Featured Publications
Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice JACC State-of-the-Art Review
Khera R, Oikonomou E, Nadkarni G, Morley J, Wiens J, Butte A, Topol E. Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice JACC State-of-the-Art Review. Journal Of The American College Of Cardiology 2024, 84: 97-114. PMID: 38925729, DOI: 10.1016/j.jacc.2024.05.003.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsSevere aortic stenosis detection by deep learning applied to echocardiography
Holste G, Oikonomou E, Mortazavi B, Coppi A, Faridi K, Miller E, Forrest J, McNamara R, Ohno-Machado L, Yuan N, Gupta A, Ouyang D, Krumholz H, Wang Z, Khera R. Severe aortic stenosis detection by deep learning applied to echocardiography. European Heart Journal 2023, 44: 4592-4604. PMID: 37611002, PMCID: PMC11004929, DOI: 10.1093/eurheartj/ehad456.Peer-Reviewed Original ResearchConceptsSevere aortic stenosisIndividualising intensive systolic blood pressure reduction in hypertension using computational trial phenomaps and machine learning: a post-hoc analysis of randomised clinical trials
Oikonomou EK, Spatz ES, Suchard MA, Khera R. Individualising intensive systolic blood pressure reduction in hypertension using computational trial phenomaps and machine learning: a post-hoc analysis of randomised clinical trials. The Lancet Digital Health 2022, 4: e796-e805. PMID: 36307193, PMCID: PMC9768739, DOI: 10.1016/s2589-7500(22)00170-4.Peer-Reviewed Original ResearchConceptsSystolic blood pressure controlBlood pressure controlIntensive systolic blood pressure controlType 2 diabetesPressure controlCardiovascular benefitsClinical trialsMajor adverse cardiovascular eventsFirst major adverse cardiovascular eventLarge randomised clinical trialsACCORD-BP trialAdverse cardiovascular eventsRandomised clinical trialsSystolic blood pressureCox regression analysisTreatment effectsHazard ratio estimatesACCORD-BPBP trialCardiovascular eventsBlood pressurePrimary outcomeStandard treatmentBaseline variablesIndex patientsA phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST)
Oikonomou EK, Van Dijk D, Parise H, Suchard MA, de Lemos J, Antoniades C, Velazquez EJ, Miller EJ, Khera R. A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST). European Heart Journal 2021, 42: 2536-2548. PMID: 33881513, PMCID: PMC8488385, DOI: 10.1093/eurheartj/ehab223.Peer-Reviewed Original ResearchConceptsStable chest painChest painPrimary endpointMajor adverse cardiovascular eventsNon-fatal myocardial infarctionAdverse cardiovascular eventsStudy's primary endpointCoronary artery diseaseClinical trial populationsCox regression modelParticipant-level dataSCOT-HEARTCardiovascular eventsCause mortalityHazard ratioPatients 5Artery diseaseFunctional testingPROMISE trialTrial populationMyocardial infarctionLower incidenceStudy populationPainCollected variablesPerivascular Fat Attenuation Index Stratifies Cardiac Risk Associated With High-Risk Plaques in the CRISP-CT Study
Oikonomou EK, Desai MY, Marwan M, Kotanidis CP, Antonopoulos AS, Schottlander D, Channon KM, Neubauer S, Achenbach S, Antoniades C. Perivascular Fat Attenuation Index Stratifies Cardiac Risk Associated With High-Risk Plaques in the CRISP-CT Study. Journal Of The American College Of Cardiology 2020, 76: 755-757. PMID: 32762910, DOI: 10.1016/j.jacc.2020.05.078.Peer-Reviewed Original ResearchA novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography
