Featured Publications
Temporal relationship of computed and structured diagnoses in electronic health record data
Schulz WL, Young HP, Coppi A, Mortazavi BJ, Lin Z, Jean RA, Krumholz HM. Temporal relationship of computed and structured diagnoses in electronic health record data. BMC Medical Informatics And Decision Making 2021, 21: 61. PMID: 33596898, PMCID: PMC7890604, DOI: 10.1186/s12911-021-01416-x.Peer-Reviewed Original ResearchConceptsElectronic health recordsStructured diagnosisOutpatient blood pressureElectronic health record dataAcademic health systemLow-density lipoproteinHealth record dataBlood pressureStructured data elementsAdministrative claimsHypertensionClinical informationHyperlipidemiaClinical phenotypeEquivalent diagnosisVital signsHealth systemDiagnosisProblem listAdditional studiesHealth recordsRecord dataTimely accessEHR dataPatients
2023
Microfluidic Immuno‐Serolomic Assay Reveals Systems Level Association with COVID‐19 Pathology and Vaccine Protection (Small Methods 10/2023)
Kim D, Biancon G, Bai Z, VanOudenhove J, Liu Y, Kothari S, Gowda L, Kwan J, Buitrago‐Pocasangre N, Lele N, Asashima H, Racke M, Wilson J, Givens T, Tomayko M, Schulz W, Longbrake E, Hafler D, Halene S, Fan R. Microfluidic Immuno‐Serolomic Assay Reveals Systems Level Association with COVID‐19 Pathology and Vaccine Protection (Small Methods 10/2023). Small Methods 2023, 7 DOI: 10.1002/smtd.202370057.Peer-Reviewed Original ResearchAn AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model
Charkoftaki G, Aalizadeh R, Santos-Neto A, Tan W, Davidson E, Nikolopoulou V, Wang Y, Thompson B, Furnary T, Chen Y, Wunder E, Coppi A, Schulz W, Iwasaki A, Pierce R, Cruz C, Desir G, Kaminski N, Farhadian S, Veselkov K, Datta R, Campbell M, Thomaidis N, Ko A, Thompson D, Vasiliou V. An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model. Human Genomics 2023, 17: 80. PMID: 37641126, PMCID: PMC10463861, DOI: 10.1186/s40246-023-00521-4.Peer-Reviewed Original ResearchConceptsCOVID-19 patientsDisease severityViral outbreaksFuture viral outbreaksLength of hospitalizationIntensive care unitWorse disease prognosisLife-threatening illnessEffective medical interventionsCOVID-19Clinical decision treeGlucuronic acid metabolitesNew potential biomarkersHospitalization lengthCare unitComorbidity dataSerotonin levelsDisease progressionHealthy controlsPatient outcomesDisease prognosisPatient transferPatientsHealthcare resourcesPotential biomarkersMicrofluidic Immuno‐Serolomic Assay Reveals Systems Level Association with COVID‐19 Pathology and Vaccine Protection
Kim D, Biancon G, Bai Z, VanOudenhove J, Liu Y, Kothari S, Gowda L, Kwan J, Buitrago‐Pocasangre N, Lele N, Asashima H, Racke M, Wilson J, Givens T, Tomayko M, Schulz W, Longbrake E, Hafler D, Halene S, Fan R. Microfluidic Immuno‐Serolomic Assay Reveals Systems Level Association with COVID‐19 Pathology and Vaccine Protection. Small Methods 2023, 7: e2300594. PMID: 37312418, PMCID: PMC10592458, DOI: 10.1002/smtd.202300594.Peer-Reviewed Original ResearchConceptsB cell depletion therapyAcute COVID infectionAnti-spike IgGHigh-risk patientsCoronavirus disease-19COVID-19 pathologyDepletion therapyVaccine protectionAntibody responseCOVID infectionHematologic malignanciesImmune protectionDisease-19Healthy donorsMultiple time pointsSerology assaysBlood samplesSoluble markersB cellsImmunization strategiesPatientsFunctional deficiencySerological analysisTime pointsClonotype diversity
2022
Transfusion support for the oncology patient
