2023
Trends, variation, and clinical characteristics of recipients of antiviral drugs and neutralising monoclonal antibodies for covid-19 in community settings: retrospective, descriptive cohort study of 23.4 million people in OpenSAFELY
Green A, Curtis H, Higgins R, Nab L, Mahalingasivam V, Smith R, Mehrkar A, Inglesby P, Drysdale H, DeVito N, Croker R, Rentsch C, Bhaskaran K, Tazare J, Zheng B, Andrews C, Bacon S, Davy S, Dillingham I, Evans D, Fisher L, Hickman G, Hopcroft L, Hulme W, Massey J, MacDonald O, Morley J, Morton C, Park R, Walker A, Ward T, Wiedemann M, Bates C, Cockburn J, Parry J, Hester F, Harper S, Douglas I, Evans S, Goldacre B, Tomlinson L, MacKenna B. Trends, variation, and clinical characteristics of recipients of antiviral drugs and neutralising monoclonal antibodies for covid-19 in community settings: retrospective, descriptive cohort study of 23.4 million people in OpenSAFELY. BMJ Medicine 2023, 2: e000276. PMID: 36936265, PMCID: PMC9951378, DOI: 10.1136/bmjmed-2022-000276.Peer-Reviewed Original ResearchDescriptive cohort studyHigh-risk groupSevere outcomesHigh riskCohort studyHome residentsRisk groupsAntiviral drugsCOVID-19Community settingsMonoclonal antibodiesCasirivimab/imdevimabLow treatment coverageNHS regionProportion of patientsCOVID-19 infectionRoutine clinical dataOpenSAFELY platformUnvaccinated patientsClinical characteristicsLiver diseaseClinical dataTreatment coverageEligibility criteriaPatients
2022
Recording of ’COVID-19 vaccine declined‘: a cohort study on 57.9 million National Health Service patients’ records in situ using OpenSAFELY, England, 8 December 2020 to 25 May 2021
Curtis HJ, Inglesby P, MacKenna B, Croker R, Hulme WJ, Rentsch CT, Bhaskaran K, Mathur R, Morton CE, Bacon SC, Smith RM, Evans D, Mehrkar A, Tomlinson L, Walker AJ, Bates C, Hickman G, Ward T, Morley J, Cockburn J, Davy S, Williamson EJ, Eggo RM, Parry J, Hester F, Harper S, O’Hanlon S, Eavis A, Jarvis R, Avramov D, Griffiths P, Fowles A, Parkes N, Evans SJ, Douglas IJ, Smeeth L, Goldacre B. Recording of ’COVID-19 vaccine declined‘: a cohort study on 57.9 million National Health Service patients’ records in situ using OpenSAFELY, England, 8 December 2020 to 25 May 2021. Eurosurveillance 2022, 27: 2100885. PMID: 35983770, PMCID: PMC9389857, DOI: 10.2807/1560-7917.es.2022.27.33.2100885.Peer-Reviewed Original ResearchConceptsCOVID-19 vaccinationCOVID-19 vaccineCohort studyPriority patientsRetrospective cohort studyPrimary care recordsMore deprived areasUnvaccinated patientsSubsequent vaccinationSouth Asian peopleSouth Asian populationGeneral practicePatientsCare recordsClinical record systemsVaccinationNHS EnglandPatient recordsVaccineDeprived areasAsian populationsOpenSAFELYDemographic subgroupsRecord systemDemographic factorsPotentially inappropriate medication use by level of polypharmacy among US Veterans 49–64 and 65–70 years old
Guillot J, Rentsch CT, Gordon KS, Justice AC, Bezin J. Potentially inappropriate medication use by level of polypharmacy among US Veterans 49–64 and 65–70 years old. Pharmacoepidemiology And Drug Safety 2022, 31: 1056-1074. PMID: 35780391, PMCID: PMC9464694, DOI: 10.1002/pds.5506.Peer-Reviewed Original ResearchConceptsLevel of polypharmacyRace/ethnicityPIM prevalencePrevalence of PIMsInappropriate medication useElectronic health recordsCommon PIMsPharmacy fillsPROMPT criteriaInappropriate medicationsOlder patientsMedication usePsychotropic medicationsRefill recordsPolypharmacyPatientsVeterans AffairsMedicationsPrevalenceHealth recordsFiscal year 2016AgeMeaningful differencesSexTarget ageAssociation of topiramate prescribed for any indication with reduced alcohol consumption in electronic health record data