Oikonomou EK, Williams MC, Kotanidis CP, Desai MY, Marwan M, Antonopoulos AS, Thomas KE, Thomas S, Akoumianakis I, Fan LM, Kesavan S, Herdman L, Alashi A, Centeno EH, Lyasheva M, Griffin BP, Flamm SD, Shirodaria C, Sabharwal N, Kelion A, Dweck MR, Van Beek EJR, Deanfield J, Hopewell JC, Neubauer S, Channon KM, Achenbach S, Newby DE, Antoniades C. A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography. European Heart Journal 2019, 40: 3529-3543. PMID: 31504423, PMCID: PMC6855141, DOI: 10.1093/eurheartj/ehz592.Peer-Reviewed Original ResearchConceptsPerivascular adipose tissueFat attenuation indexCoronary CT angiographyCardiac risk predictionCoronary perivascular adipose tissueMajor adverse cardiac eventsCT angiographyRisk predictionHigh-risk plaque featuresPerivascular fat attenuation indexRadiomic featuresAdverse cardiac eventsConsecutive eligible participantsSCOT-HEART trialTraditional risk stratificationCoronary artery diseaseCoronary calcium scoreStandard coronary CT angiographyAcute myocardial infarctionCoronary inflammationCardiac eventsArtery diseaseCalcium scoreCardiac surgeryMACE predictionNon-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data
Oikonomou EK, Marwan M, Desai MY, Mancio J, Alashi A, Centeno E, Thomas S, Herdman L, Kotanidis CP, Thomas KE, Griffin BP, Flamm SD, Antonopoulos AS, Shirodaria C, Sabharwal N, Deanfield J, Neubauer S, Hopewell JC, Channon KM, Achenbach S, Antoniades C. Non-invasive detection of coronary inflammation using computed tomography and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data. The Lancet 2018, 392: 929-939. PMID: 30170852, PMCID: PMC6137540, DOI: 10.1016/s0140-6736(18)31114-0.Peer-Reviewed Original ResearchMeSH KeywordsAdipocytesAdipose TissueAdolescentAdultAgedAged, 80 and overComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary VesselsFemaleFollow-Up StudiesHumansImaging, Three-DimensionalMaleMiddle AgedPlaque, AtheroscleroticPredictive Value of TestsProportional Hazards ModelsProspective StudiesRisk AssessmentSurvival AnalysisYoung AdultConceptsRight coronary arteryProximal right coronary arteryCardiac mortalityCoronary inflammationCoronary CTACoronary arteryDerivation cohortValidation cohortOutcome dataHealth Research Oxford Biomedical Research CentreCoronary artery disease indexHigh-risk plaque featuresPerivascular fat attenuation indexCoronary artery inflammationFat attenuation indexIntensive secondary preventionCardiovascular risk factorsResidual cardiovascular riskProspective outcome dataMajor coronary arteriesHounsfield unitsLeft circumflex arteryCox regression modelRisk predictionCardiac risk predictionAssessment of Prognostic Value of Left Ventricular Global Longitudinal Strain for Early Prediction of Chemotherapy-Induced Cardiotoxicity
Oikonomou EK, Kokkinidis DG, Kampaktsis PN, Amir EA, Marwick TH, Gupta D, Thavendiranathan P. Assessment of Prognostic Value of Left Ventricular Global Longitudinal Strain for Early Prediction of Chemotherapy-Induced Cardiotoxicity. JAMA Cardiology 2019, 4: 1007-1018. PMID: 31433450, PMCID: PMC6705141, DOI: 10.1001/jamacardio.2019.2952.Peer-Reviewed Original ResearchConceptsCancer therapy-related cardiac dysfunctionGlobal longitudinal strainLeft ventricular global longitudinal strainVentricular global longitudinal strainPrognostic valueCutoff valuePublication biasMeasurement of GLSNew-onset heart failure symptomsAbsolute global longitudinal strainWorse global longitudinal strainLarge prospective multicenter studyLeft ventricular ejection fractionDiscriminatory performanceLongitudinal strainChemotherapy-Induced CardiotoxicityGLS cutoff valueSubclinical ventricular dysfunctionHeart failure symptomsProspective multicenter studyVentricular ejection fractionCochrane Library databasesRisk of biasOptimal cutoff valueBetter prognostic performanceThe role of adipose tissue in cardiovascular health and disease
