Authors :
Fawzi Babtain, MBBS, MHSc, FRCPC, SCSN (EEG, EMG) – King Faisal Specialist Hospital aand Research Center- Jeddah; Tasneem Banjar, MD – Epilepsy Fellow, King Faisal Specialist Hospital and Research Centre-Jeddah; Danya Attiya, MD – Epilepsy Fellow, King Faisal Specialist Hospital and Research Centre-Jeddah; Saleh Baeesa, MBBS, FRCS – Epilepsy Surgeon, King Faisal Specialist Hospital and Research Centre-Jeddah; Youssef Alsaid, MBBS, FRCPC – Epileptologist, King Faisal Specialist Hospital and Research Centre-Jeddah
Rationale: The impact of the timing of last seizure (TTLS) prior to admission to epilepsy monitoring unit (EMU) on epilepsy classification is unclear for which, we conducted this study._x000D_
Methods: We reviewed patients with epilepsy admitted to EMU between January 2021 and April 2022. We determined the last seizure before EMU admission. We considered EMU yield as; confirmed the pre-admission classification, added a new knowledge to the hypothesis, or failed to confirm epilepsy classification._x000D_
Results: We studied 156 patients. There were 72 (46%) men, with the mean age of 30 years (Table 1 showed patients’ demographics). TTLS was divided according to one- or three-months cutoff. We confirmed the pre-EMU epilepsy classification in 52 (33%) patients, learned new findings on epilepsy classification in 80 (51%) patients, and failed to classify epilepsy in 24 (15%) patients. The odds of confirming the epilepsy classification were more than two times in patients with TTLS within a month before admission to EMU compared to those with TTLS of more thana month (OR=2.4, p value = 0.04; 95% CI, 1.1-5.9). Similar findings when 3 months TTLS cutoff was considered (OR= 6.2, p value = 0.002; 95% CI, 1.6-40.2). Confirming epilepsy classification was also significantly associated with earlier seizures recorded, and subsequently shorter hospital stay in EMU (Figure 1). We did not observe similar findings when we added or failed to add a new epilepsy classification.
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Table 1. Patient’s characteristics, according to last seizure recorded prior to EMU_x000D_
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| _x000D_
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Last seizure within a month_x000D_
(N=111)_x000D_
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Last seizure more than a month_x000D_
(N=45)_x000D_
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P value_x000D_
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Men (%)_x000D_
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53 (48 %)_x000D_
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19 (42 %)_x000D_
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0.8_x000D_
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Age (mean)_x000D_
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29.5 years_x000D_
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30 years_x000D_
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0.7_x000D_
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Age at disease onset (mean)_x000D_
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16 years_x000D_
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17 years_x000D_
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0.7_x000D_
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Disease duration (mean)_x000D_
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13 years_x000D_
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14 years_x000D_
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0.9_x000D_
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Presence of epilepsy risk factors (%)_x000D_
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49 (44 %)_x000D_
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17 (38 %)_x000D_
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0.5_x000D_
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No. of ASMs[1] (median)_x000D_
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2 (IQR=1- 4)_x000D_
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2 (IQR=1- 5)_x000D_
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0.7_x000D_
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Brain MRI_x000D_
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Normal (%)_x000D_
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39 (35%)_x000D_
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24 (53%)_x000D_
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0.04_x000D_
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MTS_x000D_
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22 (20%)_x000D_
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11 (24%)_x000D_
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0.5_x000D_
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MCD_x000D_
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17 (15%)_x000D_
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4 (9%)_x000D_
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0.2_x000D_
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Other pathologies_x000D_
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33 (30%)_x000D_
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6 (13%)_x000D_
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0.05_x000D_
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Baseline EEG_x000D_
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Normal or no IEDs[2]_x000D_
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21 (19%)_x000D_
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4 (9%)_x000D_
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0.2_x000D_
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Focal IEDs_x000D_
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78 (70%)_x000D_
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38 (84%)_x000D_
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0.07_x000D_
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Multifocal IEDs_x000D_
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8 (7%)_x000D_
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2 (4%)_x000D_
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0.5_x000D_
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Generalized IEDs_x000D_
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4 (4%)_x000D_
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1 (2%)_x000D_
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0.6_x000D_
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Epilepsy classification_x000D_
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TLE_x000D_
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35 (32%)_x000D_
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11 (24%)_x000D_
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0.2_x000D_
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FLE_x000D_
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36 (32%)_x000D_
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13 (29%)_x000D_
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0.8_x000D_
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Other epilepsy_x000D_
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29 (26%)_x000D_
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14 (31%)_x000D_
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0.5_x000D_
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Undetermined_x000D_
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11 (9%)_x000D_
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7 (16%)_x000D_
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0.3_x000D_
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Number of seizures (mean)_x000D_
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5 (1 - 60)_x000D_
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2.5 (1 - 9)_x000D_
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0.02_x000D_
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Length of hospital stay (mean)_x000D_
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3 (1 - 7.5)_x000D_
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3.5 (1 - 6.5)_x000D_
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0.06_x000D_
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[1] ASMs: Anti-seizure medications_x000D_
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[2] IEDs: Interictal epileptic discharges_x000D_
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Conclusions: The timing of last seizure prior to EMU admission enhanced the confirmation of epilepsy classifications, and shortened EMU stay. Such findings can improve the utilization of EMU in the presurgical evaluation of patients with epilepsy._x000D_
Funding: None