortKidney biopsyTubulointerstitial nephritisDiagnosis of acute tubulointerstitial nephritisProportion of biopsiesElectronic health recordsAnalyzed patientsDevelopment cohortBaseline prevalenceAccurate diagnosisBiopsyCohortHealth recordsClinician's abilityDiagnostic modelPotential predictorsNephritisAssess discriminationKidneyAUC
2023
Identification and validation of urinary CXCL9 as a biomarker for diagnosis of acute interstitial nephritis
Moledina D, Obeid W, Smith R, Rosales I, Sise M, Moeckel G, Kashgarian M, Kuperman M, Campbell K, Lefferts S, Meliambro K, Bitzer M, Perazella M, Luciano R, Pober J, Cantley L, Colvin R, Wilson F, Parikh C. Identification and validation of urinary CXCL9 as a biomarker for diagnosis of acute interstitial nephritis. Journal Of Clinical Investigation 2023, 133: e168950. PMID: 37395276, PMCID: PMC10313360, DOI: 10.1172/jci168950.Peer-Reviewed Original ResearchConceptsUrinary CXCL9External validation cohortValidation cohortControl groupAIN diagnosisDiscovery cohortKidney tissueDiagnostic biomarkersAcute interstitial nephritisCXCL9 mRNA expressionAcute kidney injuryBiopsy-confirmed diagnosisAvailable clinical testsNational InstituteKidney injuryTubulointerstitial nephritisInterstitial nephritisKidney biopsyHistological confirmationHistological diagnosisTreatment optionsLymphocyte chemotaxisCXCL9MRNA expression differencesPatients
2021
Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data
Moledina DG, Eadon MT, Calderon F, Yamamoto Y, Shaw M, Perazella MA, Simonov M, Luciano R, Schwantes-An TH, Moeckel G, Kashgarian M, Kuperman M, Obeid W, Cantley LG, Parikh CR, Wilson FP. Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data. Nephrology Dialysis Transplantation 2021, 37: 2214-2222. PMID: 34865148, PMCID: PMC9755995, DOI: 10.1093/ndt/gfab346.Peer-Reviewed Original ResearchConceptsAcute interstitial nephritisInterstitial nephritisUrine biomarkersBiopsy-proven acute interstitial nephritisElectronic health record dataExternal validation cohortTypical clinical featuresBlood urea nitrogenTumor necrosis factorCharacteristic curve analysisHealth record dataExternal validationElectronic health recordsAIN diagnosisModest AUCsSerum creatinineCreatinine ratioKidney biopsyClinical featuresValidation cohortNecrosis factorUnrecognized casesInterleukin-9PatientsUrea nitrogen
2020
A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children
Sandokji I, Yamamoto Y, Biswas A, Arora T, Ugwuowo U, Simonov M, Saran I, Martin M, Testani JM, Mansour S, Moledina DG, Greenberg JH, Wilson FP. A Time-Updated, Parsimonious Model to Predict AKI in Hospitalized Children. Journal Of The American Society Of Nephrology 2020, 31: 1348-1357. PMID: 32381598, PMCID: PMC7269342, DOI: 10.1681/asn.2019070745.Peer-Reviewed Original ResearchConceptsExternal validation cohortValidation cohortElectronic health recordsSevere AKIClinical risk stratification toolDevelopment of AKIHealth recordsRisk stratification toolInternal validation cohortLength of stayCharacteristic curveElectronic medical recordsNeonatal AKIInpatient mortalitySecondary outcomesHospital admissionPrimary outcomeHospitalized childrenCreatinine valuesMedical recordsStudy populationAKICohortChildrenPredictive variables
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
2012
Predictors of Death and Dialysis in Severe AKI: The UPHS-AKI Cohort
Wilson FP, Yang W, Feldman HI. Predictors of Death and Dialysis in Severe AKI: The UPHS-AKI Cohort. Clinical Journal Of The American Society Of Nephrology 2012, 8: 527-537. PMID: 23258795, PMCID: PMC3613955, DOI: 10.2215/cjn.06450612.Peer-Reviewed Original ResearchConceptsSevere AKIC-indexIntensive care unit locationPredictors of deathEffective risk stratificationEndpoint of deathMore effective therapeutic interventionsHigh-risk subgroupsHarrell's C-indexLower overall mortalityProportional hazards modelEffective therapeutic interventionsPennsylvania Health SystemBaseline creatinineHospital AKIPressor medicationsSerum creatinineClinical factorsDerivation cohortHigher creatinineHospital admissionOverall mortalityLiver diseaseRisk stratificationValidation cohort