Featured Publications
Clinical characteristics and outcomes for 7,995 patients with SARS-CoV-2 infection
McPadden J, Warner F, Young HP, Hurley NC, Pulk RA, Singh A, Durant TJS, Gong G, Desai N, Haimovich A, Taylor RA, Gunel M, Dela Cruz CS, Farhadian SF, Siner J, Villanueva M, Churchwell K, Hsiao A, Torre CJ, Velazquez EJ, Herbst RS, Iwasaki A, Ko AI, Mortazavi BJ, Krumholz HM, Schulz WL. Clinical characteristics and outcomes for 7,995 patients with SARS-CoV-2 infection. PLOS ONE 2021, 16: e0243291. PMID: 33788846, PMCID: PMC8011821, DOI: 10.1371/journal.pone.0243291.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 infectionYale New Haven HealthSARS-CoV-2Hospital mortalityRisk of admissionMale sexRisk factorsSARS-CoV-2 testingInvasive mechanical ventilationSevere acute respiratory syndrome virusBurden of diseaseRT-PCR testingAcademic health systemDiverse patient populationsRespiratory syndrome virusEthnic groupsAdult patientsClinical characteristicsDischarge dispositionRespiratory supportPrimary outcomeTreatment guidelinesMechanical ventilationRetrospective studyPatient populationAssociation 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 test
2024
SOFA score performs worse than age for predicting mortality in patients with COVID-19
Sherak R, Sajjadi H, Khimani N, Tolchin B, Jubanyik K, Taylor R, Schulz W, Mortazavi B, Haimovich A. SOFA score performs worse than age for predicting mortality in patients with COVID-19. PLOS ONE 2024, 19: e0301013. PMID: 38758942, PMCID: PMC11101117, DOI: 10.1371/journal.pone.0301013.Peer-Reviewed Original ResearchConceptsCrisis standards of careIn-hospital mortalityIntensive care unitAcademic health systemSequential Organ Failure Assessment scoreCohort of intensive care unitSequential Organ Failure AssessmentStandard of careLogistic regression modelsMortality predictionPredicting in-hospital mortalityHealth systemUnivariate logistic regression modelCrisis standardsDisease morbidityCOVID-19Hypertension Trends and Disparities Over 12 Years in a Large Health System: Leveraging the Electronic Health Records
Brush J, Lu Y, Liu Y, Asher J, Li S, Sawano M, Young P, Schulz W, Anderson M, Burrows J, Krumholz H. Hypertension Trends and Disparities Over 12 Years in a Large Health System: Leveraging the Electronic Health Records. Journal Of The American Heart Association 2024, 13: e033253. PMID: 38686864, PMCID: PMC11179912, DOI: 10.1161/jaha.123.033253.Peer-Reviewed Original ResearchConceptsElectronic health recordsRegional health systemImprove hypertension careHealth systemHealth recordsHypertension careDiastolic blood pressureAge-adjusted prevalence ratesNon-Hispanic Black patientsPrevalence ratesLarger health systemCross-sectional analysisTransformation of medical dataLeveraging real-world dataHigh prevalence rateHypertension trendsHypertension prevalenceBlood pressureBlood pressure measurementsHypertension diagnosisPrimary outcomeNational trendsProportion of patientsAntihypertensive medicationsBlack patients
2022
Change in covid-19 risk over time following vaccination with CoronaVac: test negative case-control study
Hitchings MDT, Ranzani OT, Lind ML, Dorion M, D'Agostini TL, de Paula RC, de Paula OFP, de Moura Villela EF, Scaramuzzini Torres MS, de Oliveira SB, Schulz W, Almiron M, Said R, de Oliveira RD, Vieira da Silva P, de Araújo WN, Gorinchteyn JC, Dean NE, Andrews JR, Cummings DAT, Ko AI, Croda J. Change in covid-19 risk over time following vaccination with CoronaVac: test negative case-control study. The BMJ 2022, 377: e070102. PMID: 35697361, PMCID: PMC9189440, DOI: 10.1136/bmj-2022-070102.Peer-Reviewed Original ResearchConceptsSymptomatic COVID-19Negative