2021
High epileptiform discharge burden predicts delayed cerebral ischemia after subarachnoid hemorrhage
Kim JA, Zheng WL, Elmer J, Jing J, Zafar SF, Ghanta M, Moura V, Gilmore EJ, Hirsch LJ, Patel A, Rosenthal E, Westover MB. High epileptiform discharge burden predicts delayed cerebral ischemia after subarachnoid hemorrhage. Clinical Neurophysiology 2021, 141: 139-146. PMID: 33812771, PMCID: PMC8429508, DOI: 10.1016/j.clinph.2021.01.022.Peer-Reviewed Original ResearchConceptsED burdenSubarachnoid hemorrhageEpileptiform dischargesCerebral ischemiaSAH patientsHigh riskOnset of DCIMajor risk periodContinuous EEG recordingsDCI patientsDCI riskRetrospective analysisNovel biomarkersGroup-based trajectory analysisRisk periodPatientsDay 3.5DCIBurdenHemorrhageIschemiaRiskEEG recordingsBurden rateUseful parameter
2020
Validation of an algorithm of time-dependent electro-clinical risk stratification for electrographic seizures (TERSE) in critically ill patients
Cissé FA, Osman GM, Legros B, Depondt C, Hirsch LJ, Struck AF, Gaspard N. Validation of an algorithm of time-dependent electro-clinical risk stratification for electrographic seizures (TERSE) in critically ill patients. Clinical Neurophysiology 2020, 131: 1956-1961. PMID: 32622337, DOI: 10.1016/j.clinph.2020.05.031.Peer-Reviewed Original ResearchConceptsElectrographic seizuresRisk stratificationIll patientsAcute brain injuryContinuous electroencephalography monitoringElectrographic status epilepticusSubgroup of patientsDuration of EEGClinical seizuresConsecutive patientsStatus epilepticusElectroencephalography monitoringBrain injuryMedical recordsSubstantial burdenPatientsClinical practiceCEEGClinical neurophysiologistsSeizuresClinical implementationEEG recordingsTwo-thirdsFuture studiesEEG time
2019
Comparison of machine learning models for seizure prediction in hospitalized patients
Struck AF, Rodriguez‐Ruiz A, Osman G, Gilmore EJ, Haider HA, Dhakar MB, Schrettner M, Lee JW, Gaspard N, Hirsch LJ, Westover MB, Consortium C. Comparison of machine learning models for seizure prediction in hospitalized patients. Annals Of Clinical And Translational Neurology 2019, 6: 1239-1247. PMID: 31353866, PMCID: PMC6649418, DOI: 10.1002/acn3.50817.Peer-Reviewed Original ResearchConceptsLow-risk patientsNegative predictive valueEvaluation cohortContinuous EEGElastic net logistic regressionMulticenter databaseRisk stratificationSeizure riskPatientsPredictive valueComparable AUCSecondary analysisLogistic regressionCohortFirst hourSeizure predictionEEG recordingsEEGRisk calibrationLarge proportionSeizuresComplex neural networks
2017
Standardized computer-based organized reporting of EEG: SCORE – Second version
Beniczky S, Aurlien H, Brøgger JC, Hirsch LJ, Schomer DL, Trinka E, Pressler RM, Wennberg R, Visser GH, Eisermann M, Diehl B, Lesser RP, Kaplan PW, Nguyen The Tich S, Lee JW, Martins-da-Silva A, Stefan H, Neufeld M, Rubboli G, Fabricius M, Gardella E, Terney D, Meritam P, Eichele T, Asano E, Cox F, van Emde Boas W, Mameniskiene R, Marusic P, Zárubová J, Schmitt FC, Rosén I, Fuglsang-Frederiksen A, Ikeda A, MacDonald DB, Terada K, Ugawa Y, Zhou D, Herman ST. Standardized computer-based organized reporting of EEG: SCORE – Second version. Clinical Neurophysiology 2017, 128: 2334-2346. PMID: 28838815, DOI: 10.1016/j.clinph.2017.07.418.Peer-Reviewed Original ResearchConceptsCritical care EEG terminologyUseful clinical toolEEG terminologyNeonatal recordingsClinical careClinical relevanceClinical neurophysiologyClinical practiceDiagnostic significanceClinical toolInternational FederationInternational consensusScoresEEG recordingsStandardized listStandardized terminologyEEGAdditional choiceStandardized termsSeizuresBrief Potentially Ictal Rhythmic Discharges [B(I)RDs] in Noncritically Ill Adults