Oikonomou EK, Antoniades C. The role of adipose tissue in cardiovascular health and disease. Nature Reviews Cardiology 2018, 16: 83-99. PMID: 30287946, DOI: 10.1038/s41569-018-0097-6.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsAdipose tissueCardiovascular systemCardiovascular healthInsulin resistance leadPro-atherogenic profileCardiovascular risk stratificationAdipose tissue functionAdipose tissue biologyComplex homeostatic mechanismsRisk stratificationLocal inflammationCardiovascular diseasePossible clinical translationParacrine effectsTherapeutic targetingHomeostatic mechanismsDiseaseGaseous messengerTissueClinical translationTissue biologyTissue functionCrucial regulatorCurrent knowledgeHealth
2023
Machine learning in precision diabetes care and cardiovascular risk prediction
Oikonomou E, Khera R. Machine learning in precision diabetes care and cardiovascular risk prediction. Cardiovascular Diabetology 2023, 22: 259. PMID: 37749579, PMCID: PMC10521578, DOI: 10.1186/s12933-023-01985-3.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsArtificial intelligence solutionsArtificial intelligence productsData-driven methodIntelligence solutionsArtificial intelligenceMachine learningPersonalized solutionsIntelligence productsBias mitigationMachineKey issuesPredictive modelSuch modelsSuccessful applicationRisk predictionParadigm shiftIntelligenceKey propertiesApplicationsLearningPersonalized careFrameworkSolutionCurrent regulatory frameworkHealthcareUse of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020
Dhingra L, Aminorroaya A, Oikonomou E, Nargesi A, Wilson F, Krumholz H, Khera R. Use of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020. JAMA Network Open 2023, 6: e2316634. PMID: 37285157, PMCID: PMC10248745, DOI: 10.1001/jamanetworkopen.2023.16634.Peer-Reviewed Original ResearchConceptsHealth Information National Trends SurveyUS adultsExacerbate disparitiesWearable device usersCardiovascular diseaseCardiovascular healthPopulation-based cross-sectional studySelf-reported cardiovascular diseaseCardiovascular disease risk factorsNational Trends SurveyOverall US adult populationCardiovascular risk factor profileSelf-reported accessAssociated with lower useUse of wearable devicesImprove cardiovascular healthLower household incomeLower educational attainmentUS adult populationRisk factor profileNationally representative sampleCross-sectional studyProportion of adultsTrends SurveyWearable device dataPersistence on Novel Cardioprotective Antihyperglycemic Therapies in the United States
Nargesi A, Clark C, Aminorroaya A, Chen L, Liu M, Reddy A, Amodeo S, Oikonomou E, Suchard M, McGuire D, Lin Z, Inzucchi S, Khera R. Persistence on Novel Cardioprotective Antihyperglycemic Therapies in the United States. The American Journal Of Cardiology 2023, 196: 89-98. PMID: 37012183, PMCID: PMC11007258, DOI: 10.1016/j.amjcard.2023.03.002.Peer-Reviewed Original ResearchConceptsSGLT-2iGLP-1RAsGlucagon-like peptide-1 receptor agonistsUnited States administrative claims databasesSodium-glucose cotransporter 2 inhibitorsCommercial insurancePeptide-1 receptor agonistsType 2 diabetes mellitusSodium-glucose cotransporter-2 inhibitorsConsistent medication useHealth outcome benefitsCotransporter 2 inhibitorsElevated cardiovascular riskInitiation of therapyAdministrative claims databaseProportion of daysCotransporter-2 inhibitorsRate of prescriptionAntihyperglycemic therapyCardiovascular riskDiabetes mellitusMedication useCardioprotective effectsPrescription practicesClaims database
2022
Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19
