2024
Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing
Nargesi A, Adejumo P, Dhingra L, Rosand B, Hengartner A, Coppi A, Benigeri S, Sen S, Ahmad T, Nadkarni G, Lin Z, Ahmad F, Krumholz H, Khera R. Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing. JACC Heart Failure 2024 PMID: 39453355, DOI: 10.1016/j.jchf.2024.08.012.Peer-Reviewed Original ResearchReduced ejection fractionEjection fractionHeart failureLeft ventricular ejection fractionVentricular ejection fractionYale-New Haven HospitalIdentification of patientsCommunity hospitalIdentification of heart failureLanguage modelNorthwestern MedicineMeasure care qualityQuality of careNew Haven HospitalDeep learning-based natural language processingHFrEFGuideline-directed careDeep learning language modelsMIMIC-IIIDetect HFrEFNatural language processingReclassification improvementHospital dischargePatientsCare qualityArtificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images.
Oikonomou E, Sangha V, Dhingra L, Aminorroaya A, Coppi A, Krumholz H, Baldassarre L, Khera R. Artificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images. Circulation Cardiovascular Quality And Outcomes 2024 PMID: 39221857, DOI: 10.1161/circoutcomes.124.011504.Peer-Reviewed Original ResearchCancer therapeutics-related cardiac dysfunctionGlobal longitudinal strainLeft ventricular systolic dysfunctionCardiac dysfunctionBreast cancerNon-Hodgkin lymphoma therapyNon-Hodgkin's lymphomaVentricular systolic dysfunctionAssociated with worse global longitudinal strainRisk stratification strategiesHigh-risk groupMonths post-treatmentPost hoc analysisElectrocardiographic (ECGTrastuzumab exposureLymphoma therapySystolic dysfunctionAI-ECGBefore treatmentRisk biomarkersLongitudinal strainLow riskStratification strategiesHigher incidencePositive screenA Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression
Oikonomou E, Holste G, Yuan N, Coppi A, McNamara R, Haynes N, Vora A, Velazquez E, Li F, Menon V, Kapadia S, Gill T, Nadkarni G, Krumholz H, Wang Z, Ouyang D, Khera R. A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression. JAMA Cardiology 2024, 9: 534-544. PMID: 38581644, PMCID: PMC10999005, DOI: 10.1001/jamacardio.2024.0595.Peer-Reviewed Original ResearchCardiac magnetic resonanceAortic valve replacementCardiac magnetic resonance imagingAV VmaxSevere ASAortic stenosisCohort studyPeak aortic valve velocityCohort study of patientsAortic valve velocityCohort of patientsTraditional cardiovascular risk factorsAssociated with faster progressionStudy of patientsCedars-Sinai Medical CenterAssociated with AS developmentCardiovascular risk factorsCardiovascular imaging modalitiesIndependent of ageModerate ASEjection fractionEchocardiographic studiesValve replacementRisk stratificationCardiac structureThe PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID
Krumholz H, Sawano M, Bhattacharjee B, Caraballo C, Khera R, Li S, Herrin J, Coppi A, Holub J, Henriquez Y, Johnson M, Goddard T, Rocco E, Hummel A, Al Mouslmani M, Putrino D, Carr K, Carvajal-Gonzalez S, Charnas L, De Jesus M, Ziegler F, Iwasaki A. The PAX LC Trial: A Decentralized, Phase 2, Randomized, Double-blind Study of Nirmatrelvir/Ritonavir Compared with Placebo/Ritonavir for Long COVID. The American Journal Of Medicine 2024 PMID: 38735354, DOI: 10.1016/j.amjmed.2024.04.030.Peer-Reviewed Original ResearchLC trialPROMIS-29Participants' homesTargeting viral persistencePlacebo-controlled trialDouble-blind studyElectronic health recordsCore Outcome MeasuresLong COVIDEQ-5D-5LRepeated measures analysisEvidence-based treatmentsPhase 2Double-blindParticipant-centred approachStudy drugPrimary endpointSecondary endpointsCommunity-dwellingHealth recordsHealthcare utilizationContiguous US statesViral persistencePatient groupDrug treatment
