{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T19:32:27Z","timestamp":1786649547341,"version":"build-2736575974"},"reference-count":29,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"1","license":[{"start":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T00:00:00Z","timestamp":1729641600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,1]]},"abstract":"\n Objectives:<\/jats:title>\n To highlight the significance of various clinical and radiological parameters in association with specific electroencephalographic (EEG) patterns in order to prioritize EEG referrals.<\/jats:p>\n <\/jats:sec>\n \n Method:<\/jats:title>\n This retrospective, cross-sectional study was conducted in the neurology department of King Fahad University Hospital, Alkhobar, and involved a review and analysis of EEG and medical records pertaining to 604 patients referred for routine EEG. The data were analyzed using SPSS version 22. An association between various parameters and EEG yield was established.<\/jats:p>\n <\/jats:sec>\n \n Results:<\/jats:title>\n \n Factors associated with the yield of abnormal EEG patterns were diverse, like generalized tonic-clonic seizures (GTCs) (\n P<\/jats:italic>\n =.05), status epilepticus (SE) (\n P<\/jats:italic>\n =.05), altered level of consciousness (ALC) (\n P<\/jats:italic>\n =.00), abnormal movement (\n P<\/jats:italic>\n =.00), cardiac arrest (\n P<\/jats:italic>\n =.00), prior history of epilepsy (\n P<\/jats:italic>\n =.04), chronic renal disease (CRD) (\n P<\/jats:italic>\n =.03), abnormal neurological exam (\n P<\/jats:italic>\n =.00), and cortical lesions on brain imaging (\n P<\/jats:italic>\n =.00). Among the abnormal EEG patterns, epileptiform activity (EA) in EEG was associated with focal seizures (\n P<\/jats:italic>\n =.03), GTCs (\n P<\/jats:italic>\n =.00), falls (\n P<\/jats:italic>\n =.05), cardiac arrest (\n P<\/jats:italic>\n =.00), a history of epilepsy (\n P<\/jats:italic>\n =.00), and hypoxic ischemic injury (\n P<\/jats:italic>\n =.03). Encephalopathy in EEG was also associated with focal sz (\n P<\/jats:italic>\n =.02), GTCs (\n P<\/jats:italic>\n =.00), SE (\n P<\/jats:italic>\n =.01), ALC (\n P<\/jats:italic>\n =.00), cardiac arrest (\n P<\/jats:italic>\n =.00), history of stroke (\n P<\/jats:italic>\n =.01), and epilepsy (\n P<\/jats:italic>\n =.00).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion:<\/jats:title>\n Among the studied parameters, patient level of consciousness, neurological exam findings, and neuroimaging findings, with some discrepancies, were found to be the most consistent in predicting the EEG yield. The study demonstrated the value of a proper neurological exam and careful selection of patients to gain the optimum benefit from the routine EEG.<\/jats:p>\n <\/jats:sec>","DOI":"10.4103\/aam.aam_73_23","type":"journal-article","created":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T06:00:14Z","timestamp":1729663214000},"page":"37-44","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Clinical and Radiological Parameters Affecting the Yield of Routine Electroencephalography in Various Indications"],"prefix":"10.4103","volume":"24","author":[{"given":"Rizwana","family":"Shahid","sequence":"first","affiliation":[{"name":"Department of Neurology, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Azra","family":"Zafar","sequence":"additional","affiliation":[{"name":"Department of Neurology, College of Medicine, 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