Kranzler HR, Leong SH, Naps M, Hartwell EE, Fiellin DA, Rentsch CT. Association of topiramate prescribed for any indication with reduced alcohol consumption in electronic health record data. Addiction 2022, 117: 2826-2836. PMID: 35768956, PMCID: PMC10317468, DOI: 10.1111/add.15980.Peer-Reviewed Original ResearchConceptsAUDIT-C scoresAlcohol use disorderElectronic health record dataHealth record dataUse disordersNEG patientsTopiramate dosageAlcohol Use Disorders Identification Test-Consumption scoresPropensity score-matched groupsHistory of AUDParallel group comparisonPropensity score-matched comparison groupRecord dataBaseline drinking levelsReduced alcohol consumptionHealth care systemTopiramate prescriptionsPre-post differencesAUD historyTopiramate's effectsPatientsRecord diagnosisAlcohol consumptionTopiramateComparison group
2021
A comprehensive high cost drugs dataset from the NHS in England - An OpenSAFELY-TPP Short Data Report
Rowan A, Bates C, Hulme W, Evans D, Davy S, Kennedy N, Galloway J, Mansfield K, Bechman K, Matthewman J, Yates M, Brown J, Schultze A, Norton S, Walker A, Morton C, Bhaskaran K, Rentsch C, Williamson E, Croker R, Bacon S, Hickman G, Ward T, Green A, Fisher L, Curtis H, Tazare J, Eggo R, Inglesby P, Cockburn J, McDonald H, Mathur R, Wong A, Forbes H, Parry J, Hester F, Harper S, Douglas I, Smeeth L, Tomlinson L, Lees C, Evans S, Smith C, Langan S, Mehkar A, MacKenna B, Goldacre B. A comprehensive high cost drugs dataset from the NHS in England - An OpenSAFELY-TPP Short Data Report. Wellcome Open Research 2021, 6: 360. PMID: 35634533, PMCID: PMC9120928, DOI: 10.12688/wellcomeopenres.17360.1.Peer-Reviewed Original ResearchHigh-cost drugsSevere COVID-19 outcomesMonths of drugUnique patient IDCOVID-19 outcomesCOVID-19 pandemicLong-term conditionsNHS DigitalNHS EnglandCertain medicinesPatientsSpecialist medicinePatient IDDrugsDrug namesHospitalAverage numberMedicine dataMedicineDescriptive analysisReportYearsOpenSAFELYPandemicData reportsOpenSAFELY: impact of national guidance on switching anticoagulant therapy during COVID-19 pandemic
Collaborative T, Curtis HJ, MacKenna B, Walker AJ, Croker R, Mehrkar A, Morton C, Bacon S, Hickman G, Inglesby P, Bates C, Evans D, Ward T, Cockburn J, Davy S, Bhaskaran K, Schultze A, Rentsch CT, Williamson E, Hulme W, Tomlinson L, Mathur R, Drysdale H, Eggo RM, Wong AY, Forbes H, Parry J, Hester F, Harper S, Douglas I, Smeeth L, Goldacre B. OpenSAFELY: impact of national guidance on switching anticoagulant therapy during COVID-19 pandemic. Open Heart 2021, 8: e001784. PMID: 34785588, PMCID: PMC8595296, DOI: 10.1136/openhrt-2021-001784.Peer-Reviewed Original ResearchMeSH KeywordsAgedAnticoagulantsBlood CoagulationBlood Coagulation TestsCOVID-19Drug MonitoringDrug PrescriptionsDrug SubstitutionDrug UtilizationEnglandFactor Xa InhibitorsFemaleHumansMaleMiddle AgedPatient SafetyPractice Guidelines as TopicPractice Patterns, Physicians'Primary Health CareRetrospective StudiesRisk AssessmentRisk FactorsState MedicineWarfarinConceptsWarfarin