Mihaela Aslan, PhD
Research Scientist (General Medicine)Cards
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Research Scientist (General Medicine)
Biography
Mihaela Aslan, Ph.D., is a graduate from the Department of Statistics at Yale University. As a mathematical statistician, she conducts methodological research on a range of topics, such as growth mixture models, competing risks methods in survival analysis, and observational methods to emulate randomized clinical trials. Multi-site observational study design represents another major methodological focus of Dr. Aslan's research. Some of her representative studies have focused on clinical topics such as prostate cancer, PTSD, suicidal ideation and behavior in patients with severe mental illness, Gulf War syndrome, and prediabetes. In her 17-year tenure with the Yale University School of Medicine and the VA Cooperative Studies Program (CSP), and in her current role as the Acting Director of Clinical Epidemiology Research Center (CERC), her goals are centered around advancing scientific knowledge, and helping train the next generation of analysts on applied clinical epidemiology methods, for improving translation and implementation of research results into clinical practice, and to benefit the health and healthcare of Veterans, and by extension, of all human beings.
Appointments
General Internal Medicine
Research ScientistPrimary
Other Departments & Organizations
Research
Research at a Glance
Yale Co-Authors
Publications Timeline
Nallakkandi Rajeevan, PhD
Hongyu Zhao, PhD
Joel Gelernter, MD
Daniel F. Levey, PhD
John Concato, MD, FACP, MS, MPH
Ning Sun, PhD
Publications
2024
Association of Race and Ethnicity with Prescriptions for Continuous Glucose Monitoring Systems Among a National Sample of Veterans with Diabetes on Insulin Therapy
Lipska K, Oladele C, Zawack K, Gulanski B, Mutalik P, Reaven P, Lynch J, Lee K, Shih M, Lee J, Aslan M. Association of Race and Ethnicity with Prescriptions for Continuous Glucose Monitoring Systems Among a National Sample of Veterans with Diabetes on Insulin Therapy. Diabetes Technology & Therapeutics 2024 PMID: 39177775, DOI: 10.1089/dia.2024.0152.Peer-Reviewed Original ResearchConceptsVeterans with diabetesAssociation of raceCross-sectional analysis of dataU.S. Veterans Health AdministrationNational sample of veteransNational sampleInsulin therapyVeterans Health AdministrationSystem-level factorsSample of veteransNon-Hispanic patientsSelf-reported raceContinuous glucose monitoringCross-sectional analysisContinuous glucose monitoring useRate of prescriptionMultivariate mixed-effects modelAfrican American patientsLatino patientsHealth AdministrationAlaska NativesType 2 diabetesPercentage of patientsSignificant disparitiesMixed-effects modelsIdentifying Veterans Who Benefit From Nirmatrelvir-Ritonavir: A Target Trial Emulation
Yan L, Bui D, Li Y, Rajeevan N, Rowneki M, Berry K, Argraves S, Huang Y, Hynes D, Cunningham F, Huang G, Aslan M, Ioannou G, Bajema K. Identifying Veterans Who Benefit From Nirmatrelvir-Ritonavir: A Target Trial Emulation. Clinical Infectious Diseases 2024, ciae202. PMID: 38864601, DOI: 10.1093/cid/ciae202.Peer-Reviewed Original ResearchAltmetricConceptsRisk quartileVeterans Health AdministrationLowest risk quartileHighest risk quartileTarget trial emulationRisk prediction modelUntreated veteransRisk of deathOlder veteransYounger veteransHealth AdministrationTrial emulationMeasure incidenceNirmatrelvir-ritonavirVeteransHospitalUntreated participantsCOVID-19QuartileRiskSevere coronavirus disease 2019ParticipantsPersonsCoronavirus disease 2019Severe COVID-1932. Comparative Genetic Architectures of Schizophrenia in Admixed African American and European Populations