Stendahl K, Schulz W, Snyder E. Transfusion support for the oncology patient. 2022, 482-488. DOI: 10.1002/9781119719809.ch41.ChaptersOncology patientsTransfusion supportBlood productsRed blood cell transfusionAntibiotic-refractory infectionsAppropriate blood productsChronic transfusion supportMost oncology patientsSignificant transfusion reactionsBlood cell transfusionGranulocyte infusionsCell transfusionSevere neutropeniaOxygen-carrying capacityAppropriate therapyTransfusion therapyTransfusion reactionsPatientsABO antigensABO groupHost antibodiesTransfusion servicesRBC unitsBlood componentsWhole bloodDe novo emergence of a remdesivir resistance mutation during treatment of persistent SARS-CoV-2 infection in an immunocompromised patient: a case report
Gandhi S, Klein J, Robertson AJ, Peña-Hernández MA, Lin MJ, Roychoudhury P, Lu P, Fournier J, Ferguson D, Mohamed Bakhash SAK, Catherine Muenker M, Srivathsan A, Wunder EA, Kerantzas N, Wang W, Lindenbach B, Pyle A, Wilen CB, Ogbuagu O, Greninger AL, Iwasaki A, Schulz WL, Ko AI. De novo emergence of a remdesivir resistance mutation during treatment of persistent SARS-CoV-2 infection in an immunocompromised patient: a case report. Nature Communications 2022, 13: 1547. PMID: 35301314, PMCID: PMC8930970, DOI: 10.1038/s41467-022-29104-y.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 infectionVirologic responsePersistent SARS-CoV-2 infectionResistance mutationsPre-treatment specimensB-cell deficiencyRemdesivir resistanceRemdesivir therapyViral sheddingCase reportAntiviral agentsPatientsCombinatorial therapyInfectionTherapyWhole-genome sequencingTreatmentImportance of monitoringDe novo emergenceFold increaseRNA-dependent RNA polymeraseNovo emergencePotential benefitsMutationsIndolent
2021
Feasibility of using real-world data in the evaluation of cardiac ablation catheters: a test-case of the National Evaluation System for Health Technology Coordinating Center
Dhruva SS, Jiang G, Doshi AA, Friedman DJ, Brandt E, Chen J, Akar JG, Ross JS, Ervin KR, Farr K, Shah ND, Coplan P, Noseworthy PA, Zhang S, Forsyth T, Schulz WL, Yu Y, Drozda JP. Feasibility of using real-world data in the evaluation of cardiac ablation catheters: a test-case of the National Evaluation System for Health Technology Coordinating Center. BMJ Surgery Interventions & Health Technologies 2021, 3: e000089. PMID: 35047806, PMCID: PMC8749235, DOI: 10.1136/bmjsit-2021-000089.Peer-Reviewed Original ResearchPositive predictive valuePersistent atrial fibrillationIschemic ventricular tachycardiaAblation catheterHealth systemAtrial fibrillationVentricular tachycardiaCardiac ablation catheterAcute heart failureDuration of patientsHealth system dataCardiac tamponadeIschemic strokeRetrospective cohortHeart failureClinical outcomesEndpoint ascertainmentPredictive valueCatheterChart validationCoordinating CenterTachycardiaPatientsFibrillationParticipant population
2020
Rates and Predictors of Patient Underreporting of Hospitalizations During Follow-Up After Acute Myocardial Infarction
Caraballo C, Khera R, Jones PG, Decker C, Schulz W, Spertus JA, Krumholz HM. Rates and Predictors of Patient Underreporting of Hospitalizations During Follow-Up After Acute Myocardial Infarction. Circulation Cardiovascular Quality And Outcomes 2020, 13: e006231. PMID: 32552061, PMCID: PMC9465954, DOI: 10.1161/circoutcomes.119.006231.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionMyocardial infarctionHospitalization eventsMedical recordsLongitudinal multicenter cohort studyMulticenter cohort studyMedical record abstractionDifferent patient characteristicsHealth care eventsPatients' underreportingTRIUMPH registryAccuracy of reportingCohort studyPatient characteristicsRecord abstractionProspective studyClinical studiesClinical investigationHospitalizationPatientsCare eventsInfarctionEvent ratesParticipantsPredictorsLeveraging the Electronic Health Records for Population Health: A Case Study of Patients With Markedly Elevated Blood Pressure
