2025
A computable electronic health record ARDS classifier recapitulates an association between the MUC5B promoter polymorphism and ARDS in critically ill adults.
Kerchberger V, McNeil J, Zheng N, Chang D, Rosenberger C, Rogers A, Bastarache J, Feng Q, Wei W, Ware L. A computable electronic health record ARDS classifier recapitulates an association between the MUC5B promoter polymorphism and ARDS in critically ill adults. CHEST Critical Care 2025, 100150. DOI: 10.1016/j.chstcc.2025.100150.Peer-Reviewed Original ResearchElectronic health recordsCritically Ill AdultsElectronic health record dataMUC5B Promoter PolymorphismIll adultsAt-risk adultsNegative predictive valuePositive predictive valueDiagnostic billing codesHealth recordsHospital participationGenetic risk factorsDNA biobanksBilling codesBioVUStudy designPromoter polymorphismCohort of critically ill adultsAt-riskCohen's kappaModerate agreementRisk factorsGenotyped cohortPredictive valueBiobank
2014
Chapter 12 Linking Genomic and Clinical Data for Discovery and Personalized Care
Denny J, Xu H. Chapter 12 Linking Genomic and Clinical Data for Discovery and Personalized Care. 2014, 395-424. DOI: 10.1016/b978-0-12-401678-1.00012-9.Peer-Reviewed Original ResearchElectronic health recordsEHR dataNatural language processingSuch algorithmsLanguage processingDecision supportPhenotype algorithmsIdeal repositoryHealth recordsNumber of challengesRepositoryAlgorithmClinical notesClinical careClinical documentationGenomic dataResult dataAccurate caseDNA biobanksEarly demonstration projectsHealth care qualityClinical recordsMedication recordsClinical dataTool
2012
The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients
Birdwell K, Grady B, Choi L, Xu H, Bian A, Denny J, Jiang M, Vranic G, Basford M, Cowan J, Richardson D, Robinson M, Ikizler T, Ritchie M, Stein C, Haas D. The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients. Pharmacogenetics And Genomics 2012, 22: 32-42. PMID: 22108237, PMCID: PMC3237759, DOI: 10.1097/fpc.0b013e32834e1641.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsATP Binding Cassette Transporter, Subfamily BATP Binding Cassette Transporter, Subfamily B, Member 1Body WeightCytochrome P-450 CYP3ADatabases, Nucleic AcidDose-Response Relationship, DrugDrug MonitoringElectronic Health RecordsFemaleGenetic Association StudiesGenotypeHemoglobinsHumansImmunosuppressive AgentsKidney TransplantationLinkage DisequilibriumMaleMiddle AgedPolymorphism, Single NucleotidePregnane X ReceptorReceptors, SteroidTacrolimusConceptsTacrolimus dose requirementsKidney transplant recipientsDose requirementsElectronic medical recordsBlood concentrationsTransplant recipientsMedical recordsCYP3A5 rs776746Electronic medical record dataInterindividual pharmacokinetic variabilityTacrolimus blood concentrationsNarrow therapeutic indexDNA biobanksMedical record dataTherapeutic drug monitoringDrug-metabolizing enzymesKidney transplantationClinical factorsPrimary outcomeImmunosuppressive drugsPharmacokinetic variabilityTacrolimus clearanceClinical covariatesPharmacogenomic predictorsTherapeutic index
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