Bigdeli T, Chatzinakos C, Voloudakis G, Gorman B, Barr P, Genovese G, Burstein D, Braff D, Gaziano J, Muralidhar S, Huang G, Pyarajan S, 572 C, Program M, Aslan M, Harvey P, Roussos P. 32. Comparative Genetic Architectures of Schizophrenia in Admixed African American and European Populations. Biological Psychiatry 2024, 95: s88. DOI: 10.1016/j.biopsych.2024.02.210.Peer-Reviewed Original ResearchPredicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning
Cogill S, Nallamshetty S, Fullenkamp N, Heberer K, Lynch J, Lee K, Aslan M, Shih M, Lee J. Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning. PLOS ONE 2024, 19: e0290221. PMID: 38662748, PMCID: PMC11045098, DOI: 10.1371/journal.pone.0290221.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsHigh-risk groupSARS-CoV-2 infectionAnticoagulant useAdverse outcomesPredictor of adverse outcomesHigher risk of adverse outcomesLower body mass indexRisk of adverse outcomesVaccination of high-risk groupsOral anticoagulant useOutcome of SARS-CoV-2 infectionRetrospective longitudinal observational studySARS-CoV-2U.S. Veterans Health AdministrationClinical outcomes of SARS-CoV-2 infectionIdentification of patientsBody mass indexVeterans Health AdministrationPredictors of hospitalizationEscalation of careLongitudinal observational studyClinical outcomesOmicron SARS-CoV-2 variantSARS-CoV-2 variantsUnvaccinated patientsCorrelates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder
Bigdeli T, Barr P, Rajeevan N, Graham D, Li Y, Meyers J, Gorman B, Peterson R, Sayward F, Radhakrishnan K, Natarajan S, Nielsen D, Wilkinson A, Malhotra A, Zhao H, Brophy M, Shi Y, O’Leary T, Gleason T, Przygodzki R, Pyarajan S, Muralidhar S, Gaziano J, Huang G, Concato J, Siever L, DeLisi L, Kimbrel N, Beckham J, Swann A, Kosten T, Fanous A, Aslan M, Harvey P. Correlates of suicidal behaviors and genetic risk among United States veterans with schizophrenia or bipolar I disorder. Molecular Psychiatry 2024, 1-9. PMID: 38491344, DOI: 10.1038/s41380-024-02472-1.Peer-Reviewed Original ResearchCitationsAltmetricConceptsBipolar I disorderSuicidal behaviorElectronic health recordsPolygenic scoresVeterans Health AdministrationSelf-reported SBColumbia-Suicide Severity Rating ScaleBipolar I disorder patientsCorrelates of suicidal behaviorClasses of psychotropic medicationsSelf-injurious behaviorHealth recordsSeverity Rating ScaleDiagnosed mental illnessAssociated with clinical variablesElectronic health record codesEHR domainDepressive disorderC-SSRSLifetime diagnosisSubstance-relatedPsychotropic medicationsSuicidal ideationExternalizing behaviorsSuicide attemptsCorrelates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort
Barr P, Bigdeli T, Meyers J, Peterson R, Sanchez-Roige S, Mallard T, Dick D, Harden K, Wilkinson A, Graham D, Nielsen D, Swann A, Lipsky R, Kosten T, Aslan M, Harvey P, Kimbrel N, Beckham J, Aslan M, Antonelli M, de Asis M, Bauer M, Brophy M, Concato J, Cunningham F, Freedman R, Gaziano M, Gleason T, Harvey P, Huang G, Kelsoe J, Kosten T, Lehner T, Lohr J, Marder S, Miller P, O Leary T, Patterson T, Peduzzi P, Przygodski R, Siever L, Sklar P, Strakowski S, Zhao H, Fanous A, Farwell W, Malhorta A, Mane S, Palacios P, Bigdeli T, Corsey M, Zaluda L, Johnson J, Sueiro M, Cavaliere D, Jeanpaul V, Maffucci A, Mancini L, Deen J, Muldoon G, Whitbourne S, Canive J, Adamson L, Calais L, Fuldauer G, Kushner R, Toney G, Lackey M, Mank A, Mahdavi N, Villarreal G, Muly E, Amin F, Dent M, Wold J, Fischer B, Elliott A, Felix C, Gill G, Parker P, Logan C, McAlpine J, DeLisi L, Reece S, Hammer M, Agbor-Tabie D, Goodson W, Aslam M, Grainger M, Richtand N, Rybalsky A, Al Jurdi R, Boeckman E, Natividad T, Smith D, Stewart M, Torres S, Zhao Z, Mayeda A, Green A, Hofstetter J, Ngombu S, Scott M, Strasburger A, Sumner J, Paschall G, Mucciarelli J, Owen R, Theus S, Tompkins D, Potkin S, Reist C, Novin M, Khalaghizadeh S, Douyon R, Kumar N, Martinez B, Sponheim S, Bender T, Lucas H, Lyon A, Marggraf M, Sorensen L, Surerus C, Sison C, Amato J, Johnson D, Pagan-Howard N, Adler L, Alerpin S, Leon T, Mattocks K, Araeva N, Sullivan J, Suppes T, Bratcher K, Drag L, Fischer E, Fujitani L, Gill S, Grimm D, Hoblyn J, Nguyen T, Nikolaev E, Shere L, Relova R, Vicencio A, Yip M, Hurford I, Acheampong S, Carfagno G, Haas G, Appelt C, Brown E, Chakraborty B, Kelly E, Klima G, Steinhauer S, Hurley R, Belle R, Eknoyan D, Johnson K, Lamotte J, Granholm E, Bradshaw K, Holden J, Jones R, Le T, Molina I, Peyton M, Ruiz I, Sally L, Tapp A, Devroy S, Jain V, Kilzieh N, Maus L, Miller K, Pope H, Wood A, Meyer E, Givens P, Hicks P, Justice S, McNair K, Pena J, Tharp D, Davis L, Ban M, Cheatum L, Darr P, Grayson W, Munford J, Whitfield B, Wilson E, Melnikoff S, Schwartz B, Tureson M, D Souza D, Forselius K, Ranganathan M, Rispoli L, Sather M, Colling C, Haakenson C, Kruegar D, Muralidhar S, Ramoni R, Breeling J, Chang K, O Donnell C, Tsao P, Moser J, Brewer J, Warren S, Argyres D, Stevens B, Humphries D, Do N, Shayan S, Nguyen X, Pyarajan S, Cho K, Hauser E, Sun Y, Wilson P, McArdle R, Dellitalia L, Harley J, Whittle J. Correlates of Risk for Disinhibited Behaviors in the Million Veteran Program Cohort. JAMA Psychiatry 2024, 81: 188-197. PMID: 37938835, PMCID: PMC10633411, DOI: 10.1001/jamapsychiatry.2023.4141.Peer-Reviewed Original ResearchAltmetricConceptsSubstance use disordersPolygenic risk scoresMillion Veteran ProgramCorrelates of riskElectronic health recordsPsychiatric problemsComorbid psychiatric problemsViral hepatitis C.Chronic airway obstructionHealth recordsElectronic health record dataUS veteran populationMillion Veteran Program cohortCommon etiologic pathwayHealth care centersHealth record dataInternational Statistical ClassificationSuicide-related behaviorsAirway obstructionCohort studyHepatitis C.Recent genome-wide association studiesLiver diseaseUS veteransCare centerThe Million Veteran Program 1990–1991 Gulf War Era Survey: An Evaluation of Veteran Response, Characteristics, and Representativeness of the Gulf War Era Veteran Population
Harrington K, Quaden R, Steele L, Helmer D, Hauser E, Ahmed S, Aslan M, Radhakrishnan K, Honerlaw J, Nguyen X, Muralidhar S, Concato J, Cho K, Gaziano J, Whitbourne S, Program O. The Million Veteran Program 1990–1991 Gulf War Era Survey: An Evaluation of Veteran Response, Characteristics, and Representativeness of the Gulf War Era Veteran Population. International Journal Of Environmental Research And Public Health 2024, 21: 72. PMID: 38248536, PMCID: PMC10815483, DOI: 10.3390/ijerph21010072.Peer-Reviewed Original ResearchConceptsGulf War IllnessMillion Veteran ProgramVeteran populationVeterans Health Administration (VHA) servicesHealth conditionsComparable health statusLarge research cohortsVA Million Veteran ProgramSimilar medical conditionsHigher socioeconomic statusGW veteransMean ageVHA servicesHealth characteristicsMedical conditionsEligible veteransHealth statusResearch cohortCohortSocioeconomic statusVeterans' responsesVeteransVeteran ProgramBroader populationFull population
