Diagnostic yield of electroencephalography in a general inpatient population

Clinical Outcomes and Systemic Complications Related to the Severity and Etiology of Status Epilepticus Using a Common Data Model

BACKGROUND

Status epilepticus (SE) is a critical neurological emergency in patients with neurological and nonneurological diseases. Mortality rises with SE severity. However, whether brain injury or systemic organ dysfunction causes death after SE remains unclear. We studied clinical outcomes and systemic dysfunctions associated with SE using standardized data from the common data model. This model includes clinical evaluations and treatments that provide real-world evidence for standard practice.

METHODS

This retrospective cohort study used the common data model database of a single tertiary academic medical center. Patients diagnosed with SE (corresponding to G41 of the International Classification of Diseases 10 and administration of antiseizure medication) between January 1, 2001, and January 1, 2018, were enrolled. Demographics, classifications of SE severity, and outcomes were collected as operational definitions by using a common data model format. Systemic complications were defined based on the Sequential Organ Failure Assessment criteria.

RESULTS

The electronic medical records of 1,825,196 patients were transformed into a common data model, and 410 patients were enrolled. The proportion of patients classified as having nonrefractory SE was 65.4% (268/410), followed by refractory (28.5%, 117/410) and super-refractory SE (6.1%, 25/410). Patients with more severe SE had longer intensive care unit and hospital stays. Renal dysfunction and thrombocytopenia were higher in the in-hospital death group (P = 0.002 and 0.003, respectively). In multivariable analysis, the Acute Physiology and Chronic Health Evaluation II score and platelet count were significantly different in the in-hospital death group (odds ratio, 1.169, P = 0.004; and 0.989, P = 0.043).

CONCLUSIONS

Systemic complications after SE, especially low platelet counts, were linked to worse outcomes and increased mortality in a common data model. The common data model offers expandability and comprehensive analysis, making it a potentially valuable tool for SE research.

Clinical factors associated with the yield of routine outpatient scalp electroencephalograms: A retrospective analysis from a tertiary hospital

The routine outpatient electroencephalogram (EEG) is most often used in the diagnosis and classification of epilepsy. The diagnostic yield of outpatient EEGs is low and the clinical factors contributing to the EEG outcome have not been well established. In this study, we sought to determine the yield and the factors predicting the EEG outcome. We retrospectively analyzed 1092 routine adult EEGs that were performed in a tertiary referral center over a period of 1year. Patient demographics, sources of referral, and indications for EEG were recorded. The majority of the referrals were from neurologists (54.7%), followed by the emergency department (15.4%). The indications for requesting an EEG included patients with a provisional or established diagnosis of epilepsy (56.3%), first seizure (10.7%), and seizure mimickers (29.1%). The majority (66.7%) of the EEGs were normal, whereas 13.2% demonstrated epileptiform discharges. At the time of recording, epileptic seizures occurred in 0.6% of the cases. With logistic regression analysis, three factors were found to be significantly associated with an abnormal (epileptiform) EEG: no antiepileptic drug therapy, the age of the patient, and indication for EEG (pre-test provisional diagnosis). Patients who are not on antiepileptic drug therapy and with a diagnosis of epilepsy or seizures are more likely to have epileptiform abnormalities in EEGs. Our findings suggest that careful selection of patients is likely to improve the diagnostic yield and cost-effectiveness of routine outpatient EEG.