2023
A privacy-preserving and computation-efficient federated algorithm for generalized linear mixed models to analyze correlated electronic health records data
Yan Z, Zachrison K, Schwamm L, Estrada J, Duan R. A privacy-preserving and computation-efficient federated algorithm for generalized linear mixed models to analyze correlated electronic health records data. PLOS ONE 2023, 18: e0280192. PMID: 36649349, PMCID: PMC9844867, DOI: 10.1371/journal.pone.0280192.Peer-Reviewed Original ResearchConceptsFederated algorithmPrivacy-preserving data integrationEHR dataElectronic health record dataComputation resource requirementsHealth record dataLongitudinal EHR dataPrivacy protectionData integrationResource requirementsMultiple healthcare facilitiesNumerical experimentsComputational efficiencyGeneralized linear mixed modelRecord dataCorrelated dataSite‐level heterogeneityAlgorithmNetworkSummary statisticsResearch NetworkLimited amountDatasetLinear mixed modelsGLMM
2019
Epilepsy Among Elderly Medicare Beneficiaries
Moura L, Smith J, Blacker D, Vogeli C, Schwamm L, Cole A, Hernandez-Diaz S, Hsu J. Epilepsy Among Elderly Medicare Beneficiaries. Medical Care 2019, 57: 318-324. PMID: 30762723, PMCID: PMC6417929, DOI: 10.1097/mlr.0000000000001072.Peer-Reviewed Original ResearchConceptsMedicare administrative dataEpilepsy statusMedicare beneficiariesMedicare dataEpilepsy diagnosisElectronic health record dataElderly Medicare beneficiariesHealth record dataHealth insurance claimsAdministrative dataElectronic health recordsIncident epilepsyPrevalent epilepsyDrug claimsEpilepsyDiagnostic thresholdStratified random sampleInverse probabilityHealth recordsMedicare claims can identify post-stroke epilepsy
Moura L, Smith J, Blacker D, Vogeli C, Schwamm L, Hsu J. Medicare claims can identify post-stroke epilepsy. Epilepsy Research 2019, 151: 40-47. PMID: 30780120, PMCID: PMC6640134, DOI: 10.1016/j.eplepsyres.2019.02.002.Peer-Reviewed Original ResearchConceptsElectronic health recordsAccountable care organizationsMedicare claimsCommunity-dwelling elderly individualsPost-stroke epilepsyElderly Medicare beneficiariesClaims-based algorithmPositive predictive valuePioneer Accountable Care OrganizationsDiscrete etiologyNeurologist visitOverall prevalenceMedicare patientsClaims diagnosesPSE diagnosisElderly individualsMedicare beneficiariesPatientsPredictive valueEpilepsyFuture epidemiological surveillanceEpidemiological surveillanceInverse probabilityHealth recordsDiagnosis
2014
Exposing Hidden Truncation-Related Errors in Acute Stroke Perfusion Imaging
Copen W, Deipolyi A, Schaefer P, Schwamm L, González R, Wu O. Exposing Hidden Truncation-Related Errors in Acute Stroke Perfusion Imaging. American Journal Of Neuroradiology 2014, 36: 638-645. PMID: 25500309, PMCID: PMC7964314, DOI: 10.3174/ajnr.a4186.Peer-Reviewed Original ResearchConceptsPerfusion scanVolume of lesionsScan durationSymptom onsetAcute infarctsHemodynamic measurementsLesion reversalClinical trialsLesion volumePatient managementPerfusion MRPerfusion imagingInjected contrast agentPerfusion imagesPatient CTLesionsDurationMTTCTLong scan durationScansContrast agentsShort scan durationTmaxPerfusion estimates
2009
A score to predict early risk of recurrence after ischemic strokeSYMBOLSYMBOL
