Details

Autor(en) / Beteiligte

• Bennett- Back, O
• Uliel-Siboni, S
• Kramer, U

Titel

The Yield of Video-EEG Telemetry Evaluation for Non-Surgical Candidate Children

Ist Teil von

• European journal of paediatric neurology, 2016-11, Vol.20 (6), p.848-854

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2016

Quelle

Access via ScienceDirect (Elsevier)

Beschreibungen/Notizen

• Abstract Background Video EEG (VEEG) is performed for most pediatric patients in order to evaluate unclear paroxysmal events and improve our understanding of difficult to control epileptic patients. Purpose To characterize the video EEG studies on children who are not candidates for surgery in order to identify the parameters that affect results in level of improving the rate of acquisition, as well as improving the ability to expect the likelihood of epilepsy and of gathering new information as a result of the VEEG. Methods Retrospective chart analysis of all consecutive patients who underwent VEEG in two VEEG monitoring units. Results: 323 children of a mean age of 7 years (STD 4.73, range 0-17 years) were monitored for a mean duration of 2 days (STD 1.65, range 1-10 days( The main reasons for monitoring were: evaluation of unclear events (n=234), evaluation of previously diagnosed epilepsy (n=36) and confirmation of Electrical Status Epilepticus in Sleep (ESES) (n=34). The main event types for evaluation were: staring episodes (n=67), myoclonic jerks (n=35) and abnormal eye movements (n=22). Suspected events were captured in 70% of the patients. There was a positive correlation between acquisition of suspected events and each of the following: duration of the monitoring, the frequency of investigated events per history, the type of investigated events. A prior interictal epileptic activity on routine EEG was a positive predictor of an event to be epileptic (p=0.003). Amongst the group of known epileptic patients, VEEG had role in changing diagnosis in 53% of patients. Many of them had focal interictal epileptiform activity in their routine EEG. Conclusions Selecting patients with frequent events and longer monitoring periods increase the yield of VEEG. Looking carefully into clinical characteristics of the patient prior to VEEG can clarify diagnosis therefore render the VEEG test superfluous to subgroups of patients. Prior routine epileptic EEG, coexistence of other seizure types, behaviors accompanying the investigated habitual behavior and abnormalities in other investigations (MRI, cognitive function and EEG) are the parameters that can predict diagnosis of epilepsy. Precise diagnosis in known epileptic patients as a result of VEEG is more likely for those with focal interictal epileptifom discharges in routine EEG.