2025
High Risk of Persistence and Risk of Dysplasia after Ultrashort Barrett's Diagnosis.
Skef W, Haydel J, Rao A, Allencherril R, George R, Ketwaroo G, Thrift A, El-Serag H, Wenker T. High Risk of Persistence and Risk of Dysplasia after Ultrashort Barrett's Diagnosis. The American Journal Of Gastroenterology 2025 PMID: 40052679, DOI: 10.14309/ajg.0000000000003383.Peer-Reviewed Original ResearchFollow-up EGDRisk of dysplasiaBody mass indexBarrett's esophagusPersistent BEFollow-upCohort of United States veteransWhite raceLong segment BEUnited States veteransHispanic ethnicityPredictor of dysplasiaFollow-up endoscopyClinical risk factorsRetrospective cohort studyNon-Hispanic Black patientsNon-HispanicRisk of persistenceProportion of non-HispanicChi-square testConsecutive patientsStates veteransPathology databaseHighest risk of persistenceBE diagnosisVoxel-Wise Map of Intracerebral Hemorrhage Locations Associated With Worse Outcomes
Karam G, Chen M, Zeevi D, Harms B, Berson E, Torres-Lopez V, Rivier C, Malhotra A, Qureshi A, Falcone G, Sheth K, Payabvash S. Voxel-Wise Map of Intracerebral Hemorrhage Locations Associated With Worse Outcomes. Stroke 2025, 56: 868-877. PMID: 40052269, DOI: 10.1161/strokeaha.124.048453.Peer-Reviewed Original ResearchConceptsImpact of intracerebral hemorrhageAssociated with worse outcomesClinical risk factorsVoxel-wise mapsMapping of brain regionsBaseline hematomaVoxel-wise analysisHematoma volumeICH locationBrain regionsValidation cohortWorse outcomesPresence of intraventricular hemorrhageRisk factorsBaseline hematoma volumeModified Rankin Scale scorePoor scan qualityMulticenter clinical trialRankin Scale scoreDeep white matterLow-risk categoryComprehensive stroke centerIntraventricular hemorrhageConsecutive patientsPatient agePolygenic score integrating neurodegenerative and vascular risk informs dementia risk stratification
D'Aoust T, Clocchiatti‐Tuozzo S, Rivier C, Mishra A, Hachiya T, Grenier‐Boley B, Soumaré A, Duperron M, Le Grand Q, Bouteloup V, Proust‐Lima C, Samieri C, Neuffer J, Sargurupremraj M, Chêne G, Helmer C, Thibault M, Amouyel P, Lambert J, Kamatani Y, Jacqmin‐Gadda H, Tregouët D, Inouye M, Dufouil C, Falcone G, Debette S. Polygenic score integrating neurodegenerative and vascular risk informs dementia risk stratification. Alzheimer's & Dementia 2025, 21: e70014. PMID: 40042447, PMCID: PMC11881617, DOI: 10.1002/alz.70014.Peer-Reviewed Original ResearchConceptsOlder community-dwelling peopleCommunity-dwelling peopleDementia risk stratificationVascular contribution to dementiaAssociated with dementia riskGenetic riskDementia clinical trialsApo E4Polygenic risk scoresGenetic risk groupsHigh-risk individualsDementia riskImprove risk predictionEast Asian ancestryAD-PRSPopulation-basedPolygenic scoresRisk stratificationMemory-clinic patientsPrevention programsClinical risk factorsDementiaClinical participantsRisk scoreAlzheimer's diseaseDetection of pulmonary hypertension in preterm infants with bronchopulmonary dysplasia using oxygen saturation data
Ramanand P, Indic P, Gentle S, Ambalavanan N. Detection of pulmonary hypertension in preterm infants with bronchopulmonary dysplasia using oxygen saturation data. Pediatric Research 2025, 1-8. PMID: 39915610, DOI: 10.1038/s41390-025-03891-8.Peer-Reviewed Original ResearchDetection of pulmonary hypertensionBronchopulmonary dysplasiaPreterm infantsPulmonary hypertensionClinical risk factorsOxygen saturation dataBedside markersPresence of patent ductus arteriosusRisk factorsSignificant clinical risk factorsPatent ductus arteriosusIncreased risk of mortalityMultivariate logistic regression modelIdentification of PHPresence of PHRisk of mortalityOxygen saturation variabilityDuctus arteriosusClinical courseBackgroundPulmonary hypertensionClinical featuresPretermLogistic regression modelsAssociated PHIncreased riskPredictors of Venous Thromboembolism Following Geriatric Distal Femur Fracture Fixation: Are These Patients at Higher Risk Compared With Hip Fracture Patients?
