Data from: Acute single channel EEG predictors of cognitive function after stroke

Background: Early and accurate identification of factors that predict
post-stroke cognitive outcome is important to set realistic targets for
rehabilitation and to guide patients and their families accordingly.
However, behavioral measures of cognition are difficult to obtain in the
acute phase of recovery due to clinical factors (e.g. fatigue) and
functional barriers (e.g. language deficits). The aim of the current study
was to test whether single channel wireless EEG data obtained acutely
following stroke could predict longer-term cognitive function. Methods:
Resting state Relative Power (RP) of delta, theta, alpha, beta,
delta/alpha ratio (DAR), and delta/theta ratio (DTR) were obtained from a
single electrode over FP1 in 24 participants within 72 hours of a
first-ever stroke. The Montreal Cognitive Assessment (MoCA) was
administered at 90-days post-stroke. Correlation and regression analyses
were completed to identify relationships between 90-day cognitive function
and electrophysiological data, neurological status, and demographic
characteristics at admission. Results: Four acute qEEG indices
demonstrated moderate to high correlations with 90-day MoCA scores: DTR (r
= -0.57, p = 0.01), RP theta (r = 0.50, p = 0.01), RP delta (r = -0.47, p
= 0.02), and DAR (r = -0.45, p = 0.03). Acute DTR (b = -0.36, p <
0.05) and stroke severity on admission (b = -0.63, p < 0.01) were
the best linear combination of predictors of MoCA scores 90-days
post-stroke, accounting for 75% of variance. Conclusions: Data generated
by a single pre-frontal electrode support the prognostic value of acute
DAR, and identify DTR as a potential marker of post-stroke cognitive
outcome. Use of single channel recording in an acute clinical setting may
provide an efficient and valid predictor of cognitive function after
stroke.