2024
Differential diagnosis of suspected multiple sclerosis: global health considerations
Correale J, Solomon A, Cohen J, Banwell B, Gracia F, Gyang T, de Bedoya F, Harnegie M, Hemmer B, Jacob A, Kim H, Marrie R, Mateen F, Newsome S, Pandit L, Prayoonwiwat N, Sahraian M, Sato D, Saylor D, Shi F, Siva A, Tan K, Viswanathan S, Wattjes M, Weinshenker B, Yamout B, Fujihara K. Differential diagnosis of suspected multiple sclerosis: global health considerations. The Lancet Neurology 2024, 23: 1035-1049. PMID: 39304243, DOI: 10.1016/s1474-4422(24)00256-4.Peer-Reviewed Original ResearchConceptsWestern EuropeLatin AmericaEastern EuropeMiddle EastSoutheast AsiaNorth AmericaLatinEuropeHealth considerationsDifferential diagnosis of multiple sclerosisAfricaAmericaPacific regionAsiaDiagnosis of multiple sclerosisDifferential diagnosisCollaborative effortsComprehensive approachMultiple sclerosisEastMedical careDifferential diagnosis of suspected multiple sclerosis: considerations in people from minority ethnic and racial backgrounds in North America, northern Europe, and Australasia
Amezcua L, Rotstein D, Shirani A, Ciccarelli O, Ontaneda D, Magyari M, Rivera V, Kimbrough D, Dobson R, Taylor B, Williams M, Marrie R, Banwell B, Hemmer B, Newsome S, Cohen J, Solomon A, Royal W. Differential diagnosis of suspected multiple sclerosis: considerations in people from minority ethnic and racial backgrounds in North America, northern Europe, and Australasia. The Lancet Neurology 2024, 23: 1050-1062. PMID: 39304244, DOI: 10.1016/s1474-4422(24)00288-6.Peer-Reviewed Original ResearchMeSH KeywordsAustralasiaDiagnosis, DifferentialEthnic and Racial MinoritiesEthnicityEuropeHumansMultiple SclerosisNorth AmericaConceptsSocial determinants of healthDeterminants of healthRacial backgroundSocial determinantsDiagnosis of multiple sclerosisClinical characteristics of peopleCharacteristics of peopleWhite peopleMultiple sclerosisDifferential diagnosisPrevalence of multiple sclerosisSocial challengesMinorityChanging demographicsDifferential diagnosis of multiple sclerosisWhite populationNorthern EuropePeopleEuropeMultiple sclerosis can be diagnosed solely with dissemination in space: No
Hemond C, Solomon A. Multiple sclerosis can be diagnosed solely with dissemination in space: No. Multiple Sclerosis Journal 2024, 30: 639-641. PMID: 38616532, DOI: 10.1177/13524585241245297.Peer-Reviewed Original ResearchAssessing Free-Living Postural Sway in Persons With Multiple Sclerosis
Meyer B, Cohen J, DePetrillo P, Ceruolo M, Jangraw D, Cheney N, Solomon A, McGinnis R. Assessing Free-Living Postural Sway in Persons With Multiple Sclerosis. IEEE Transactions On Neural Systems And Rehabilitation Engineering 2024, 32: 967-973. PMID: 38373134, PMCID: PMC10966905, DOI: 10.1109/tnsre.2024.3366903.Peer-Reviewed Original ResearchConceptsMeasures of postural swayPostural swayFall riskPostural instabilityAssessment of postural instabilityRemote patient monitoring technologyPostural sway assessmentMeasures of balanceMeasures of swayPredicting fall riskPatient-reported measuresPatient monitoring technologyForce platformBalance impairmentDisease statusMobility impairmentsWearable accelerometersLab-based measuresAssociated with disease statusSwayMultiple sclerosisAnalyzed dataRiskArea under curveDaily lifeMultiple Sclerosis Diagnostic Delay and Misdiagnosis
Kaisey M, Solomon A. Multiple Sclerosis Diagnostic Delay and Misdiagnosis. Neurologic Clinics 2024, 42: 1-13. PMID: 37980109, DOI: 10.1016/j.ncl.2023.07.001.Peer-Reviewed Original ResearchConceptsMultiple sclerosis misdiagnosisPatients' clinical outcomesMS diagnostic criteriaMS symptomsClinical outcomesDiagnostic delayDiagnostic challengeDiagnostic criteriaMS misdiagnosisDiagnostic biomarkersAccurate diagnosisIncorrect diagnosisPatientsDiagnosisMisdiagnosisEducational effortsSymptoms
2023
A multicenter pilot study evaluating simplified central vein assessment for the diagnosis of multiple sclerosis