Seddio A, Vasudevan R, Gouzoulis M, Jabbouri S, Grauer J, Fram B. Predictors of Venous Thromboembolism Following Geriatric Distal Femur Fracture Fixation: Are These Patients at Higher Risk Compared With Hip Fracture Patients? JAAOS Global Research And Reviews 2025, 9: e24.00246. PMID: 39823200, PMCID: PMC11745856, DOI: 10.5435/jaaosglobal-d-24-00246.Peer-Reviewed Original ResearchConceptsOdds of venous thromboembolismDirect oral anticoagulantsVenous thromboembolismHeightened oddsHFx patientsIncreased odds of VTEPredictors of venous thromboembolismRisk factors of venous thromboembolismIncidence of venous thromboembolismRate of venous thromboembolismAssociated with considerable morbidityAssociated with reduced oddsFactors of venous thromboembolismEffective therapeutic optionIndependent risk factorClinical risk factorsHip fracture patientsRetrospective cohort studyFemur fracture fixationCoagulopathy disordersOral anticoagulantsElixhauser Comorbidity IndexSurgical managementActive cancerDistal femur fracture fixationBiomarker Panels for Discriminating Risk of CKD Progression in Children.
Greenberg J, Abraham A, Xu Y, Schelling J, Coca S, Schrauben S, Wilson F, Waikar S, Vasan R, Gutierrez O, Shlipak M, Ix J, Warady B, Kimmel P, Bonventre J, Parikh C, Denburg M, Furth S. Biomarker Panels for Discriminating Risk of CKD Progression in Children. Journal Of The American Society Of Nephrology 2025 PMID: 39820177, DOI: 10.1681/asn.0000000602.Peer-Reviewed Original ResearchPlasma KIM-1CKD progressionKIM-1Alpha 1-microglobulinUrine albumin/creatinineBaseline urine protein-to-creatinine ratiosBiomarker panelRisk factorsRisk of CKD progressionAssociated with CKD progressionUrine alpha-1-microglobulinRisk group classificationProtein-to-creatinine ratioUrine protein-to-creatinine ratioClinical risk factorsChildren 6 monthsHigh-risk groupUrine KIM-1Clinically relevant biomarkersConventional risk factorsCombination of biomarkersTubular healthBaseline eGFRMedian ageEGFR decline
2024
Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT)
Dierksen F, Sommer J, Tran A, Lin H, Haider S, Maier I, Aneja S, Sanelli P, Malhotra A, Qureshi A, Claassen J, Park S, Murthy S, Falcone G, Sheth K, Payabvash S. Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT). Diagnostics 2024, 14: 2827. PMID: 39767188, PMCID: PMC11674633, DOI: 10.3390/diagnostics14242827.Peer-Reviewed Original ResearchIntegrated discrimination indexNet reclassification indexPerihematomal edemaHead computed tomographyIntracerebral hemorrhageComputed tomographyClinical variablesClinical predictors of poor outcomeOutcome predictionAcute supratentorial intracerebral hemorrhageAdmission head computed tomographyRadiomic featuresNon-contrast head computed tomographyPredictors of poor outcomeModified Rankin Scale scoreIntracerebral hemorrhage scoreSupratentorial intracerebral hemorrhageIntracerebral hemorrhage patientsClinical risk factorsRankin Scale scoreReceiver operating characteristic areaOperating characteristics areaSecondary brain injuryHematoma evacuationPatient selectionParental Reflective Functioning on the Parent Development Interview: A narrative review of measurement, association, and future directions
Slade A, Sleed M. Parental Reflective Functioning on the Parent Development Interview: A narrative review of measurement, association, and future directions. Infant Mental Health Journal 2024, 45: 464-480. PMID: 38650168, DOI: 10.1002/imhj.22114.Peer-Reviewed Original ResearchParent Development InterviewReflective functioningSecure parent-child relationshipQuality of parental representationsDevelopment InterviewIntergenerational transmission of attachmentParental reflective functioningTransmission of attachmentParent-child interactionsParent-child relationshipPRF scalesParental representationsChild attachmentParental mentalizationParental RFChild outcomesIntergenerational transmissionNarrative reviewCaregiving capacityReview of measuresParentsChildrenClinical risk factorsMentalAttachmentArtificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging
Feher A, Bednarski B, Miller R, Shanbhag A, Lemley M, Miras L, Sinusas A, Miller E, Slomka P. Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging. Journal Of Nuclear Medicine 2024, 65: jnumed.123.266761. PMID: 38548351, PMCID: PMC11064832, DOI: 10.2967/jnumed.123.266761.Peer-Reviewed Original ResearchConceptsMyocardial perfusion imagingHF hospitalizationHeart failureStress left ventricular ejection fractionPerfusion imagingHF exacerbationPredictive of HF hospitalizationsSPECT/CT myocardial perfusion imagingMyocardial perfusionInternational cohortAcute heart failure exacerbationMedian follow-upVentricular ejection fractionReceiver-operating-characteristic curveClinical risk factorsHeart failure exacerbationExternal validation cohortAcute HF exacerbationPrevent HF hospitalizationsImaging parametersCalcium scoreEjection fractionClinical parametersCT scanValidation cohortInternational Prognostic Score for Nodular Lymphocyte–Predominant Hodgkin Lymphoma
Binkley M, Flerlage J, Savage K, Akhtar S, Steiner R, Zhang X, Dickinson M, Prica A, Major A, Hendrickson P, Hopkins D, Ng A, Casulo C, Baron J, Roberts K, Al Kendi J, Balogh A, Ricardi U, Torka P, Specht L, De Silva R, Pickard K, Blazin L, Henry M, Smith C, Halperin D, Brady J, Brennan B, Senchenko M, Reeves M, Hoppe B, Terezakis S, Talaulikar D, Picardi M, Kirova Y, Fergusson P, Hawkes E, Lee D, Doo N, Barraclough A, Cheah C, Ku M, Hamad N, Mutsando H, Gilbertson M, Marconi T, Viiala N, Maurer M, Eichenauer D, Hoppe R, Borchmann P, Fuchs M, Hartmann S, Eich H, Lo A, Skinnider B, Rauf M, Maghfoor I, Pinnix C, Milgrom S, Vega F, Alomari M, Collins G, Advani R, Metzger M, Wirth A, Tsang R, Smith S, Kelsey C, McKay P, Koenig J, Constine L, Sakthivel K, Plastaras J, Gao S, Al Rahbi N, Levis M, Sridhar A, Shah N, Osborne W, Chang I, Miall F, Mikhaeel G, Penn A, Volchkov E, Della Pepa R, Northend M, Opat S, Salvaris R, Tedjaseputra A, Palese M, Shankar A, Natkunam Y, Kelly K. International Prognostic Score for Nodular Lymphocyte–Predominant Hodgkin Lymphoma. Journal Of Clinical Oncology 2024, 42: 2271-2280. PMID: 38531001, DOI: 10.1200/jco.23.01655.Peer-Reviewed Original ResearchNodular lymphocyte-predominant Hodgkin lymphomaProgression-free survivalLymphocyte-predominant Hodgkin lymphomaInternational Prognostic ScoreImmunoarchitectural patternsOverall survivalHodgkin lymphomaPrognostic scoreSplenic involvementAssociated with worse progression-free survivalAssociated with progression-free survivalDe-escalation of therapyMedian follow-upAge of patientsProspective clinical trialHigh-risk patientsStage III-IVClinical risk factorsRisk of transformationStage I to IIB symptomsAdult patientsIII-IVActive surveillanceRare cancersUsing clinical and genetic risk factors for risk prediction of 8 cancers in the UK Biobank
Hu J, Ye Y, Zhou G, Zhao H. Using clinical and genetic risk factors for risk prediction of 8 cancers in the UK Biobank. JNCI Cancer Spectrum 2024, 8: pkae008. PMID: 38366150, PMCID: PMC10919929, DOI: 10.1093/jncics/pkae008.Peer-Reviewed Original ResearchPolygenic risk scoresUK BiobankCancer riskClinical risk factorsRisk of breast cancerRisk factorsPolygenic risk score modelHigh risk of developing cancerRisk of developing cancerLate-onset patientsRisk predictionClinical variablesHigh-risk individualsCox proportional hazards modelsProportional hazards modelGenetic risk factorsBaseline traitsClinical risk modelRisk scoreEarly-onset patientsHazards modelLate-onset groupEarly-onset groupBreast cancerHigh risk