Ay H, Gungor L, Arsava E, Rosand J, Vangel M, Benner T, Schwamm L, Furie K, Koroshetz W, Sorensen A. A score to predict early risk of recurrence after ischemic strokeSYMBOLSYMBOL. Neurology 2009, 74: 128-135. PMID: 20018608, PMCID: PMC2809031, DOI: 10.1212/wnl.0b013e3181ca9cff.Peer-Reviewed Original ResearchConceptsRecurrent strokeEarly riskPrognostic scoreConsecutive ischemic stroke patientsComprehensive prognostic scoreTIA/strokeAcute stroke careIschemic stroke patientsPredictors of recurrenceRisk of recurrenceCox regression modelEtiologic stroke subtypesPatient management algorithmsBrain infarctsAcute settingIschemic strokeStroke subtypesIndependent predictorsStroke careStroke patientsImaging featuresPrior historySeparate cohortClinical practiceStrokeNumber Needed to Treat to Benefit and to Harm for Intravenous Tissue Plasminogen Activator Therapy in the 3- to 4.5-Hour Window
Saver J, Gornbein J, Grotta J, Liebeskind D, Lutsep H, Schwamm L, Scott P, Starkman S. Number Needed to Treat to Benefit and to Harm for Intravenous Tissue Plasminogen Activator Therapy in the 3- to 4.5-Hour Window. Stroke 2009, 40: 2433-2437. PMID: 19498197, PMCID: PMC2724988, DOI: 10.1161/strokeaha.108.543561.Peer-Reviewed Original ResearchConceptsTissue plasminogen activatorRankin ScaleIntravenous tissue plasminogen activator therapyIntravenous tissue plasminogen activatorTissue plasminogen activator therapyPlasminogen activatorAcute cerebral ischemiaModified Rankin ScalePlasminogen activator therapyResults of therapyEffect sizeCerebral ischemiaPoststroke disabilityAdditional patientsActivator therapyWorse outcomesGlobal disabilityTreatment decisionsBetter outcomesClinical practicePatientsNNTBLikelihood of helpEffect size estimatesTable analysisCost-Effectiveness of Patient Selection Using Penumbral-Based MRI for Intravenous Thrombolysis
Earnshaw S, Jackson D, Farkouh R, Schwamm L. Cost-Effectiveness of Patient Selection Using Penumbral-Based MRI for Intravenous Thrombolysis. Stroke 2009, 40: 1710-1720. PMID: 19286581, DOI: 10.1161/strokeaha.108.540138.Peer-Reviewed Original ResearchMeSH KeywordsAgedAlgorithmsCerebral HemorrhageCost-Benefit AnalysisDecision Support TechniquesFemaleFibrinolytic AgentsHumansImage Processing, Computer-AssistedInfusions, IntravenousMagnetic Resonance ImagingMalePatient SelectionProportional Hazards ModelsQuality-Adjusted Life YearsStrokeThrombolytic TherapyTomography, X-Ray ComputedTreatment OutcomeConceptsMRI selection
2005
Recommendations for the Establishment of Stroke Systems of Care
Schwamm L, Pancioli A, Acker J, Goldstein L, Zorowitz R, Shephard T, Moyer P, Gorman M, Johnston S, Duncan P, Gorelick P, Frank J, Stranne S, Smith R, Federspiel W, Horton K, Magnis E, Adams R. Recommendations for the Establishment of Stroke Systems of Care. Stroke 2005, 36: 690-703. PMID: 15689577, DOI: 10.1161/01.str.0000158165.42884.4f.Peer-Reviewed Original Research
2001
Predicting Tissue Outcome in Acute Human Cerebral Ischemia Using Combined Diffusion- and Perfusion-Weighted MR Imaging
Wu O, Koroshetz W, Østergaard L, Buonanno F, Copen W, Gonzalez R, Rordorf G, Rosen B, Schwamm L, Weisskoff R, Sorensen A. Predicting Tissue Outcome in Acute Human Cerebral Ischemia Using Combined Diffusion- and Perfusion-Weighted MR Imaging. Stroke 2001, 32: 933-942. PMID: 11283394, DOI: 10.1161/01.str.32.4.933.Peer-Reviewed Original Research