Clinical and Radiological Parameters Affecting the Yield of Routine Electroencephalography in Various Indications.

Area of Science:

• Neurology
• Clinical Neurophysiology

Background:

• Electroencephalography (EEG) is a crucial diagnostic tool in neurology.
• Optimizing EEG referral selection can improve diagnostic yield and resource allocation.

Purpose of the Study:

• To identify clinical and radiological parameters associated with specific EEG patterns.
• To prioritize EEG referrals based on predictive factors.

Main Methods:

• Retrospective analysis of EEG and medical records for 604 patients.
• Statistical analysis to establish associations between parameters and EEG yield.

Main Results:

• Altered level of consciousness, abnormal neurological exams, and neuroimaging findings significantly predicted abnormal EEG patterns.
• Specific seizure types, epilepsy history, and conditions like status epilepticus and cardiac arrest were associated with abnormal EEG findings.
• Epileptiform activity and encephalopathy on EEG correlated with various clinical indicators.

Conclusions:

• Patient's level of consciousness, neurological examination, and neuroimaging are key predictors of EEG results.
• A meticulous neurological assessment and judicious patient selection enhance the utility of routine EEG.
• This study underscores the importance of informed EEG referral practices.