2023
Risk Factors, Trends, and Outcomes Associated With Postpartum Sepsis Readmissions
Liu L, Wen T, Reddy U, Mourad M, Goffman D, Nathan L, Sheen J, D'Alton M, Friedman A. Risk Factors, Trends, and Outcomes Associated With Postpartum Sepsis Readmissions. Obstetrics And Gynecology 2023, 143: 346-354. PMID: 37944152, DOI: 10.1097/aog.0000000000005437.Peer-Reviewed Original ResearchPostpartum readmissionDelivery hospitalizationsSepsis readmissionsJoinpoint Regression ProgramAdverse outcomesSepsis diagnosisSevere morbidityAssociated diagnosisRisk factorsNational Cancer Institute's Joinpoint Regression ProgramAverage annual percent changeRetrospective cohort studyClinical risk factorsNationwide Readmissions DatabaseMedian ZIP code incomeAdjusted odds ratioChronic medical conditionsIntra-amniotic infectionAnnual percent changeZip code incomeLogistic regression modelsChronic hypertensionMaternal sepsisPregestational diabetesCohort studyDo Polygenic Risk Scores Add to Clinical Data in Predicting Pancreatic Cancer? A Scoping Review.
Wang L, Grimshaw A, Mezzacappa C, Rahimi Larki N, Yang Y, Justice A. Do Polygenic Risk Scores Add to Clinical Data in Predicting Pancreatic Cancer? A Scoping Review. Cancer Epidemiology Biomarkers & Prevention 2023, 32: 1490-1497. PMID: 37610426, PMCID: PMC10873036, DOI: 10.1158/1055-9965.epi-23-0468.Peer-Reviewed Original ResearchConceptsRoutine risk factorsPancreatic cancerRisk factorsPolygenic risk scoresClinical dataRisk scoreAddition of PRSClinical risk factorsRoutine clinical dataCancer risk predictionDatabase inceptionCancerClinical applicabilityRelevant exposuresGenetic riskRisk predictionCancer-specific polygenic risk scoresScoping ReviewRiskEuropean ancestryPopulation representativeScoresMost studiesAppropriate controlsFactorsResearching COVID to Enhance Recovery (RECOVER) adult study protocol: Rationale, objectives, and design
Horwitz L, Thaweethai T, Brosnahan S, Cicek M, Fitzgerald M, Goldman J, Hess R, Hodder S, Jacoby V, Jordan M, Krishnan J, Laiyemo A, Metz T, Nichols L, Patzer R, Sekar A, Singer N, Stiles L, Taylor B, Ahmed S, Algren H, Anglin K, Aponte-Soto L, Ashktorab H, Bassett I, Bedi B, Bhadelia N, Bime C, Bind M, Black L, Blomkalns A, Brim H, Castro M, Chan J, Charney A, Chen B, Chen L, Chen P, Chestek D, Chibnik L, Chow D, Chu H, Clifton R, Collins S, Costantine M, Cribbs S, Deeks S, Dickinson J, Donohue S, Durstenfeld M, Emery I, Erlandson K, Facelli J, Farah-Abraham R, Finn A, Fischer M, Flaherman V, Fleurimont J, Fonseca V, Gallagher E, Gander J, Gennaro M, Gibson K, Go M, Goodman S, Granger J, Greenway F, Hafner J, Han J, Harkins M, Hauser K, Heath J, Hernandez C, Ho O, Hoffman M, Hoover S, Horowitz C, Hsu H, Hsue P, Hughes B, Jagannathan P, James J, John J, Jolley S, Judd S, Juskowich J, Kanjilal D, Karlson E, Katz S, Kelly J, Kelly S, Kim A, Kirwan J, Knox K, Kumar A, Lamendola-Essel M, Lanca M, Lee-Lannotti J, Lefebvre R, Levy B, Lin J, Logarbo B, Logue J, Longo M, Luciano C, Lutrick K, Malakooti S, Mallett G, Maranga G, Marathe J, Marconi V, Marshall G, Martin C, Martin J, May H, McComsey G, McDonald D, Mendez-Figueroa H, Miele L, Mittleman M, Mohandas S, Mouchati C, Mullington J, Nadkarni G, Nahin E, Neuman R, Newman L, Nguyen A, Nikolich J, Ofotokun I, Ogbogu P, Palatnik A, Palomares K, Parimon T, Parry S, Parthasarathy S, Patterson T, Pearman A, Peluso M, Pemu P, Pettker