Kotanidis CP, Xie C, Alexander D, Rodrigues JCL, Burnham K, Mentzer A, O’Connor D, Knight J, Siddique M, Lockstone H, Thomas S, Kotronias R, Oikonomou EK, Badi I, Lyasheva M, Shirodaria C, Lumley SF, Constantinides B, Sanderson N, Rodger G, Chau KK, Lodge A, Tsakok M, Gleeson F, Adlam D, Rao P, Indrajeet D, Deshpande A, Bajaj A, Hudson BJ, Srivastava V, Farid S, Krasopoulos G, Sayeed R, Ho LP, Neubauer S, Newby DE, Channon KM, Deanfield J, Antoniades C, Consortium C, Ahern D, Ai Z, Ainsworth M, Allan C, Allcock A, Angus B, Ansari M, Arancibia-Cárcamo C, Aschenbrenner D, Attar M, Baillie J, Barnes E, Bashford-Rogers R, Bashyal A, Beer S, Berridge G, Beveridge A, Bibi S, Bicanic T, Blackwell L, Bowness P, Brent A, Brown A, Broxholme J, Buck D, Burnham K, Byrne H, Camara S, Ferreira I, Charles P, Chen W, Chen Y, Chong A, Clutterbuck E, Coles M, Conlon C, Cornall R, Cribbs A, Curion F, Davenport E, Davidson N, Davis S, Dendrou C, Dequaire J, Dib L, Docker J, Dold C, Dong T, Downes D, Drakesmith H, Dunachie S, Duncan D, Eijsbouts C, Esnouf R, Espinosa A, Etherington R, Fairfax B, Fairhead R, Fang H, Fassih S, Felle S, Mendoza M, Ferreira R, Fischer R, Foord T, Forrow A, Frater J, Fries A, Sanchez V, Garner L, Geeves C, Georgiou D, Godfrey L, Golubchik T, Vazquez M, Green A, Harper H, Harrington H, Heilig R, Hester S, Hill J, Hinds C, Hird C, Ho L, Hoekzema R, Hollis B, Hughes J, Hutton P, Jackson-Wood M, Jainarayanan A, James-Bott A, Jansen K, Jeffery K, Jones E, Jostins L, Kerr G, Kim D, Klenerman P, Knight J, Kumar V, Sharma P, Kurupati P, Kwok A, Lee A, Linder A, Lockett T, Lonie L, Lopopolo M, Lukoseviciute M, Luo J, Marinou S, Marsden B, Martinez J, Matthews P, Mazurczyk M, McGowan S, McKechnie S, Mead A, Mentzer A, Mi Y, Monaco C, Montadon R, Napolitani G, Nassiri I, Novak A, O'Brien D, O'Connor D, O'Donnell D, Ogg G, Overend L, Park I, Pavord I, Peng Y, Penkava F, Pinho M, Perez E, Pollard A, Powrie F, Psaila B, Quan T, Repapi E, Revale S, Silva-Reyes L, Richard J, Rich-Griffin C, Ritter T, Rollier C, Rowland M, Ruehle F, Salio M, Sansom S, Peres R, Delgado A, Sauka-Spengler T, Schwessinger R, Scozzafava G, Screaton G, Seigal A, Semple M, Sergeant M, Karali C, Sims D, Skelly D, Slawinski H, Sobrinodiaz A, Sousos N, Stafford L, Stockdale L, Strickland M, Sumray O, Sun B, Taylor C, Taylor S, Taylor A, Thongjuea S, Thraves H, Todd J, Tomic A, Tong O, Trebes A, Trzupek D, Tucci F, Turtle L, Udalova I, Uhlig H, van Grinsven E, Vendrell I, Verheul M, Voda A, Wang G, Wang L, Wang D, Watkinson P, Watson R, Weinberger M, Whalley J, Witty L, Wray K, Xue L, Yeung H, Yin Z, Young R, Youngs J, Zhang P, Zurke Y, investigators O, Banning A, Antonopoulos A, Bajaj A, Kelion A, Deshpande A, Kardos A, Hudson B, Koo B, Shirodaria C, Xie C, Kotanidis C, Mahon C, Berry C, Adlam D, Newby D, Connolly D, Scaletta D, Alexander D, Nicol E, McAlindon E, Oikonomou E, Pugliese F, Pontone G, Benedetti G, He G, West H, Kondo H, Benedek I, Das I, Deanfield J, Graby J, Greenwood J, Rodrigues J, Ge J, Channon K, Fabritz L, Fan L, Kingham L, Guglielmo M, Lyasheva M, Schmitt M, Beer M, Anderson M, Desai M, Marwan M, Takahashi N, Mehta N, Dai N, Screaton N, Sabharwal N, Maurovich-Horvat P, Rao P, Kotronias R, Kharbanda R, Preston R, Wood R, Blankstein R, Rajani R, Mirsadraee S, Munir S, Thomas S, Neubauer S, Klömpken S, Petersen S, Achenbach S, Anthony S, Mak S, Mittal T, Benedek T, Sharma V, Lin W. Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19. The Lancet Digital Health 2022, 4: e705-e716. PMID: 36038496, PMCID: PMC9417284, DOI: 10.1016/s2589-7500(22)00132-7.Peer-Reviewed Original ResearchConceptsInternal mammary arteryVascular inflammationSARS-CoV-2 variantsPrognostic valueHospital mortalityMammary arteryCT angiogramDexamethasone treatmentCOVID-19Angiography scansHuman internal mammary arteryB.1.1.7 SARS-CoV-2 variantNon-invasive imaging biomarkersBlood transcriptional modulesCytokine-driven inflammationDysregulation of coagulationAdverse clinical outcomesLong-term complicationsBritish Heart FoundationPulmonary CT angiographyNational Health Service TrustPlatelet aggregation pathwaysHealth Service TrustCT angiography scansUK National Health Service TrustsPhenomapping-Derived Tool to Individualize the Effect of Canagliflozin on Cardiovascular Risk in Type 2 Diabetes.