Yoo JY, Marcuse LV, Fields MC, Rosengard JL, Traversa MV, Gaspard N, Hirsch LJ. Brief Potentially Ictal Rhythmic Discharges [B(I)RDs] in Noncritically Ill Adults. Journal Of Clinical Neurophysiology 2017, 34: 222-229. PMID: 28463933, DOI: 10.1097/wnp.0000000000000357.Peer-Reviewed Original ResearchConceptsIctal rhythmic dischargesIll adultsRhythmic dischargesSeizure onset areaAdult patientsElectrographic characteristicsStatus epilepticusAcute findingsIll patientsRefractory epilepsyClinical historySeizure onsetClinical significanceEpileptiform dischargesAmbulatory settingPatientsBenign patternControl groupEpilepsyRhythmic activityOnset areaAlpha activityAdultsBrief runsEEG recordings
2013
Intracranially recorded interictal spikes: Relation to seizure onset area and effect of medication and time of day
Goncharova II, Spencer SS, Duckrow RB, Hirsch LJ, Spencer DD, Zaveri HP. Intracranially recorded interictal spikes: Relation to seizure onset area and effect of medication and time of day. Clinical Neurophysiology 2013, 124: 2119-2128. PMID: 23856192, DOI: 10.1016/j.clinph.2013.05.027.Peer-Reviewed Original ResearchIntracranial EEG evaluation of relationship within a resting state network
Duncan D, Duckrow RB, Pincus SM, Goncharova I, Hirsch LJ, Spencer DD, Coifman RR, Zaveri HP. Intracranial EEG evaluation of relationship within a resting state network. Clinical Neurophysiology 2013, 124: 1943-1951. PMID: 23790525, DOI: 10.1016/j.clinph.2013.03.028.Peer-Reviewed Original ResearchConceptsDefault mode networkIntracranial EEG evaluationMode networkLocalization-related epilepsyCross-approximate entropyNeuronal involvementHemodynamic measurementsIntracranial EEG recordingsEEG evaluationBackground activityGamma powerFMRI studyIntracranial EEGBrain activityPatientsEEG recordingsLow levelsT2EpilepsyMagnitude squared coherenceT1Pitfalls in ictal EEG interpretation
Gaspard N, Hirsch LJ. Pitfalls in ictal EEG interpretation. Neurology 2013, 80: s26-s42. PMID: 23267042, DOI: 10.1212/wnl.0b013e31827974f8.Peer-Reviewed Original Research
2007
Cyclic electrographic seizures in critically ill patients
Friedman DE, Schevon C, Emerson RG, Hirsch LJ. Cyclic electrographic seizures in critically ill patients. Epilepsia 2007, 49: 281-287. PMID: 17900293, DOI: 10.1111/j.1528-1167.2007.01327.x.Peer-Reviewed Original ResearchConceptsCyclic seizuresIll patientsPattern of seizuresStandard EEG recordingsNonconvulsive seizuresStatus epilepticusElectrographic seizuresSeizure activityUnderlying pathophysiologyElectroencephalographic monitoringSeizure initiationEEG frequency spectrumPatientsSeizuresContinuous EEGEEG powerPathophysiologyEEG recordingsCsAEpilepticusCessation
2002
Heart rate and EKG changes in 102 seizures: analysis of influencing factors
Opherk C, Coromilas J, Hirsch LJ. Heart rate and EKG changes in 102 seizures: analysis of influencing factors. Epilepsy Research 2002, 52: 117-127. PMID: 12458028, DOI: 10.1016/s0920-1211(02)00215-2.Peer-Reviewed Original ResearchConceptsEKG abnormalitiesIctal heart rateHeart rateGeneralized seizuresEKG changesT-wave inversionMajority of seizuresHippocampal sclerosisSeizure durationST depressionSinus tachycardiaRisk factorsUnexpected deathHigh riskCardiac arrhythmiasEpileptic seizuresSeizuresAbnormalitiesPatientsMajor causeLeft hemisphereEpilepsyEEG recordingsResponsible factorsSUDEPIctal heart rate differentiates epileptic from non-epileptic seizures
Opherk C, Hirsch LJ. Ictal heart rate differentiates epileptic from non-epileptic seizures. Neurology 2002, 58: 636-638. PMID: 11865145, DOI: 10.1212/wnl.58.4.636.Peer-Reviewed Original Research