patientsNational Health ServiceCOVID-19 pandemicNational guidanceCare home residencyINR test resultsRenal function testsFrequent blood testingSafety alertsRoutine clinical dataAtrial fibrillation diagnosisElevated INRMedication changesOral anticoagulantsAnticoagulant therapyCohort studyAppropriate patientsINR testsFunction testsBlood testingPrimary careClinical dataDOACPatientsWarfarinTrends and clinical characteristics of 57.9 million COVID-19 vaccine recipients: a federated analysis of patients’ primary care records in situ using OpenSAFELY
Curtis HJ, Inglesby P, Morton CE, MacKenna B, Green A, Hulme W, Walker AJ, Morley J, Mehrkar A, Bacon S, Hickman G, Bates C, Croker R, Evans D, Ward T, Cockburn J, Davy S, Bhaskaran K, Schultze A, Rentsch CT, Williamson EJ, Rowan A, Fisher L, McDonald HI, Tomlinson L, Mathur R, Drysdale H, Eggo RM, Wing K, Wong AY, Forbes H, Parry J, Hester F, Harper S, O’Hanlon S, Eavis A, Jarvis R, Avramov D, Griffiths P, Fowles A, Parkes N, Douglas IJ, Evans SJ, Smeeth L, Goldacre B, . Trends and clinical characteristics of 57.9 million COVID-19 vaccine recipients: a federated analysis of patients’ primary care records in situ using OpenSAFELY. British Journal Of General Practice 2021, 72: bjgp.2021.0376. PMID: 34750106, PMCID: PMC8589463, DOI: 10.3399/bjgp.2021.0376.Peer-Reviewed Original ResearchConceptsVaccine recipientsVaccine coverageCOVID-19 vaccine recipientsFirst COVID-19 vaccinationNHS EnglandPre-existing medical conditionsPrimary care recordsLow vaccination coverageCOVID-19 vaccinationSevere mental illnessCare home residentsClinical characteristicsCohort studySecond doseVaccination coverageHome residentsMedical conditionsGeneral practiceMass vaccinationNHS dataCare recordsPatientsJoint CommitteeVaccine rolloutMental illnessClinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY
Walker AJ, MacKenna B, Inglesby P, Tomlinson L, Rentsch CT, Curtis HJ, Morton CE, Morley J, Mehrkar A, Bacon S, Hickman G, Bates C, Croker R, Evans D, Ward T, Cockburn J, Davy S, Bhaskaran K, Schultze A, Williamson EJ, Hulme WJ, McDonald HI, Mathur R, Eggo RM, Wing K, Wong AY, Forbes H, Tazare J, Parry J, Hester F, Harper S, O’Hanlon S, Eavis A, Jarvis R, Avramov D, Griffiths P, Fowles A, Parkes N, Douglas IJ, Evans SJ, Smeeth L, Goldacre B, . Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY. British Journal Of General Practice 2021, 71: bjgp.2021.0301. PMID: 34340970, PMCID: PMC8340730, DOI: 10.3399/bjgp.2021.0301.Peer-Reviewed Original ResearchConceptsLong COVIDEnglish primary carePrimary careDiagnostic codesPopulation-based cohort studyAcute COVID-19Different diagnostic thresholdsProportion of peoplePlanning of servicesPersistent symptomsCohort studyGeneral practiceClinicians' understandingDiagnostic thresholdNHS EnglandPatient recordsClinical codesClinical codingCareCOVID-19East of EnglandPatientsDemographic factorsCOVIDWeeksHydroxychloroquine treatment does not reduce COVID-19 mortality; underdosing to the wrong patients? – Authors' reply
Rentsch CT, DeVito NJ, MacKenna B, Morton CE, Bhaskaran K, Brown JP, Schultze A, Hulme WJ, Croker R, Walker AJ, Williamson EJ, Bates C, Bacon S, Mehrkar A, Curtis HJ, Evans D, Wing K, Inglesby P, Mathur R, Drysdale H, Wong AYS, McDonald HI, Cockburn J, Forbes H, Parry J, Hester F, Harper S, Smeeth L, Douglas IJ, Dixon WG, Evans SJW, Tomlinson L, Goldacre B. Hydroxychloroquine treatment does not reduce COVID-19 mortality; underdosing to the wrong patients? – Authors' reply. The Lancet Rheumatology 2021, 3: e172-e173. PMID: 33655224, PMCID: PMC7906669, DOI: 10.1016/s2665-9913(21)00030-8.Peer-Reviewed Original Research