2023
Comparison of the Test-negative Design and Cohort Design With Explicit Target Trial Emulation for Evaluating COVID-19 Vaccine Effectiveness
Li G, Gerlovin H, Muñiz M, Wise J, Madenci A, Robins J, Aslan M, Cho K, Gaziano J, Lipsitch M, Casas J, Hernán M, Dickerman B. Comparison of the Test-negative Design and Cohort Design With Explicit Target Trial Emulation for Evaluating COVID-19 Vaccine Effectiveness. Epidemiology 2023, 35: 137-149. PMID: 38109485, PMCID: PMC11022682, DOI: 10.1097/ede.0000000000001709.Peer-Reviewed Original ResearchCitationsAltmetricConceptsTest-negative designTarget trial emulationVaccine effectivenessCohort designTrial emulationResidual confoundingCOVID-19 vaccine effectivenessHealth care-seeking behaviorBNT162b2 vaccine effectivenessCare-seeking behaviorCOVID-19 outcomesVA healthcare systemCOVID-19 vaccineBNT162b2 vaccineAbsolute riskObservational studyNationwide dataVeterans AffairsTarget trialsEffect estimatesHealthcare systemVaccineCohortNegative controlTrialsMetformin prescription for U.S. veterans with prediabetes, 2010–2019
Gulanski B, Goulet J, Radhakrishnan K, Ko J, Li Y, Rajeevan N, Lee K, Heberer K, Lynch J, Streja E, Mutalik P, Cheung K, Concato J, Shih M, Lee J, Aslan M. Metformin prescription for U.S. veterans with prediabetes, 2010–2019. Journal Of Investigative Medicine 2023, 72: 139-150. PMID: 37668313, DOI: 10.1177/10815589231201141.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsBody mass indexVeterans Health AdministrationIncident prediabetesHigh riskHealth AdministrationRetrospective observational cohort studyType 2 diabetes mellitusUse of metforminObservational cohort studyProportion of veteransMetformin prescribingGestational diabetesCohort studyMetformin prescriptionDiabetes mellitusDiabetes preventionMass indexCardiovascular diseaseMultivariable modelPrediabetesSubset of individualsMetforminU.S. veteransHealthcare systemVeteransEffectiveness of Nirmatrelvir-Ritonavir Against the Development of Post-COVID-19 Conditions Among U.S. Veterans : A Target Trial Emulation.
Ioannou G, Berry K, Rajeevan N, Li Y, Mutalik P, Yan L, Bui D, Cunningham F, Hynes D, Rowneki M, Bohnert A, Boyko E, Iwashyna T, Maciejewski M, Osborne T, Viglianti E, Aslan M, Huang G, Bajema K. Effectiveness of Nirmatrelvir-Ritonavir Against the Development of Post-COVID-19 Conditions Among U.S. Veterans : A Target Trial Emulation. Annals Of Internal Medicine 2023, 176: 1486-1497. PMID: 37903369, PMCID: PMC10620954, DOI: 10.7326/m23-1394.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsAcute COVID-19Veterans Health AdministrationUntreated comparatorsThromboembolic eventsCOVID-19Severe COVID-19Target trial emulationSARS-CoV-2Post COVID-19 conditionIndex dateVenous thromboembolismBaseline characteristicsCumulative incidencePulmonary embolismAcute infectionMedian ageOral antiviralsTrial emulationVHA careOutpatient treatmentInternational ClassificationHealth AdministrationU.S. veteransVeterans AffairsOrgan systems
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