Lu Y, Huang C, Mahajan S, Schulz WL, Nasir K, Spatz ES, Krumholz HM. Leveraging the Electronic Health Records for Population Health: A Case Study of Patients With Markedly Elevated Blood Pressure. Journal Of The American Heart Association 2020, 9: e015033. PMID: 32200730, PMCID: PMC7428633, DOI: 10.1161/jaha.119.015033.Peer-Reviewed Original ResearchConceptsDiastolic blood pressureSystolic blood pressureElevated blood pressureBlood pressureElectronic health recordsPopulation health surveillanceHealth recordsYale New Haven Health SystemHealth surveillanceHealth systemPatterns of patientsLarge health systemUsual careOutpatient encountersControl ratePatientsCare patternsPopulation healthMonthsHgSurveillancePrevalenceRecordsVisitsCare
2019
Blood utilisation and transfusion reactions in adult patients transfused with conventional or pathogen‐reduced platelets
Bahar B, Schulz WL, Gokhale A, Spencer BR, Gehrie EA, Snyder EL. Blood utilisation and transfusion reactions in adult patients transfused with conventional or pathogen‐reduced platelets. British Journal Of Haematology 2019, 188: 465-472. PMID: 31566724, PMCID: PMC7003815, DOI: 10.1111/bjh.16187.Peer-Reviewed Original ResearchConceptsPathogen-reduced plateletsTransfusion reactionsPlatelet componentsAdult patientsPlatelet transfusionsSeptic transfusion reactionsRed blood cell transfusion requirementsPR plateletsYale-New Haven HospitalPlatelet component transfusionsComparable clinical efficacyType of transfusionTransfusion requirementsTransfusion trendsPlatelet administrationComponent transfusionClinical efficacyNumber of RBCsConventional plateletsBlood utilisationPatientsTransfusionMean timePlateletsRBCs
2018
Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study
Huang C, Murugiah K, Mahajan S, Li SX, Dhruva SS, Haimovich JS, Wang Y, Schulz WL, Testani JM, Wilson FP, Mena CI, Masoudi FA, Rumsfeld JS, Spertus JA, Mortazavi BJ, Krumholz HM. Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study. PLOS Medicine 2018, 15: e1002703. PMID: 30481186, PMCID: PMC6258473, DOI: 10.1371/journal.pmed.1002703.Peer-Reviewed Original ResearchMeSH KeywordsAcute Kidney InjuryAgedClinical Decision-MakingData MiningDecision Support TechniquesFemaleHumansMachine LearningMaleMiddle AgedPercutaneous Coronary InterventionProtective FactorsRegistriesReproducibility of ResultsRetrospective StudiesRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeConceptsPercutaneous coronary interventionNational Cardiovascular Data RegistryRisk prediction modelAKI eventsAKI riskCoronary interventionAKI modelMean ageCardiology-National Cardiovascular Data RegistryAcute kidney injury riskAKI risk predictionRetrospective cohort studyIdentification of patientsCandidate variablesAvailable candidate variablesCohort studyPCI proceduresPoint of careBrier scoreAmerican CollegeData registryPatientsCalibration slopeInjury riskSame cohort
2017
A novel network analysis tool to identify relationships between disease states and risks for red blood cell alloimmunization
Celli R, Schulz W, Hendrickson JE, Tormey CA. A novel network analysis tool to identify relationships between disease states and risks for red blood cell alloimmunization. Vox Sanguinis 2017, 112: 469-472. PMID: 28337751, DOI: 10.1111/vox.12515.Peer-Reviewed Original Research
2016
Transfusion support for the oncology patient
Schulz W, Snyder E. Transfusion support for the oncology patient. 2016, 574-580. DOI: 10.1002/9781119013020.ch50.ChaptersOncology patientsTransfusion supportTransfusion-transmitted diseasesSafety of transfusionTA-GVHDTransplant patientsAdverse eventsDonor testingAppropriate therapyABO incompatibilityPatient populationTransfusion therapyOncologic disordersMajor therapyPatientsTransfusion servicesCellular antigensBlood componentsTherapyFrequent exposureTransfusionSpecific assessmentRiskAlloimmunizationImmunomodulation