Introduction: Seizures are a common complication of intracerebral hemorrhage (ICH), with most occurring within 24 hours of stroke onset, and stroke is a common cause of seizures in the elderly population. Post-stroke seizures are associated with an increased risk of poor outcomes (Tanaka et al., 2024). American Heart Association guidelines suggest monitoring with electroencephalography (EEG), particularly in comatose patients (Greenberg et al. 2022). However prompt EEG monitoring is difficult to obtain in emergency department (ED) settings. Gururangan et al. (2025) proposed the introduction of a point-of-care (POC) EEG system into the stroke-code workflow to enhance differential diagnosis and to monitor for seizures in high-risk patients. Description: A 92-year-old male with past history of atrial fibrillation on rivaroxaban, pacemaker placement, hypertension and peripheral neuropathy presented to the ED with acute onset altered mental status, expressive aphasia, and right-side weakness, prompting stroke code activation in the ED. On arrival, GCS score was 10 and NIHSS score was 12. Initial CT revealed a left parietal ICH without midline shift. The patient was given anti-inhibitor coagulant complex to reverse anticoagulant activity. POC EEG monitoring was initiated in the ED, and the device’s artificial intelligence (AI) algorithm alerted the team to suspected continuous seizure activity, for which the patient was loaded with levetiracetam and lacosamide. The patient was intubated and admitted to the intensive care unit (ICU). Subsequent imaging did not show any worsening bleeding, and no further seizure activity was captured on POC or follow-up conventional EEG, though intermittent lateralized periodic discharges were still seen. He was extubated within two days, transferred to the floor after three days in the ICU, and discharged to a skilled nursing facility for further rehabilitation. Discussion: Although guidelines acknowledge seizures as a common risk in patients with ICH, post-stroke evaluation often lacks EEG monitoring. In our case, AI-enabled POC EEG monitoring facilitated the early detection of ongoing nonconvulsive seizures without hindering stroke protocols, highlighting the impact of incorporating these tools into stroke code workflow.
Kozak et al. (Sun,) studied this question.