case-control studyCase-control studyHospital admissionOdds ratioCOVID-19Series completionCovid-19 related hospital admissionReverse transcription polymerase chain reaction testingTranscription polymerase chain reaction testingSevere COVID-19 outcomesSARS-CoV-2 infectionPolymerase chain reaction testingInactivated whole virus vaccineDoses of CoronaVacAcute respiratory illnessTest-negative controlsWhole virus vaccineRelated hospital admissionsHealthcare worker statusConditional logistic regressionCOVID-19 outcomesCOVID-19 symptomsMunicipality of residenceSARS-CoV-2
2021
Prevalence of Dyslipidemia and Availability of Lipid-Lowering Medications Among Primary Health Care Settings in China
Lu Y, Zhang H, Lu J, Ding Q, Li X, Wang X, Sun D, Tan L, Mu L, Liu J, Feng F, Yang H, Zhao H, Schulz WL, Krumholz HM, Pan X, Li J, Huang C, Dong Z, Jiang B, Guo Z, Zhang Y, Sun J, Liu Y, Ren Z, Meng Y, Wang Z, Xi Y, Xing L, Tian Y, Liu J, Fu Y, Liu T, Sun W, Yan S, Jin L, Zheng Y, Wang J, Yan J, Xu X, Chen Y, Xing X, Zhang L, Zhong W, Fang X, Zhu L, Xu Y, Guo X, Xu C, Zhou G, Fan L, Qi M, Zhu S, Qi J, Li J, Yin L, Liu Q, Geng Q, Feng Y, Wang J, Wen H, Han X, Liu P, Ding X, Xu J, Deng Y, He J, Liu G, Jiang C, Zha S, Yang C, Bai G, Yu Y, Tashi Z, Qiu L, Hu Z, He H, Zhang J, Zhou M, Li X, Zhao J, Ma S, Ma Y, Huang Y, Zhang Y, Li F, Shen J. Prevalence of Dyslipidemia and Availability of Lipid-Lowering Medications Among Primary Health Care Settings in China. JAMA Network Open 2021, 4: e2127573. PMID: 34586366, PMCID: PMC8482054, DOI: 10.1001/jamanetworkopen.2021.27573.Peer-Reviewed Original ResearchConceptsAtherosclerotic cardiovascular diseaseLipid-lowering medicationsPrimary care institutionsPrevalence of dyslipidemiaControl of dyslipidemiaLipoprotein cholesterolCare institutionsControl rateFemale sexCardiovascular diseaseMAIN OUTCOMEHigh riskNonstatin lipid-lowering drugsHigh-density lipoprotein cholesterolLow-density lipoprotein cholesterolPrimary health care settingsMajor public health problemLipid lowering medicationsMillion Persons ProjectOverall control rateLDL-C levelsLipid-lowering drugsCross-sectional studyPublic health problemHealth care settingsToward 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 Database
2020
Longitudinal analyses reveal immunological misfiring in severe COVID-19
Lucas C, Wong P, Klein J, Castro TBR, Silva J, Sundaram M, Ellingson MK, Mao T, Oh JE, Israelow B, Takahashi T, Tokuyama M, Lu P, Venkataraman A, Park A, Mohanty S, Wang H, Wyllie AL, Vogels CBF, Earnest R, Lapidus S, Ott IM, Moore AJ, Muenker MC, Fournier JB, Campbell M, Odio CD, Casanovas-Massana A, Herbst R, Shaw A, Medzhitov R, Schulz W, Grubaugh N, Dela Cruz C, Farhadian S, Ko A, Omer S, Iwasaki A. Longitudinal analyses reveal immunological misfiring in severe COVID-19. Nature 2020, 584: 463-469. PMID: 32717743, PMCID: PMC7477538, DOI: 10.1038/s41586-020-2588-y.Peer-Reviewed Original ResearchConceptsSevere COVID-19Moderate COVID-19Immune signaturesDisease outcomeCOVID-19Disease trajectoriesInterleukin-5Early immune signaturesInnate cell lineagesType 2 effectorsT cell numbersPoor clinical outcomeWorse disease outcomesImmune response profileCoronavirus disease 2019Distinct disease trajectoriesCytokine levelsImmunological correlatesImmune profileClinical outcomesEarly elevationImmune profilingIL-13Immunoglobulin EDisease 2019Development and Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation
Haimovich AD, Ravindra NG, Stoytchev S, Young HP, Wilson FP, van Dijk D, Schulz WL, Taylor RA. Development and Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation. Annals Of Emergency Medicine 2020, 76: 442-453. PMID: 33012378, PMCID: PMC7373004, DOI: 10.1016/j.annemergmed.2020.07.022.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedBetacoronavirusClinical Laboratory TechniquesCoronavirus InfectionsCOVID-19COVID-19 TestingEmergency Service, HospitalFemaleHumansMaleMiddle AgedOxygen Inhalation TherapyPandemicsPneumonia, ViralRespiratory InsufficiencyRetrospective StudiesRisk AssessmentSARS-CoV-2Severity of Illness IndexYoung AdultConceptsCOVID-19 Severity IndexQuick COVID-19 severity indexQuick Sequential Organ Failure AssessmentSequential Organ Failure AssessmentOrgan Failure AssessmentHours of admissionRespiratory failureSeverity IndexScoring systemSevere acute respiratory syndrome coronavirus 2Acute respiratory syndrome coronavirus 2Respiratory syndrome coronavirus 2Bedside scoring systemOxygen requirementPneumonia severity scoresHours of hospitalizationElixhauser Comorbidity IndexEmergency department patientsSeverity Index scoreCOVID-19 patientsSyndrome coronavirus 2Coronavirus disease 2019Failure AssessmentSimple scoring systemIndependent test cohortLeveraging the Electronic Health Records for Population Health: A Case Study of Patients With Markedly Elevated Blood Pressure
Lu Y, Huang C, Mahajan S, Schulz WL, Nasir K, Spatz ES, Krumholz HM. Leveraging the Electronic Health Records for Population Health: A Case Study of Patients With Markedly Elevated Blood Pressure. Journal Of The American Heart Association 2020, 9: e015033. PMID: 32200730, PMCID: PMC7428633, DOI: 10.1161/jaha.119.015033.Peer-Reviewed Original ResearchConceptsDiastolic blood pressureSystolic blood pressureElevated blood pressureBlood pressureElectronic health recordsPopulation health surveillanceHealth recordsYale New Haven Health SystemHealth surveillanceHealth systemPatterns of patientsLarge health systemUsual careOutpatient encountersControl ratePatientsCare patternsPopulation healthMonthsHgSurveillancePrevalenceRecordsVisitsCare
2019
Blood utilisation and transfusion reactions in adult patients transfused with conventional or pathogen‐reduced platelets
Bahar B, Schulz WL, Gokhale A, Spencer BR, Gehrie EA, Snyder EL. Blood utilisation and transfusion reactions in adult patients transfused with conventional or pathogen‐reduced platelets. British Journal Of Haematology 2019, 188: 465-472. PMID: 31566724, PMCID: PMC7003815, DOI: 10.1111/bjh.16187.Peer-Reviewed Original ResearchConceptsPathogen-reduced plateletsTransfusion reactionsPlatelet componentsAdult patientsPlatelet transfusionsSeptic transfusion reactionsRed blood cell transfusion requirementsPR plateletsYale-New Haven HospitalPlatelet component transfusionsComparable clinical efficacyType of transfusionTransfusion requirementsTransfusion trendsPlatelet administrationComponent transfusionClinical efficacyNumber of RBCsConventional plateletsBlood utilisationPatientsTransfusionMean timePlateletsRBCsCharacteristics of High Cardiovascular Risk in 1.7 Million Chinese Adults.
Lu J, Lu Y, Yang H, Bilige W, Li Y, Schulz W, Masoudi FA, Krumholz HM. Characteristics of High Cardiovascular Risk in 1.7 Million Chinese Adults. Annals Of Internal Medicine 2019, 170: 298-308. PMID: 30776800, DOI: 10.7326/m18-1932.Peer-Reviewed Original ResearchConceptsHigh CVD riskCVD riskHigh riskHigh cardiovascular disease riskCardiovascular risk increasesHigh cardiovascular riskOverall study populationCardiovascular disease riskBody mass indexMultivariable mixed modelsNational Health CommissionAntihypertensive medicationsAspirin useCardiovascular riskCVD screeningMass indexStudy populationChinese adultsHan ethnicityDisease riskStatinsMixed modelsHealth CommissionSocioeconomic statusPopulation subgroups