2023
Computational phenotypes for patients with opioid-related disorders presenting to the emergency department
Taylor R, Gilson A, Schulz W, Lopez K, Young P, Pandya S, Coppi A, Chartash D, Fiellin D, D’Onofrio G. Computational phenotypes for patients with opioid-related disorders presenting to the emergency department. PLOS ONE 2023, 18: e0291572. PMID: 37713393, PMCID: PMC10503758, DOI: 10.1371/journal.pone.0291572.Peer-Reviewed Original ResearchConceptsSubstance use disordersUse disordersED visitsPatient presentationCarlson comorbidity indexOpioid-related diagnosesOpioid-related disordersOne-year survivalRate of medicationOpioid use disorderElectronic health record dataPatient-oriented outcomesYears of ageHealth record dataChronic substance use disordersED returnComorbidity indexAcute overdoseMedical managementClinical entityRetrospective studyEmergency departmentChronic conditionsInclusion criteriaUnique cohortAn AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model
Charkoftaki G, Aalizadeh R, Santos-Neto A, Tan W, Davidson E, Nikolopoulou V, Wang Y, Thompson B, Furnary T, Chen Y, Wunder E, Coppi A, Schulz W, Iwasaki A, Pierce R, Cruz C, Desir G, Kaminski N, Farhadian S, Veselkov K, Datta R, Campbell M, Thomaidis N, Ko A, Thompson D, Vasiliou V. An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model. Human Genomics 2023, 17: 80. PMID: 37641126, PMCID: PMC10463861, DOI: 10.1186/s40246-023-00521-4.Peer-Reviewed Original ResearchConceptsCOVID-19 patientsDisease severityViral outbreaksFuture viral outbreaksLength of hospitalizationIntensive care unitWorse disease prognosisLife-threatening illnessEffective medical interventionsCOVID-19Clinical decision treeGlucuronic acid metabolitesNew potential biomarkersHospitalization lengthCare unitComorbidity dataSerotonin levelsDisease progressionHealthy controlsPatient outcomesDisease prognosisPatient transferPatientsHealthcare resourcesPotential biomarkersSevere 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 ResearchDetection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices
Khunte A, Sangha V, Oikonomou E, Dhingra L, Aminorroaya A, Mortazavi B, Coppi A, Brandt C, Krumholz H, Khera R. Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices. Npj Digital Medicine 2023, 6: 124. PMID: 37433874, PMCID: PMC10336107, DOI: 10.1038/s41746-023-00869-w.Peer-Reviewed Original ResearchArtificial intelligenceRandom Gaussian noiseNoisy electrocardiogramGaussian noiseElectrocardiogram (ECGWearable devicesSingle-lead electrocardiogramPortable devicesSNRWearableNoiseDevice noiseRepositoryAI-based screeningIntelligenceDetectionDevicesNoise sourcesVentricular systolic dysfunctionModelElectrocardiogramSingle-lead electrocardiographyTraining
2022
Association between primary or booster COVID-19 mRNA vaccination and Omicron lineage BA.1 SARS-CoV-2 infection in people with a prior SARS-CoV-2 infection: A test-negative case–control analysis
