The Role of Serial Follow-up and Sleep Deprivation Methods in Improving Electroencephalography Diagnostic Yield in a Cohort of Omanis Aged 13 Years and Above: A Clinical Audit Study.

The aim of this audit study was to establish the utility of follow-up and sleep-deprived electroencephalography testing to improve the detection of interictal abnormalities in a tertiary referral center in Oman. As part of our ongoing auditing process, a total of 3010 EEGs were included in this study. All EEGs were routinely performed for Omanis aged 13 years and above, who were referred for possible diagnosis of seizure disorders. Each EEG was performed over an average period of 20-30 minutes. Of the 3010 EEGs, there were 553 follow-up and sleep-deprived EEGs, including initial baseline EEG studies which were analyzed for this study. The total progressive yield of serial follow-up EEGs to detect overall EEG changes was 53.5%, distributed as 8.8%, 11.4%, 0%, and 33.3% for the second, third, fourth, and fifth serial EEG studies, respectively. For the sleep deprivation EEG group, the yield was 6.5% for detecting overall EEG changes compared to the initial EEG studies. A limitation in this study was the small sample size in the subsequent follow-up and sleep deprivation EEGs. In conclusion, we found a minimal contribution of serial follow-up and sleep deprivation methods in improving the EEG abnormality detection in our study. National guidelines and an increase in awareness among physicians are required to increase the benefit of these well-established, yet not optimally utilized EEG methods.

The Usefulness of Nap Sleep Recording During Routine Electroencephalography: An Audit Study.

OBJECTIVES: A measure to increase the electroencephalogram (EEG) outcome includes a short period of nap sleep during a routine standard EEG with the aim of increasing its sensitivity to interictal abnormalities or provoking seizures. As part of an ongoing auditing of our EEG data, we aimed to investigate the contribution of nap sleep during routine outpatient department based EEGs requested for a variety of reasons. METHODS: EEG data at the Department of Clinical Physiology at Sultan Qaboos University Hospital, Oman, from July 2006 to December 2007 and from January 2009 to December 2010 (total 42 months) were reviewed. The EEGs were for patients older than 13-years referred for possible epilepsy, blackouts, headache, head trauma, and other non-specified attacks. The recording period was between 20 to 40 minutes. Abnormalities were identified during waking and nap sleep periods. RESULTS: A total of 2 547 EEGs were reviewed and 744 were abnormal (29.2%). Of those abnormal EEGs, nap sleep was obtained in 258 (34.7%) EEGs, and 39 (15.1%) showed abnormalities during nap sleep. Nineteen out of the 39 (48.7%) EEGs were abnormal during awake and nap sleep; and 20 (51.3%) were abnormal during nap sleep, which represented only 2.7% of the total abnormal EEGs (n = 744). CONCLUSIONS: The contribution of the short nap sleep to the pickup rate of interictal abnormalities in EEG was minimal. We recommend the EEG service to include one cycle of spontaneous sleep EEG directed at patients with a history suggestive of epilepsy if their awake EEGs are normal.

The Correlation between Electroencephalography Amplitude and Interictal Abnormalities: Audit study.

OBJECTIVES: The aim of this study was to establish the relationship between background amplitude and interictal abnormalities in routine electroencephalography (EEG). METHODS: This retrospective audit was conducted between July 2006 and December 2009 at the Department of Clinical Physiology at Sultan Qaboos University Hospital (SQUH) in Muscat, Oman. A total of 1,718 electroencephalograms (EEGs) were reviewed. All EEGs were from patients who had been referred due to epilepsy, syncope or headaches. EEGs were divided into four groups based on their amplitude: group one ≤20 µV; group two 21-35 µV; group three 36-50 µV, and group four >50 µV. Interictal abnormalities were defined as epileptiform discharges with or without associated slow waves. Abnormalities were identified during periods of resting, hyperventilation and photic stimulation in each group. RESULTS: The mean age ± standard deviation of the patients was 27 ± 12.5 years. Of the 1,718 EEGs, 542 (31.5%) were abnormal. Interictal abnormalities increased with amplitude in all four categories and demonstrated a significant association (P <0.05). A total of 56 EEGs (3.3%) had amplitudes that were ≤20 µV and none of these showed interictal epileptiform abnormalities. CONCLUSION: EEG amplitude is an important factor in determining the presence of interictal epileptiform abnormalities in routine EEGs. This should be taken into account when investigating patients for epilepsy. A strong argument is made for considering long-term EEG monitoring in order to identify unexplained seizures which may be secondary to epilepsy. It is recommended that all tertiary institutions provide EEG telemetry services.