C, Plunkett B, Pogreba-Brown K, Poppas A, Porterfield J, Quigley J, Quinn D, Raissy H, Rebello C, Reddy U, Reece R, Reeder H, Rischard F, Rosas J, Rosen C, Rouphael N, Rouse D, Ruff A, Saint Jean C, Sandoval G, Santana J, Schlater S, Sciurba F, Selvaggi C, Seshadri S, Sesso H, Shah D, Shemesh E, Sherif Z, Shinnick D, Simhan H, Singh U, Sowles A, Subbian V, Sun J, Suthar M, Teunis L, Thorp J, Ticotsky A, Tita A, Tragus R, Tuttle K, Urdaneta A, Utz P, VanWagoner T, Vasey A, Vernon S, Vidal C, Walker T, Ward H, Warren D, Weeks R, Weiner S, Weyer J, Wheeler J, Whiteheart S, Wiley Z, Williams N, Wisnivesky J, Wood J, Yee L, Young N, Zisis S, Foulkes A. Researching COVID to Enhance Recovery (RECOVER) adult study protocol: Rationale, objectives, and design. PLOS ONE 2023, 18: e0286297. PMID: 37352211, PMCID: PMC10289397, DOI: 10.1371/journal.pone.0286297.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 infectionRisk factorsClinical risk factorsPost-acute sequelaePrimary study outcomeProportional hazards regressionCommunity-based outreachMulti-site observational studyPASC symptomsQuarterly questionnairesRetrospective cohortVaccination statusOrgan dysfunctionAcute phaseLong COVIDHazards regressionEligible participantsTreatment optionsPrior infectionStudy protocolClinical trialsNew symptomsLongitudinal cohortLaboratory examinationsObservational studyQuantitative cardiovascular magnetic resonance findings and clinical risk factors predict cardiovascular outcomes in breast cancer patients
Kwan J, Arbune A, Henry M, Hu R, Wei W, Nguyen V, Lee S, Lopez-Mattei J, Guha A, Huber S, Bader A, Meadows J, Sinusas A, Mojibian H, Peters D, Lustberg M, Hull S, Baldassarre L. Quantitative cardiovascular magnetic resonance findings and clinical risk factors predict cardiovascular outcomes in breast cancer patients. PLOS ONE 2023, 18: e0286364. PMID: 37252927, PMCID: PMC10228774, DOI: 10.1371/journal.pone.0286364.Peer-Reviewed Original ResearchConceptsBreast cancer patientsSystolic heart failureCardiovascular outcomesCancer patientsHeart failureValvular diseaseStrain abnormalitiesLeft ventricular ejection fraction reductionCancer treatment-related cardiotoxicityCardiovascular magnetic resonance findingsVentricular ejection fraction reductionYale-New Haven HospitalEjection fraction reductionTreatment-related cardiotoxicityAdverse cardiovascular outcomesClinical risk factorsNormal LV functionGlobal longitudinal strainIschemic heart diseaseMagnetic resonance findingsRisk regression modelsNew Haven HospitalSubclinical cardiotoxicityDiastolic dysfunctionStatin use0395 Effects of Insomnia and Rest-Activity on Hospitalizations and Emergency Department Visits in People with Stable Heart Failure
Jeon S, Conley S, Hollenbeak C, O’Connell M, Yaggi H, Jacoby D, Wang Z, Tocchi C, Redeker N. 0395 Effects of Insomnia and Rest-Activity on Hospitalizations and Emergency Department Visits in People with Stable Heart Failure. Sleep 2023, 46: a175-a175. DOI: 10.1093/sleep/zsad077.0395.Peer-Reviewed Original ResearchRest-activity rhythmED visitsHeart failureRisk factorsInsomnia Severity IndexHazard ratioEffects of insomniaInsomnia severityNew York Heart Association classDate of hospitalizationClinical risk factorsStable heart failureEmergency department visitsRandomized clinical trialsSelf-management educationAvailable medical recordsProportional hazards modelCognitive behavioral therapyGreater comorbidityHF patientsHigher insomnia severityCardiac eventsEarly hospitalizationFirst hospitalizationFrequent hospitalizationsA Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage
Myserlis E, Georgakis M, Demel S, Sekar P, Chung J, Malik R, Hyacinth H, Comeau M, Falcone G, Langefeld C, Rosand J, Woo D, Anderson C. A Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage. Stroke 2023, 54: 973-982. PMID: 36799223, PMCID: PMC10050100, DOI: 10.1161/strokeaha.122.041701.Peer-Reviewed Original ResearchConceptsClinical risk factorsIncident intracerebral hemorrhageIntracerebral hemorrhageHigh-risk populationRisk factorsGenomic risk scoresRisk scoreHigher oddsHigh riskRisk factor-adjusted modelsStandard clinical risk factorsVascular risk factorsLobar intracerebral hemorrhageLow-risk populationNonlobar intracerebral hemorrhageUse of anticoagulantsPopulation-based UK Biobank cohortUK Biobank cohortEuropean ancestryAntithrombotic treatmentClinical predictorsSD incrementMedication usersLifetime riskMetaGRS
2022
Radiation therapy prior to CAR T-cell therapy in lymphoma: impact on patient outcomes
Figura N, Sim A, Jain M, Chavez J, Robinson T. Radiation therapy prior to CAR T-cell therapy in lymphoma: impact on patient outcomes. Expert Review Of Hematology 2022, 15: 1023-1030. PMID: 36369950, DOI: 10.1080/17474086.2022.2147919.Peer-Reviewed Original ResearchConceptsCAR T-cell therapyT-cell therapySalvage radiotherapyPatient outcomesAnti-CD19 chimeric antigen receptor (CAR) T-cell therapyChimeric antigen receptor T-cell therapyLarge B-cell lymphomaCurrent retrospective dataHigh tumor burdenClinical risk factorsAblative radiation dosesHypothesis-driven clinical trialsB-cell lymphomaMost patientsR DLBCLLocal recurrenceTumor burdenClinical evidenceRisk factorsTreatment paradigmClinical trialsTreatment outcomesRadiation therapyElevated riskPatientsCopy number variants and fetal growth in stillbirths
Dalton S, Workalemahu T, Allshouse A, Page J, Reddy U, Saade G, Pinar H, Goldenberg R, Dudley D, Silver R. Copy number variants and fetal growth in stillbirths. American Journal Of Obstetrics And Gynecology 2022, 228: 579.e1-579.e11. PMID: 36356697, PMCID: PMC10149588, DOI: 10.1016/j.ajog.2022.11.1274.Peer-Reviewed Original ResearchConceptsAbnormal copy number variantsFetal growth abnormalitiesGestational ageOdds ratioStillbirth Collaborative Research NetworkGenetic abnormalitiesChromosomal microarrayGestational age outcomesGestational age infantsGrowth abnormalitiesClinical risk factorsCohort study designAdjusted odds ratioCopy number variantsUnknown clinical significancePathogenic copy number variantsPlacental insufficiencyAge infantsNumber variantsFetal growthMaternal ageRisk factorsClinical significanceHigh incidenceStillbirthAbstract 12593: Type 2 Diabetes Mellitus Polygenic Score Predicts New Onset Diabetes in Patients With Established Atherosclerotic Cardiovascular Disease: A FOURIER Sub-Study
Moura F, Kamanu F, Wiviott S, Giugliano R, Florez J, Roselli C, Keech A, Lubitz S, Ellinor P, Ruff C, Marston N, Sabatine M. Abstract 12593: Type 2 Diabetes Mellitus Polygenic Score Predicts New Onset Diabetes in Patients With Established Atherosclerotic Cardiovascular Disease: A FOURIER Sub-Study. Circulation 2022, 146: a12593-a12593. DOI: 10.1161/circ.146.suppl_1.12593.Peer-Reviewed Original ResearchNew-onset T2DPolygenic scoresGenetic riskClinical risk factorsAtherosclerotic cardiovascular diseaseGenome-wide significant single nucleotide polymorphismsGenetic risk categoriesAmerican Diabetes Association definitionRisk factorsCardiovascular diseaseSignificant single nucleotide polymorphismsPredicting new-onset diabetesBMI levelsNew-onset diabetes casesAssociation definitionType 2 diabetesNormal weightBaseline ageDiabetes casesNew-onset diabetesPre-diabetesSub-studySingle nucleotide polymorphismsBMIT2D
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