Gamaleldin M Osman1, Davi F Araújo2, Carolina B Maciel3,4. 1. Department of Neurology, Henry Ford Hospital, Detroit, Michigan, 48202, USA. 2. Federal University of Ceará School of Medicine, Fortaleza, CE, 60430-160, Brazil. 3. Department of Neurology. Neurocritical Care Division, Yale University School of Medicine, New Haven, CT, 06520, USA. carolina.maciel@yale.edu. 4. Department of Neurology, Neurocritical Care Division, McKnight Brain Institute, 1149 Newell Dr/L3-185, Gainesville, FL, 32610, USA. carolina.maciel@yale.edu.
Abstract
PURPOSE OF REVIEW: To present data available on the epidemiology and significance of rhythmic and periodic patterns that lie on the ictal interictal continuum and propose an algorithm for the clinical approach to patients exhibiting these patterns. RECENT FINDINGS: There is accumulating evidence on the prognostic implications of various rhythmic and periodic patterns in the critically ill population. These patterns are not only associated with increased seizure risk but have also been associated with worse outcome and increased long-term risk of epilepsy in recent studies. There is emerging evidence suggesting that certain EEG features as well as ancillary studies including serum, neuroimaging, and invasive multimodality monitory can assist in the risk stratification of neuronal injury associated with these patterns, allowing for a targeted approach to these patterns. We present a case illustrating the clinical nuances of these patterns. We propose an algorithm for a personalized and targeted approach to ictal interictal patterns based on risk stratification according to clinical, EEG, imaging, and invasive monitoring markers.
PURPOSE OF REVIEW: To present data available on the epidemiology and significance of rhythmic and periodic patterns that lie on the ictal interictal continuum and propose an algorithm for the clinical approach to patients exhibiting these patterns. RECENT FINDINGS: There is accumulating evidence on the prognostic implications of various rhythmic and periodic patterns in the critically ill population. These patterns are not only associated with increased seizure risk but have also been associated with worse outcome and increased long-term risk of epilepsy in recent studies. There is emerging evidence suggesting that certain EEG features as well as ancillary studies including serum, neuroimaging, and invasive multimodality monitory can assist in the risk stratification of neuronal injury associated with these patterns, allowing for a targeted approach to these patterns. We present a case illustrating the clinical nuances of these patterns. We propose an algorithm for a personalized and targeted approach to ictal interictal patterns based on risk stratification according to clinical, EEG, imaging, and invasive monitoring markers.
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