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