Highlights
- •Determining a correct diagnosis in individuals with suspected epilepsy is challenging, if seizures and epileptic discharges are not recorded
- •Our aim was to assess whether the percentage of REM sleep (REM%) could discriminate between individuals with epilepsy and with differential diagnoses
- •We performed a retrospective, monocentric study with 128 individuals admitted to the EMU for diagnostic purposes
- •We found that REM% was significantly lower in individuals with the diagnosis of epilepsy and had a good predictive performance
- •Reduced REM% could be a supplementary biomarker for epilepsy in challenging diagnostic settings
Abstract
Objective
Establishing the diagnosis of epilepsy can be challenging if interictal epileptic
discharges (IEDs) or seizures are undetectable. Many individuals with epilepsy experience
sleep disturbances. A reduced percentage of REM sleep (REM%) has been observed following
seizures. We aimed to assess differences of REM% in individuals with epilepsy in comparison
with differential diagnoses.
Methods
We performed a retrospective, monocentric, two-armed case-control study with 128 age-matched
individuals who underwent ≥72 hours of continuous video-EEG monitoring at our epilepsy
monitoring unit (EMU) for diagnostic evaluation. We assessed REM% on the first and
last night of EMU admission. Logistic regressions models were used to evaluate the
predictive value of REM%.
Results
We included 64 individuals diagnosed with epilepsy and 64 with a differential diagnosis.
REM% in the epilepsy group was significantly lower [12.2% (±4.7) vs. 17.2% (±5.2),
p<0.001]. We found no significant influence of sex, age, anti-seizure, or other medications.
A REM%-based and an IED and seizure-based regression model were not significantly
different [area under the curve (AUC) 0.791 (95% confidence interval (CI): 0.713-0.870)
vs. 0.853 (95% CI: 0.788-0.919), p=0.23]. A combined model, based on IEDs, seizures,
and REM%, was superior to the IED model alone [0.933 (0.891-0.975), p<0.01].
Interpretation
Our study shows significantly reduced REM% in individuals with epilepsy. REM%-based
models show a good predictive performance. REM% assessment could improve diagnostic
accuracy – especially for challenging cases, e.g., when IEDs or seizures are absent
and patient history and semiology appear ambiguous. REM% as a biomarker should be
evaluated in prospective, multicentric trials.
Keywords
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Article info
Publication history
Published online: April 01, 2022
Accepted:
March 30,
2022
Received in revised form:
March 15,
2022
Received:
February 11,
2022
Identification
Copyright
© 2022 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