Oikonomou EK, Suchard MA, McGuire DK, Khera R. Phenomapping-Derived Tool to Individualize the Effect of Canagliflozin on Cardiovascular Risk in Type 2 Diabetes. Diabetes Care 2022, 45: 965-974. PMID: 35120199, PMCID: PMC9016734, DOI: 10.2337/dc21-1765.Peer-Reviewed Original ResearchConceptsCanagliflozin Cardiovascular Assessment StudyMajor adverse cardiovascular eventsType 2 diabetesHazard ratioSodium-glucose cotransporter 2 inhibitorsCardiovascular disease benefitAdverse cardiovascular eventsCotransporter 2 inhibitorsEffects of canagliflozinCanagliflozin dosesCanagliflozin's effectsCardiovascular eventsCardiovascular riskPatients 5Cardioprotective effectsSGLT2 inhibitorsDisease benefitBaseline variablesOriginal trialCanagliflozinType 2DiabetesPatientsRisk estimatesEffect estimatesThe impact of induction therapy on mortality and treated rejection in cardiac transplantation: A retrospective study
Bellumkonda L, Oikonomou EK, Hsueh C, Maulion C, Testani J, Patel J. The impact of induction therapy on mortality and treated rejection in cardiac transplantation: A retrospective study. The Journal Of Heart And Lung Transplantation 2022, 41: 482-491. PMID: 35094919, DOI: 10.1016/j.healun.2022.01.008.Peer-Reviewed Original ResearchConceptsInduction therapyCause mortalityOutcome measuresLeft ventricular assist device therapyT-cell depleting agentsVentricular assist device therapyDual organ transplantsRoutine induction therapySecondary outcome measuresTime of transplantationPrimary outcome measureCox regression modelPropensity score adjustmentRisk of rejectionPrior transplantCardiac transplantationHeart transplantationUNOS databaseAdult patientsOverall survivalDevice therapyMedian ageRetrospective studyReceptor antagonistReduced odds
2021
Biomarkers of Vascular Inflammation for Cardiovascular Risk Prognostication A Meta-Analysis
Antonopoulos A, Angelopoulos A, Papanikolaou P, Simantiris S, Oikonomou E, Vamvakaris K, Koumpoura A, Farmaki M, Trivella M, Vlachopoulos C, Tsioufis K, Antoniades C, Tousoulis D. Biomarkers of Vascular Inflammation for Cardiovascular Risk Prognostication A Meta-Analysis. JACC Cardiovascular Imaging 2021, 15: 460-471. PMID: 34801448, DOI: 10.1016/j.jcmg.2021.09.014.Peer-Reviewed Original ResearchConceptsCoronary heart diseaseVascular inflammationInflammatory biomarkersRisk stratificationPrognostic valueClinical risk factorsNet clinical benefitValue of biomarkersUse of biomarkersMeasurement of biomarkersMeta-regression analysisLack of reportingCardiovascular eventsCohort studyStable patientsEvent incidenceRisk prognosticationClinical benefitHeart diseaseRisk factorsRisk discriminationClinical practiceInflammationSuch biomarkersMeta-AnalysisStandardized measurement of coronary inflammation using cardiovascular computed tomography: integration in clinical care as a prognostic medical device
Oikonomou EK, Antonopoulos AS, Schottlander D, Marwan M, Mathers C, Tomlins P, Siddique M, Klüner LV, Shirodaria C, Mavrogiannis MC, Thomas S, Fava A, Deanfield J, Channon KM, Neubauer S, Desai MY, Achenbach S, Antoniades C. Standardized measurement of coronary inflammation using cardiovascular computed tomography: integration in clinical care as a prognostic medical device. Cardiovascular Research 2021, 117: 2677-2690. PMID: 34450625, DOI: 10.1093/cvr/cvab286.Peer-Reviewed Original ResearchMeSH KeywordsAdipose TissueAdiposityAdolescentAdultAgedAged, 80 and overAlgorithmsCloud ComputingComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary VesselsDecision Support TechniquesEnglandFemaleGermanyHeart Disease Risk FactorsHumansInflammationMaleMiddle AgedNomogramsOhioPredictive Value of TestsPrognosisRisk AssessmentTime FactorsYoung AdultConceptsFat attenuation indexPerivascular fat attenuation indexRisk factor-based modelCoronary artery inflammationClinical risk factorsFatal cardiac eventsCoronary artery diseaseCoronary inflammationRisk factorsFAI scorePlaque metricsCardiac eventsArtery inflammationAbsolute riskCoronary arteryClinical careNon-invasive detectionTraditional cardiovascular risk factorsPatient's absolute riskCardiovascular risk factorsFat compositionNet clinical benefitCardiovascular risk predictionDecision curve analysisFirst-line modalityEffects of canagliflozin on human myocardial redox signalling: clinical implications
