2022
Circulating T Cells and Cardiovascular Risk in People With and Without HIV Infection
Kundu S, Freiberg MS, Tracy RP, So-Armah KA, Koethe JR, Duncan MS, Tindle HA, Beckman JA, Feinstein MJ, McDonnell WJ, Justice A, Doyle MF, Study V. Circulating T Cells and Cardiovascular Risk in People With and Without HIV Infection. Journal Of The American College Of Cardiology 2022, 80: 1633-1644. PMID: 36265959, DOI: 10.1016/j.jacc.2022.08.756.Peer-Reviewed Original ResearchConceptsT cell subsetsT helper type 17 (Th17) cellsCVD risk factorsIncident CVD eventsType 17 cellsIncident CVDCell subsetsHIV infectionCVD eventsRisk factorsInternational ClassificationT effector memory cellsRe-expressing CD45RAEffector memory cellsSubset of CD4Cardiovascular disease riskProportional hazards regressionT helper cellsMedian participant ageLow CD4Cardiovascular riskObservational cohortPrevalent CVDCVD incidenceRevision diagnosisUsing the biomarker cotinine and survey self-report to validate smoking data from United States Veterans Health Administration electronic health records
McGinnis K, Skanderson M, Justice A, Tindle H, Akgün K, Wrona A, Freiberg M, Goetz M, Rodriguez-Barradas M, Brown S, Crothers K. Using the biomarker cotinine and survey self-report to validate smoking data from United States Veterans Health Administration electronic health records. JAMIA Open 2022, 5: ooac040. PMID: 37252267, PMCID: PMC9154288, DOI: 10.1093/jamiaopen/ooac040.Peer-Reviewed Original ResearchICD-10 codesClinical remindersCurrent smokingSmoking dataSelf-reported smoking statusVeterans Health Administration electronic health recordsCohort Study participantsElectronic health record dataHealth record dataElectronic health recordsSmoking informationSmoking statusSalivary cotinineEpidemiologic studiesInternational ClassificationSmokingCotinineStudy participantsICD-10Health systemHealth recordsRecord dataKappa statisticsAfrican AmericansReminders
2020
Serious Falls in Middle‐Aged Veterans: Development and Validation of a Predictive Risk Model
Womack JA, Murphy TE, Bathulapalli H, Smith A, Bates J, Jarad S, Redeker NS, Luther SL, Gill TM, Brandt CA, Justice AC. Serious Falls in Middle‐Aged Veterans: Development and Validation of a Predictive Risk Model. Journal Of The American Geriatrics Society 2020, 68: 2847-2854. PMID: 32860222, PMCID: PMC7744431, DOI: 10.1111/jgs.16773.Peer-Reviewed Original ResearchConceptsMiddle-aged veteransVeterans Health AdministrationOpioid useSerious fallsAlcohol Use Disorders Identification Test-Consumption scoresCategory-free net reclassification improvementIllicit substance use disordersMental health comorbiditiesPrescription opioid useMultivariable logistic regressionNet reclassification improvementSubstance use disordersQuality of lifeHazardous alcohol usePredictive risk modelChronic medicationsCohort studyHealth comorbiditiesNinth RevisionReclassification improvementGeriatric healthInjury codesHazardous alcoholInternational ClassificationUse disorders
2010
The need for validation of large administrative databases: Veterans Health Administration ICD-9CM coding of exudative age-related macular degeneration and ranibizumab usage
Latkany P, Duggal M, Goulet J, Paek H, Rambo M, Palmisano P, Levin W, Erdos J, Justice A, Brandt C. The need for validation of large administrative databases: Veterans Health Administration ICD-9CM coding of exudative age-related macular degeneration and ranibizumab usage. Journal Of Ocular Biology, Diseases, And Informatics 2010, 3: 30-34. PMID: 21139706, PMCID: PMC2956455, DOI: 10.1007/s12177-010-9052-4.Peer-Reviewed Original ResearchExudative age-related macular degenerationAge-related macular degenerationExcellent positive predictive valuePositive predictive valuePredictive valueMacular degenerationLarge electronic medical record systemsClinical Modification codingLarge administrative databaseNegative predictive valueElectronic medical record systemVA ConnecticutMedical record systemChart reviewNinth RevisionOphthalmology clinicAdministrative databasesClinical informationInternational ClassificationDistinct patientsTherapy policyRanibizumabPatientsRecord systemDegeneration
2007
Do Patterns of Comorbidity Vary by HIV Status, Age, and HIV Severity?
Goulet JL, Fultz SL, Rimland D, Butt A, Gibert C, Rodriguez-Barradas M, Bryant K, Justice AC. Do Patterns of Comorbidity Vary by HIV Status, Age, and HIV Severity? Clinical Infectious Diseases 2007, 45: 1593-1601. PMID: 18190322, PMCID: PMC3687553, DOI: 10.1086/523577.Peer-Reviewed Original ResearchConceptsHuman immunodeficiency virusCD4 cell countPatterns of comorbidityHIV infectionHIV statusCell countHIV severityOlder human immunodeficiency virusPrimary care guidelinesClinical Modification codesCells/Pulmonary diseaseComorbid conditionsMultivariable analysisViral loadCare guidelinesImmunodeficiency virusComorbiditiesInternational ClassificationMultimorbidityInfectionPresence of conditionsVeteransAgeDisease