Daboul L, O’Donnell C, Amin M, Rodrigues P, Derbyshire J, Azevedo C, Bar-Or A, Caverzasi E, Calabresi P, Cree B, Freeman L, Henry R, Longbrake E, Oh J, Papinutto N, Pelletier D, Prchkovska V, Raza P, Ramos M, Samudralwar R, Schindler M, Sotirchos E, Sicotte N, Solomon A, Shinohara R, Reich D, Sati P, Ontaneda D. A multicenter pilot study evaluating simplified central vein assessment for the diagnosis of multiple sclerosis. Multiple Sclerosis Journal 2023, 30: 25-34. PMID: 38088067, PMCID: PMC11037932, DOI: 10.1177/13524585231214360.Peer-Reviewed Original ResearchMeSH KeywordsAdultBrainFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedMultiple SclerosisPilot ProjectsReproducibility of ResultsVeinsYoung AdultConceptsCentral vein signMultiple sclerosisPositive lesionsInter-rater agreementDiagnosis of MSMagnetic resonance imaging (MRI) biomarkersDiagnostic performancePossible multiple sclerosisInter-rater reliability assessmentGood diagnostic performanceMcDonald criteriaMulticenter studyVein assessmentMean ageVein signImaging biomarkersLesionsMRI sequencesCharacteristic curveSclerosisPatientsDiagnosisAssessmentParticipantsOptimal methodDigital Phenotypes of Instability and Fatigue Derived From Daily Standing Transitions in Persons With Multiple Sclerosis
VanDyk T, Meyer B, DePetrillo P, Donahue N, O’Leary A, Fox S, Cheney N, Ceruolo M, Solomon A, McGinnis R. Digital Phenotypes of Instability and Fatigue Derived From Daily Standing Transitions in Persons With Multiple Sclerosis. IEEE Transactions On Neural Systems And Rehabilitation Engineering 2023, 31: 2279-2286. PMID: 37115839, PMCID: PMC10408384, DOI: 10.1109/tnsre.2023.3271601.Peer-Reviewed Original ResearchConceptsPrediction of fall riskStanding transitionsDigital phenotypingFall riskNon-fallersSymptom monitoringPhysician assessmentMultiple sclerosisBiweekly assessmentsClinical metricsCharacterize symptomsHome monitoringSymptomsFatigueMotor instabilityAccelerometryFallersAssessmentPwMSPersonsApplications of wearablePhysiciansIsolation periodActivity classifierInterventionChest-Based Wearables and Individualized Distributions for Assessing Postural Sway in Persons With Multiple Sclerosis
Meyer B, Cohen J, Donahue N, Fox S, O’Leary A, Brown A, Leahy C, VanDyk T, DePetrillo P, Ceruolo M, Cheney N, Solomon A, McGinnis R. Chest-Based Wearables and Individualized Distributions for Assessing Postural Sway in Persons With Multiple Sclerosis. IEEE Transactions On Neural Systems And Rehabilitation Engineering 2023, 31: 2132-2139. PMID: 37067975, PMCID: PMC10408383, DOI: 10.1109/tnsre.2023.3267807.Peer-Reviewed Original ResearchMeSH KeywordsBiomechanical PhenomenaHumansMultiple SclerosisPostural BalancePostureWearable Electronic DevicesConceptsPatient-reported measuresPostural sway featuresPostural swaySway featuresForce platformBalance assessmentMeasures of postural swayPostural sway measuresAssess postural swayStanding tasksSway measuresFall statusBalance impairmentLower backMobility impairmentsConcurrent validityChest accelerometerEyes-openMultiple sclerosisSensor patchSwayStatus groupsEyes-closedAccelerometerTraditional computers
2022
How Much Data Is Enough? A Reliable Methodology to Examine Long-Term Wearable Data Acquisition in Gait and Postural Sway
Meyer B, Depetrillo P, Franco J, Donahue N, Fox S, O’Leary A, Loftness B, Gurchiek R, Buckley M, Solomon A, Ng S, Cheney N, Ceruolo M, McGinnis R. How Much Data Is Enough? A Reliable Methodology to Examine Long-Term Wearable Data Acquisition in Gait and Postural Sway. Sensors 2022, 22: 6982. PMID: 36146348, PMCID: PMC9503816, DOI: 10.3390/s22186982.Peer-Reviewed Original ResearchConceptsFree-living environmentBalance impairmentIntra-class correlationPostural sway measuresMeasures of gaitEvaluation of gaitWearable accelerometer dataWear durationSway measuresPostural swayCapturing gaitEstablished patientMovement variabilityImpairment measuresGaitPatient burdenAccelerometer dataClinical measuresDays of monitoringWearable sensor-based methodsSensor wearSwayRegression analysisComprehensive assessmentStudy costsThe Sit-to-Stand Transition as a Biomarker for Impairment: Comparison of Instrumented 30-Second Chair Stand Test and Daily Life Transitions in Multiple Sclerosis