Lind M, Robertson A, Silva J, Warner F, Coppi A, Price N, Duckwall C, Sosensky P, Di Giuseppe E, Borg R, Fofana M, Ranzani O, Dean N, Andrews J, Croda J, Iwasaki A, Cummings D, Ko A, Hitchings M, Schulz W. Association between primary or booster COVID-19 mRNA vaccination and Omicron lineage BA.1 SARS-CoV-2 infection in people with a prior SARS-CoV-2 infection: A test-negative case–control analysis. PLOS Medicine 2022, 19: e1004136. PMID: 36454733, PMCID: PMC9714718, DOI: 10.1371/journal.pmed.1004136.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 infectionBooster vaccinationPrior infectionOmicron infectionPrimary vaccinationMRNA vaccinationOdds ratioAcute respiratory syndrome coronavirus 2 infectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionPrior SARS-CoV-2 infectionTest-negative case-control analysisYale New Haven Health SystemTest-negative case-control studyCOVID-19 mRNA vaccinationSyndrome coronavirus 2 infectionOmicron variant infectionPrior infection statusCoronavirus 2 infectionCase-control studyCase-control analysisOdds of infectionRisk of infectionRace/ethnicityBooster dosesDate of testUse of Whole-Genome Sequencing to Estimate the Contribution of Immune Evasion and Waning Immunity on Decreasing COVID-19 Vaccine Effectiveness
Lind M, Copin R, McCarthy S, Coppi A, Warner F, Ferguson D, Duckwall C, Borg R, Muenker M, Overton J, Hamon S, Zhou A, Cummings D, Ko A, Hamilton J, Schulz W, Hitchings M. Use of Whole-Genome Sequencing to Estimate the Contribution of Immune Evasion and Waning Immunity on Decreasing COVID-19 Vaccine Effectiveness. The Journal Of Infectious Diseases 2022, 227: 663-674. PMID: 36408616, DOI: 10.1093/infdis/jiac453.Peer-Reviewed Original ResearchConceptsVaccine effectivenessImmune evasionDelta infectionVE estimatesSecond doseTest-negative case-control studySevere acute respiratory syndrome coronavirus 2Acute respiratory syndrome coronavirus 2Whole-genome sequencingCOVID-19 vaccine effectivenessRespiratory syndrome coronavirus 2Syndrome coronavirus 2Case-control studyCoronavirus 2Calendar periodDelta variantInfectionDoseEvasionDaysLow effectivenessImmunityVariantsRapid emergence of SARS-CoV-2 Omicron variant is associated with an infection advantage over Delta in vaccinated persons
Chaguza C, Coppi A, Earnest R, Ferguson D, Kerantzas N, Warner F, Young HP, Breban MI, Billig K, Koch RT, Pham K, Kalinich CC, Ott IM, Fauver JR, Hahn AM, Tikhonova IR, Castaldi C, De Kumar B, Pettker CM, Warren JL, Weinberger DM, Landry ML, Peaper DR, Schulz W, Vogels CBF, Grubaugh ND. Rapid emergence of SARS-CoV-2 Omicron variant is associated with an infection advantage over Delta in vaccinated persons. Med 2022, 3: 325-334.e4. PMID: 35399324, PMCID: PMC8983481, DOI: 10.1016/j.medj.2022.03.010.Peer-Reviewed Original ResearchConceptsSpike gene target failureSARS-CoV-2 Omicron variantPositivity rateOmicron variantOmicron infectionVaccine dosesVaccine-induced immunityNumber of dosesTest positivity rateOdds of infectionSARS-CoV-2Significant reductionDominant Delta variantUnvaccinated personsVaccination statusHigher oddsDelta variantInfectionVaccine manufacturersDisease controlVirus copiesDosesPCR testOddsTarget failure
2021
Myopericarditis in young adults presenting to the emergency department after receiving a second COVID‐19 mRNA vaccine
Fleming‐Nouri A, Haimovich AD, Yang D, Schulz WL, Coppi A, Taylor RA. Myopericarditis in young adults presenting to the emergency department after receiving a second COVID‐19 mRNA vaccine. Academic Emergency Medicine 2021, 28: 802-805. PMID: 34310793, PMCID: PMC8441914, DOI: 10.1111/acem.14307.Peer-Reviewed Original ResearchToward Dynamic Risk Prediction of Outcomes After Coronary Artery Bypass Graft
