An objective score to identify psychogenic seizures based on age of onset and history

Abstract

Objective: Psychogenic nonepileptic seizure (PNES) is a common diagnosis after evaluation of medication resistant or atypical seizures with video-electroencephalographic monitoring (VEM), but usually follows a long delay after the development of seizures, during which patients are treated for epilepsy. Therefore, more readily available diagnostic tools are needed for earlier identification of patients at risk for PNES. A tool based on patient-reported psychosocial history would be especially beneficial because it could be implemented in the outpatient clinic.

Methods: Based on the data from 1375 patients with VEM-confirmed diagnoses, we used logistic regression to compare the frequency of specific patient-reported historical events, demographic information, age of onset, and delay from first seizure until VEM in five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of this information to differentiate PNES only from ES only, we used multivariate piecewise-linear logistic regression trained using retrospective data from chart review and validated based on data from 246 prospective standardized interviews.

Results: The prospective area under the curve of our weighted multivariate piecewise-linear by-sex score was 73%, with the threshold that maximized overall retrospective accuracy resulting in a prospective sensitivity of 74% (95% CI: 70-79%) and prospective specificity of 71% (95% CI: 64-82%). The linear model and piecewise linear without an interaction term for sex had very similar performance statistics. In the multivariate piecewise-linear sex-split predictive model, the significant factors positively associated with ES were history of febrile seizures, current employment or active student status, history of traumatic brain injury (TBI), and longer delay from first seizure until VEM. The significant factors associated with PNES were female sex, older age of onset, mild TBI, and significant stressful events with sexual abuse, in particular, increasing the likelihood of PNES. Delays longer than 20years, age of onset after 31years for men, and age of onset after 40years for women had no additional effect on the likelihood of PNES.

Discussion: Our promising results suggest that an objective score has the potential to serve as an early outpatient screening tool to identify patients with greater likelihood of PNES when considered in combination with other factors. In addition, our analysis suggests that sexual abuse, more than other psychological stressors including physical abuse, is more associated with PNES. There was a trend of increasing frequency of PNES for women during childbearing years and plateauing outside those years that was not observed in men.

Keywords: Diagnostic score; Dissociative seizures; Logistic regression; Multiple imputation.

Figure 1

The frequency of PNES as compared to ES with respect to patient-reported age of onset and delay from seizure onset to presentation. Error bars reflect exact binomial standard error. Data Gaussian smoothed with full-width half-max of 2.4 years for delay and 5 years for age of onset. A) Age of onset split by patient sex. B) Delay.

Figure 2

Performance statistics of our retrospectively trained model applied to our prospective dataset. 2A) Binary summary statistics of the performance of our piecewise by-sex model and other naïve models. Exact values for performance of all models is summarized in Supplemental Table 2. Error bars reflect standard error. Abbreviations: predictive value (PV). 2B) Receiver-operating curve for the prediction combined across imputed datasets. Our predicted model shown in black whereas the performance on permuted datasets shown in gray.

Figure 3

Individual-level predictive model trained on the retrospective dataset. Color reflects direction of effect. A) Odds ratios of all significant factors (permutation tests, $\widehat{p}$<0.05). Gray reflects 95% empirical confidence intervals of chance. The “+” indicates that the effect of concussion and sexual abuse are in addition to the effect of TBI and psychological stressors, respectively. See Supplemental Table 3 for an exact summary of all models. B) Translation of log-odds ratios to a rounded score for implementation. The sum of all components should be compared to the overall threshold of 7. Arrows reflect conditional statements, for example a male patient with an age of onset of 20 years, should add +4 to his score. Abbreviations: per decade (/d).