Tulipani L, Meyer B, Fox S, Solomon A, Mcginnis R. The Sit-to-Stand Transition as a Biomarker for Impairment: Comparison of Instrumented 30-Second Chair Stand Test and Daily Life Transitions in Multiple Sclerosis. IEEE Transactions On Neural Systems And Rehabilitation Engineering 2022, 30: 1213-1222. PMID: 35468063, PMCID: PMC9204833, DOI: 10.1109/tnsre.2022.3169962.Peer-Reviewed Original ResearchMeSH KeywordsArea Under CurveBiomarkersHumansMultiple SclerosisPostural BalanceWearable Electronic DevicesConceptsSensory impairmentInvestigate impairmentsDaily lifeLevel of clinical disabilityPerformance metricsStructured tasksImpairmentPyramidal impairmentSub scoresMultiple sclerosisDaily life monitoringDichotomize participantsSit-stand transitionsClinical disabilityClassification performanceTaskWearable sensorsSupervised settingChest featuresFaller classificationDeficitsLife monitoringLow fall riskArea under the curveFunctional assessmentEvaluation of unsupervised 30-second chair stand test performance assessed by wearable sensors to predict fall status in multiple sclerosis
Tulipani L, Meyer B, Allen D, Solomon A, McGinnis R. Evaluation of unsupervised 30-second chair stand test performance assessed by wearable sensors to predict fall status in multiple sclerosis. Gait & Posture 2022, 94: 19-25. PMID: 35220031, PMCID: PMC9086135, DOI: 10.1016/j.gaitpost.2022.02.016.Peer-Reviewed Original ResearchConceptsWearable sensorsFall statusFall riskUnsupervised conditionsChair stand test performanceClassification AUCUnsupervised monitoringChair stand testAccelerometer-derived metricsPredicting fall riskStandard Functional AssessmentSupervised performanceBalance confidenceFunctional mobilityWearableNon-fallersStand testBalance deficitsRoutine clinical assessmentSupervision visitsSensorThree-month periodPerformanceFunctional assessmentMultiple sclerosis
2021
Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis
Meyer B, Tulipani L, Gurchiek R, Allen D, Adamowicz L, Larie D, Solomon A, Cheney N, McGinnis R. Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis. IEEE Journal Of Biomedical And Health Informatics 2021, 25: 1824-1831. PMID: 32946403, PMCID: PMC8221405, DOI: 10.1109/jbhi.2020.3025049.Peer-Reviewed Original ResearchMeSH KeywordsAccidental FallsDeep LearningGaitHumansMultiple SclerosisProspective StudiesRetrospective StudiesWalkingWearable Electronic DevicesConceptsWearable sensorsPreventive interventionsBidirectional long short-termInexpensive wearable sensorsDeep neural networksWearable sensor dataFall prevention interventionsSpatiotemporal gait parametersFall risk assessmentLong-Short-TermMachine learning modelsGait biomechanicsGait parametersSensor dataFall riskNeural networkHealthcare providersStatistical featuresLearning modelsPatient reportsAccelerometer dataIdentified measuresMultiple sclerosisWearableGood performance
2020
Metrics extracted from a single wearable sensor during sit-stand transitions relate to mobility impairment and fall risk in people with multiple sclerosis
Tulipani L, Meyer B, Larie D, Solomon A, McGinnis R. Metrics extracted from a single wearable sensor during sit-stand transitions relate to mobility impairment and fall risk in people with multiple sclerosis. Gait & Posture 2020, 80: 361-366. PMID: 32615409, PMCID: PMC7413823, DOI: 10.1016/j.gaitpost.2020.06.014.Peer-Reviewed Original ResearchConceptsInertial sensorsAccelerometer-based approachFall riskBalance confidenceWearable inertial sensorsStand-to-sit transitionsTriaxial acceleration dataFall statusWearable sensorsAccelerometer-based metricsMeasures of disease severityAccelerometer featuresSelf-report outcome measuresChair stand testWearable accelerometersAccelerometer-derived metricsSit-to-standSit-stand transitionsAccuracy of functional assessmentsChallenging taskMetricsSensorClinical metricsAcceleration dataLogistic regression models
2015
Detection of postural sway abnormalities by wireless inertial sensors in minimally disabled patients with multiple sclerosis: a case–control study
Solomon A, Jacobs J, Lomond K, Henry S. Detection of postural sway abnormalities by wireless inertial sensors in minimally disabled patients with multiple sclerosis: a case–control study. Journal Of NeuroEngineering And Rehabilitation 2015, 12: 74. PMID: 26324067, PMCID: PMC4556213, DOI: 10.1186/s12984-015-0066-9.Peer-Reviewed Original ResearchConceptsActivities-specific Balance ConfidenceWireless inertial sensorsBalance impairmentMSWS-12Postural swayExpanded Disability Status ScaleMobility impairmentsPatient reportsMeasures of postural swayTimed 25-Foot WalkMS Walking ScaleMSWS-12 scoresImpaired gait speedSway path lengthResultsThe regression modelPredictors of group statusRegression modelsEyes-open conditionLogistic regression modelsCase-control studyBalance confidenceGait speedInertial sensorsInertial motion sensorsInstrumented sway