Mori M, Durant TJS, Huang C, Mortazavi BJ, Coppi A, Jean RA, Geirsson A, Schulz WL, Krumholz HM. Toward Dynamic Risk Prediction of Outcomes After Coronary Artery Bypass Graft. Circulation Cardiovascular Quality And Outcomes 2021, 14: e007363. PMID: 34078100, PMCID: PMC8635167, DOI: 10.1161/circoutcomes.120.007363.Peer-Reviewed Original ResearchConceptsCoronary artery bypass graftArtery bypass graftIntraoperative variablesBypass graftLogistic regression modelsOperative mortalityC-statisticCoronary artery bypass graft casesThoracic Surgeons Adult Cardiac Surgery DatabaseAdult Cardiac Surgery DatabaseMean patient ageGood c-statisticCardiac Surgery DatabaseBrier scoreRisk restratificationDynamic risk predictionIntraoperative deathsPostoperative complicationsPostoperative eventsAdverse eventsPatient agePreoperative variablesRegression modelsGraft casesSurgery DatabaseDiverse functional autoantibodies in patients with COVID-19
Wang EY, Mao T, Klein J, Dai Y, Huck JD, Jaycox JR, Liu F, Zhou T, Israelow B, Wong P, Coppi A, Lucas C, Silva J, Oh JE, Song E, Perotti ES, Zheng NS, Fischer S, Campbell M, Fournier JB, Wyllie AL, Vogels CBF, Ott IM, Kalinich CC, Petrone ME, Watkins AE, Dela Cruz C, Farhadian S, Schulz W, Ma S, Grubaugh N, Ko A, Iwasaki A, Ring A. Diverse functional autoantibodies in patients with COVID-19. Nature 2021, 595: 283-288. PMID: 34010947, DOI: 10.1038/s41586-021-03631-y.Peer-Reviewed Original ResearchConceptsPeripheral immune cell compositionSARS-CoV-2 infectionCOVID-19Effects of autoantibodiesTissue-associated antigensSpecific clinical characteristicsInnate immune activationImmune cell compositionCOVID-19 exhibitCOVID-19 manifestsAnalysis of autoantibodiesSARS-CoV-2Functional autoantibodiesMouse surrogateClinical characteristicsVirological controlClinical outcomesImmune activationMild diseaseAsymptomatic infectionAutoantibody reactivityDisease progressionHealthcare workersHigh prevalenceAutoantibodiesTemporal relationship of computed and structured diagnoses in electronic health record data
Schulz WL, Young HP, Coppi A, Mortazavi BJ, Lin Z, Jean RA, Krumholz HM. Temporal relationship of computed and structured diagnoses in electronic health record data. BMC Medical Informatics And Decision Making 2021, 21: 61. PMID: 33596898, PMCID: PMC7890604, DOI: 10.1186/s12911-021-01416-x.Peer-Reviewed Original ResearchConceptsElectronic health recordsStructured diagnosisOutpatient blood pressureElectronic health record dataAcademic health systemLow-density lipoproteinHealth record dataBlood pressureStructured data elementsAdministrative claimsHypertensionClinical informationHyperlipidemiaClinical phenotypeEquivalent diagnosisVital signsHealth systemDiagnosisProblem listAdditional studiesHealth recordsRecord dataTimely accessEHR dataPatients
2020
Evaluation of a Risk Stratification Model Using Preoperative and Intraoperative Data for Major Morbidity or Mortality After Cardiac Surgical Treatment
Durant TJS, Jean RA, Huang C, Coppi A, Schulz WL, Geirsson A, Krumholz HM. Evaluation of a Risk Stratification Model Using Preoperative and Intraoperative Data for Major Morbidity or Mortality After Cardiac Surgical Treatment. JAMA Network Open 2020, 3: e2028361. PMID: 33284333, DOI: 10.1001/jamanetworkopen.2020.28361.Peer-Reviewed Original Research
2019
Development and Testing of Improved Models to Predict Payment Using Centers for Medicare & Medicaid Services Claims Data
