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 ResearchConceptsSevere aortic stenosis
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
2017
Systolic Blood Pressure Response in SPRINT (Systolic Blood Pressure Intervention Trial) and ACCORD (Action to Control Cardiovascular Risk in Diabetes): A Possible Explanation for Discordant Trial Results
Huang C, Dhruva SS, Coppi AC, Warner F, Li S, Lin H, Nasir K, Krumholz HM. Systolic Blood Pressure Response in SPRINT (Systolic Blood Pressure Intervention Trial) and ACCORD (Action to Control Cardiovascular Risk in Diabetes): A Possible Explanation for Discordant Trial Results. Journal Of The American Heart Association 2017, 6: e007509. PMID: 29133522, PMCID: PMC5721802, DOI: 10.1161/jaha.117.007509.Peer-Reviewed Original ResearchConceptsSystolic blood pressure responseBlood pressure responseTreatment groupsCause deathVisit variabilityDiscordant trialsBlood pressure trialStandard treatment groupPressure responseACCORD participantsPressure trialSBP responseHeart failureMean SBPPrimary outcomeSBPDiscordant resultsMean differenceSimilar interventionsTrial resultsTrialsSimilar mean differencesTreatment effectsSignificant differencesStrokeHeterogeneity in Early Responses in ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial)
Dhruva SS, Huang C, Spatz ES, Coppi AC, Warner F, Li SX, Lin H, Xu X, Furberg CD, Davis BR, Pressel SL, Coifman RR, Krumholz HM. Heterogeneity in Early Responses in ALLHAT (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial). Hypertension 2017, 70: 94-102. PMID: 28559399, DOI: 10.1161/hypertensionaha.117.09221.Peer-Reviewed Original ResearchConceptsAntihypertensive therapySystolic blood pressure responseAdverse cardiovascular eventsFavorable initial responseBlood pressure responseHigher hazard ratioCardiovascular eventsCardiovascular outcomesHazard ratioMultivariable adjustmentHeart failureAverage SBPRandomized trialsOdds ratioCardiovascular diseaseSBPStudy participantsRespondersMonthsPressure responseImmediate respondersALLHATEarly responseInitial responseSuperior discriminationDiscovery of temporal and disease association patterns in condition-specific hospital utilization rates
Haimovich JS, Venkatesh AK, Shojaee A, Coppi A, Warner F, Li SX, Krumholz HM. Discovery of temporal and disease association patterns in condition-specific hospital utilization rates. PLOS ONE 2017, 12: e0172049. PMID: 28355219, PMCID: PMC5371293, DOI: 10.1371/journal.pone.0172049.Peer-Reviewed Original ResearchPrediction of Adverse Events in Patients Undergoing Major Cardiovascular Procedures
Mortazavi B, Desai N, Zhang J, Coppi A, Warner F, Krumholz H, Negahban S. Prediction of Adverse Events in Patients Undergoing Major Cardiovascular Procedures. IEEE Journal Of Biomedical And Health Informatics 2017, 21: 1719-1729. PMID: 28287993, DOI: 10.1109/jbhi.2017.2675340.Peer-Reviewed Original ResearchConceptsMajor cardiovascular proceduresElectronic health recordsRespiratory failureAdverse eventsCardiovascular proceduresYale-New Haven HospitalPostoperative respiratory failurePatient cohortHospital costsPatient outcomesSpecific patientPatientsHealth recordsCohort-specific modelsCharacteristic curveInfectionFailureHospitalCohortClinicians