Kondo H, Akoumianakis I, Badi I, Akawi N, Kotanidis CP, Polkinghorne M, Stadiotti I, Sommariva E, Antonopoulos AS, Carena MC, Oikonomou EK, Reus EM, Sayeed R, Krasopoulos G, Srivastava V, Farid S, Chuaiphichai S, Shirodaria C, Channon KM, Casadei B, Antoniades C. Effects of canagliflozin on human myocardial redox signalling: clinical implications. European Heart Journal 2021, 42: 4947-4960. PMID: 34293101, PMCID: PMC8691807, DOI: 10.1093/eurheartj/ehab420.Peer-Reviewed Original ResearchConceptsNADPH oxidase activityMyocardial redoxHuman cardiomyocytesNOS couplingAtrial tissueSodium-glucose cotransporter 2 inhibitorsMyocardial NADPH oxidase activityRight atrial appendage biopsiesNitric oxide synthase uncouplingCotransporter 2 inhibitorsEffects of canagliflozinHeart failure patientsBeneficial cardiac effectsExpression of inflammationRecent clinical trialsAMP kinaseHuman atrial tissueOxidase activityPrimary human cardiomyocytesAnti-apoptotic effectsTetrahydrobiopterin bioavailabilityCardiovascular outcomesCardiac effectsFailure patientsCardiac surgeryImpaired Myocardial Flow Reserve on 82Rubidium Positron Emission Tomography/Computed Tomography in Patients With Systemic Sclerosis.
Feher A, Boutagy NE, Oikonomou EK, Thorn S, Liu YH, Miller EJ, Sinusas AJ, Hinchcliff M. Impaired Myocardial Flow Reserve on 82Rubidium Positron Emission Tomography/Computed Tomography in Patients With Systemic Sclerosis. The Journal Of Rheumatology 2021, 48: 1574-1582. PMID: 34266986, PMCID: PMC10275580, DOI: 10.3899/jrheum.210040.Peer-Reviewed Original ResearchConceptsReduced Myocardial Flow ReserveMyocardial flow reserveRaynaud's phenomenonPrimary Raynaud's phenomenonSecondary Raynaud's phenomenonPatient controlsHealthy participantsFlow reservePositron Emission Tomography/Computed TomographyEmission Tomography/Computed TomographyTomography/Computed TomographyPositron emission tomography/Impaired Myocardial Flow ReserveCoronary microvascular dysfunctionLarge prospective studiesMultivariable logistic regressionEmission tomography/PET/CTSSc-RPMicrovascular dysfunctionClinical predictorsIndependent predictorsSystemic sclerosisPrognostic valueProspective study
2020
Insulin-induced vascular redox dysregulation in human atherosclerosis is ameliorated by dipeptidyl peptidase 4 inhibition
Akoumianakis I, Badi I, Douglas G, Chuaiphichai S, Herdman L, Akawi N, Margaritis M, Antonopoulos AS, Oikonomou EK, Psarros C, Galiatsatos N, Tousoulis D, Kardos A, Sayeed R, Krasopoulos G, Petrou M, Schwahn U, Wohlfart P, Tennagels N, Channon KM, Antoniades C. Insulin-induced vascular redox dysregulation in human atherosclerosis is ameliorated by dipeptidyl peptidase 4 inhibition. Science Translational Medicine 2020, 12 PMID: 32350133, PMCID: PMC7212010, DOI: 10.1126/scitranslmed.aav8824.Peer-Reviewed Original ResearchConceptsDipeptidyl peptidase-4 inhibitorsCoronary artery bypass surgeryAggressive insulin treatmentInsulin treatmentCoronary atherosclerosisEndothelial functionAbnormal responseHigh-fat diet-fed ApoEOral dipeptidyl peptidase-4 inhibitorLong-term combination therapyHuman internal mammary arteryDipeptidyl peptidase-4 inhibitionHigher cardiac mortalityPeptidase-4 inhibitionVascular insulin responsesVascular redox stateArtery bypass surgeryInternal mammary arteryInsulin resistance statusNitric oxide bioavailabilityPeptidase-4 inhibitorsPlasma DPP4 activityVascular oxidative stressRecent clinical trialsInsulin-sensitizing effects