Krumholz HM, Warner F, Coppi A, Triche EW, Li SX, Mahajan S, Li Y, Bernheim SM, Grady J, Dorsey K, Desai NR, Lin Z, Normand ST. Development and Testing of Improved Models to Predict Payment Using Centers for Medicare & Medicaid Services Claims Data. JAMA Network Open 2019, 2: e198406. PMID: 31411709, PMCID: PMC6694388, DOI: 10.1001/jamanetworkopen.2019.8406.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionHeart failurePopulation-based programsPOA codesSingle diagnostic codeDiagnostic codesComparative effectiveness research studyPublic reportingIndex admission diagnosisDays of hospitalizationClinical Modification codesService claims dataAcute care hospitalsMultiple care settingsPatient-level modelsAdmission diagnosisTotal hospitalizationsCare hospitalPrevious diagnosisNinth RevisionMyocardial infarctionCandidate variablesCare settingsClaims dataMAIN OUTCOMEComparative Effectiveness of New Approaches to Improve Mortality Risk Models From Medicare Claims Data
Krumholz HM, Coppi AC, Warner F, Triche EW, Li SX, Mahajan S, Li Y, Bernheim SM, Grady J, Dorsey K, Lin Z, Normand ST. Comparative Effectiveness of New Approaches to Improve Mortality Risk Models From Medicare Claims Data. JAMA Network Open 2019, 2: e197314. PMID: 31314120, PMCID: PMC6647547, DOI: 10.1001/jamanetworkopen.2019.7314.Peer-Reviewed Original ResearchConceptsAcute myocardial infarctionICD-9-CM codesMortality risk modelHeart failureHospital admissionC-statisticMAIN OUTCOMEMortality rateRisk-standardized mortality ratesHospital risk-standardized mortality ratesIndex admission diagnosisPatients 65 yearsDays of hospitalizationComparative effectiveness studiesClaims-based dataHospital-level performance measuresMedicare claims dataPatient-level modelsCMS modelRisk-adjustment modelsRisk modelHospital performance measuresAdmission diagnosisNinth RevisionMyocardial infarctionHealth Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform
McPadden J, Durant TJ, Bunch DR, Coppi A, Price N, Rodgerson K, Torre CJ, Byron W, Hsiao AL, Krumholz HM, Schulz WL. Health Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform. Journal Of Medical Internet Research 2019, 21: e13043. PMID: 30964441, PMCID: PMC6477571, DOI: 10.2196/13043.Peer-Reviewed Original ResearchConceptsData science platformOpen source technologiesHealth care dataSource technologiesModern big data platformScience platformData management approachTraditional computer systemsBig data workloadsBig data platformBig data sourcesReal-time datasetBiomedical research dataHealth care applicationsData-driven researchPatient monitoringScalable analyticsApache StormData lakeData workloadsAnalytics platformData acquisition workflowContinuous patient monitoringUse casesData platform
2018
Quantifying the utilization of medical devices necessary to detect postmarket safety differences: A case study of implantable cardioverter defibrillators
Bates J, Parzynski CS, Dhruva SS, Coppi A, Kuntz R, Li S, Marinac‐Dabic D, Masoudi FA, Shaw RE, Warner F, Krumholz HM, Ross JS. Quantifying the utilization of medical devices necessary to detect postmarket safety differences: A case study of implantable cardioverter defibrillators. Pharmacoepidemiology And Drug Safety 2018, 27: 848-856. PMID: 29896873, PMCID: PMC6436550, DOI: 10.1002/pds.4565.Peer-Reviewed Original ResearchConceptsAdverse event ratesSafety differencesEvent ratesMedical device utilizationICD utilizationRate ratioNational Cardiovascular Data RegistryICD modelsImplantable cardioverter defibrillatorEvent rate ratioMost patientsCardioverter defibrillatorProportion of individualsAmerican CollegeData registryRoutine surveillanceSample size estimatesAverage event rateDevice utilizationSignificance levelDifferencesPatientsRegistryDefibrillatorICD