2019
Association Between Gabapentin Receipt for Any Indication and Alcohol Use Disorders Identification Test—Consumption Scores Among Clinical Subpopulations With and Without Alcohol Use Disorder
Rentsch CT, Fiellin DA, Bryant KJ, Justice AC, Tate JP. Association Between Gabapentin Receipt for Any Indication and Alcohol Use Disorders Identification Test—Consumption Scores Among Clinical Subpopulations With and Without Alcohol Use Disorder. Alcohol Clinical And Experimental Research 2019, 43: 522-530. PMID: 30620410, PMCID: PMC6397056, DOI: 10.1111/acer.13953.Peer-Reviewed Original ResearchConceptsAlcohol use disorderAlcohol Use Disorders Identification Test-Consumption scoresAUDIT-C scoresAlcohol consumptionUnexposed patientsClinical trialsUse disordersBaseline levelsVeterans Aging Cohort StudyDoses of gabapentinAging Cohort StudyImpact of gabapentinSubstance use treatmentDifferences linear regression modelGabapentin doseCohort studyCurrent medicationsBaseline auditMultivariable differenceClinical indicationsAUD historyPatientsGabapentinClinical subpopulationsConsecutive days
2018
Viral suppression among persons in HIV care in the United States during 2009–2013: sampling bias in Medical Monitoring Project surveillance estimates
Bradley H, Althoff KN, Buchacz K, Brooks JT, Gill MJ, Horberg MA, Kitahata MM, Marconi V, Mayer KH, Mayor A, Moore R, Mugavero M, Napravnik S, Paz-Bailey G, Prejean J, Rebeiro PF, Rentsch CT, Shouse RL, Silverberg MJ, Sullivan PS, Thorne JE, Yehia B, Rosenberg ES. Viral suppression among persons in HIV care in the United States during 2009–2013: sampling bias in Medical Monitoring Project surveillance estimates. Annals Of Epidemiology 2018, 31: 3-7. PMID: 30529086, PMCID: PMC6420358, DOI: 10.1016/j.annepidem.2018.11.005.Peer-Reviewed Original ResearchConceptsMedical Monitoring ProjectHIV careCare attendanceSurveillance estimatesNorth American AIDS Cohort CollaborationHIV care attendanceMultivariable regression modelsWeighted population estimatesCohort CollaborationVS statusViral suppressionCohort dataNumber of personsConfidence intervalsCareCalendar yearFull calendar yearRegression modelsLast testAttendancePersonsHIVPatientsCareful examination
2015
Association between vitamin D deficiency and methicillin-resistant Staphylococcus aureus infection
Thomason J, Rentsch C, Stenehjem EA, Hidron AI, Rimland D. Association between vitamin D deficiency and methicillin-resistant Staphylococcus aureus infection. Infection 2015, 43: 715-722. PMID: 26141819, DOI: 10.1007/s15010-015-0815-5.Peer-Reviewed Original ResearchConceptsMRSA-infected patientsMethicillin-resistant Staphylococcus aureus (MRSA) infectionsVitamin D levelsStaphylococcus aureus infectionMRSA infectionD levelsInfected patientsAureus infectionLow serum vitamin D levelsMean vitamin D levelSerum vitamin D levelsMultivariate logistic regression modelVitamin D deficiencyMultivariate logistic regressionPotential confounding variablesLogistic regression modelsMethodsAll patientsD deficiencyHIV statusVitamin DResultsA totalInfection databasePatientsConfounding variablesInfectionErratum to: Alcohol-Related Diagnoses and All-Cause Hospitalization Among HIV-Infected and Uninfected Patients: A Longitudinal Analysis of United States Veterans from 1997 to 2011
