Usefulness and yield of routine electroencephalogram: a retrospective study

BACKGROUND

The electroencephalogram (EEG) is a common diagnostic tool used to investigate patients for various indications including seizure disorders.

AIMS

To investigate factors that predict the presence of epileptiform abnormalities on EEG and review the common indications for ordering an EEG.

METHODS

We retrospectively reviewed all routine adult EEG performed in a hospital over a 6-month period. Data collated included patient demographics, clinical indication for EEG, setting in which EEG was performed, activation procedures utilised, history of epilepsy, and whether the patient was on antiepileptic medication. Our primary objective was to evaluate the factors that were predictive of an EEG with epileptiform abnormalities.

RESULTS

Two hundred and thirty-nine routine EEG were included with indications, including first seizure (25.9%), known epilepsy (25.1%), cognitive change (15.9%), syncope (15.0%), movement disorder (6.7%), psychogenic non-epileptic events (5.4%), unresponsiveness/intensive care unit (4.6%) and psychiatric presentation (1.3%). Most (48.1%) EEG were normal; 8.9% of the EEG demonstrated epileptiform abnormalities. Using multivariate logistic regression, three variables proved significant in predicting an EEG with epileptiform abnormalities. Any seizure as an indication (first seizure or seizure in known epileptic), increasing patient age, and EEG conducted in an inpatient setting and within 48 h of seizure event were all statistically more likely to yield epileptiform abnormalities on EEG.

CONCLUSIONS

Our findings suggest that careful selection of patients based on appropriate indications for EEG referral would likely improve the yield of an EEG. Depending on the indication, a normal EEG result can be of similar usefulness to an abnormal EEG demonstrating epileptiform abnormalities.

Assessment of small sensory fiber function in myotonic dystrophy type 1

BACKGROUND

Myotonic dystrophy type 1 (DM1) is a multisystem disorder affecting the peripheral nervous system. However, studies evaluating somatic small fiber sensory nerve function, which may contribute to pain in DM1, are lacking.

METHODS

Using quantitative sensory testing of the hand and foot, we evaluated Aδ and C-fiber function. Of 20 adult DM1 patients recruited, 16 were analyzed. Their results were compared with those of 32 age- and sex-matched controls.

RESULTS

No DM1 patient had diabetes mellitus or clinical evidence of small fiber neuropathy. In DM1, hand (P < .01) and foot (P = 0.02) warm detection thresholds were higher than those of controls. Cool detection thresholds were lower in the foot (P < .001).

CONCLUSIONS

Subclinical small sensory fiber dysfunction occurs in DM1 patients without large fiber neuropathy. Further research with other modalities is required to characterize these disturbances as disease modifying therapies are developed.