We aim to prospectively investigate, in a large and heterogeneous population, the electroencephalogram (EEG)-reading performances of EEG technologists. A total of 8 EEG
technologists and 5 certifed neurophysiologists independently analyzed 20-min EEG recordings. Interrater agreement (IRA) for predefned EEG pattern identifcation between EEG technologists and neurophysiologits was assessed using percentage of agreement (PA) andGwet-AC1. Among 1528 EEG recordings, the PA [95% confdence interval] and interrater agreement (IRA, AC1) values were as follows: status epilepticus (SE) and seizures, 97% [96–98%], AC1 kappa = 0.97; interictal epileptiform discharges, 78% [76–80%], AC1 = 0.63; and conclusion dichotomized as “normal” versus “pathological”, 83.6% [82–86%], AC1 = 0.71. EEG technologists identifed SE and seizures with 99% [98–99%] negative predictive value, whereas the positive predictive values (PPVs) were 48% [34–62%] and 35% [20–53%], respectively. The PPV for normal EEGs was 72% [68–76%]. SE and seizure detection were impaired in poorly cooperating patients (SE and seizures; p< 0.001), intubated and older patients (SE; p< 0.001), and confrmed epilepsy patients (seizures; p= 0.004). EEG technologists identifed ictal features with few false negatives but high false positives, and identifed normal EEGs with good PPV. The absence of ictal features reported by EEG technologists can be reassuring; however, EEG traces should be reviewed by neurophysiologists before taking action.