Rentsch C, Tate JP, Akgün KM, Crystal S, Wang KH, Ryan Greysen S, Wang EA, Bryant KJ, Fiellin DA, Justice AC, Rimland D. Erratum to: Alcohol-Related Diagnoses and All-Cause Hospitalization Among HIV-Infected and Uninfected Patients: A Longitudinal Analysis of United States Veterans from 1997 to 2011. AIDS And Behavior 2015, 20: 565-565. PMID: 25972072, PMCID: PMC5021303, DOI: 10.1007/s10461-015-1072-4.Peer-Reviewed Case Reports and Technical NotesAlcohol-Related Diagnoses and All-Cause Hospitalization Among HIV-Infected and Uninfected Patients: A Longitudinal Analysis of United States Veterans from 1997 to 2011
Rentsch C, Tate JP, Akgün KM, Crystal S, Wang KH, Ryan Greysen S, Wang EA, Bryant KJ, Fiellin DA, Justice AC, Rimland D. Alcohol-Related Diagnoses and All-Cause Hospitalization Among HIV-Infected and Uninfected Patients: A Longitudinal Analysis of United States Veterans from 1997 to 2011. AIDS And Behavior 2015, 20: 555-564. PMID: 25711299, PMCID: PMC4550577, DOI: 10.1007/s10461-015-1025-y.Peer-Reviewed Original ResearchConceptsAlcohol-related diagnosesHospitalization ratesUnited States veteransUninfected patientsCause hospitalizationHIV infectionStates veteransUninfected individualsMultivariable Cox proportional hazards modelsCox proportional hazards modelOverall hospitalization rateProportional hazards modelCancer admissionsAntiretroviral therapyMultivariable adjustmentHIV serostatusComorbidity variablesHospitalization trendsRelative riskHigh riskHazards modelHIVHospitalizationDisease categoriesPatients
2014
Comparison of colorectal cancer screening and diagnoses in HIV-positive and HIV-negative veterans
Guest JL, Rentsch CT, Rimland D. Comparison of colorectal cancer screening and diagnoses in HIV-positive and HIV-negative veterans. AIDS Care 2014, 26: 1490-1493. PMID: 25008192, DOI: 10.1080/09540121.2014.933768.Peer-Reviewed Original ResearchConceptsFecal occult blood testingHIV-positive patientsColorectal cancerYounger ageAtlanta VA Medical CenterHIV-negative veteransOccult blood testingHIV-negative controlsHIV-positive casesColorectal cancer screeningPercent of casesVA Medical CenterYears of ageCRC ratesCRC incidenceHIV statusBlood testingCancer screeningMedical CenterHigh incidenceScreening typeAverage ageHIVPatientsColon polyps
2013
A Comparison of HAART Outcomes between the US Military HIV Natural History Study (NHS) and HIV Atlanta Veterans Affairs Cohort Study (HAVACS)
Guest JL, Weintrob AC, Rimland D, Rentsch C, Bradley WP, Agan BK, Marconi VC, Group I. A Comparison of HAART Outcomes between the US Military HIV Natural History Study (NHS) and HIV Atlanta Veterans Affairs Cohort Study (HAVACS). PLOS ONE 2013, 8: e62273. PMID: 23658717, PMCID: PMC3641058, DOI: 10.1371/journal.pone.0062273.Peer-Reviewed Original ResearchConceptsNatural history studiesUS Military HIV Natural History StudyVeterans AffairsCohort studyClinical outcomesHIV treatmentComprehensive HIV treatmentHealthcare systemHistory studiesClinic retentionHAART initiationHAART outcomesCause mortalityAIDS eventsHIV diagnosisSurvival disparitiesStudy cohortDemographic variablesMedication adherenceCrude analysisSurvival ratePatientsSubstance abuseHIVCare