An Integrative Nomogram for Identifying Cognitive Impairment Using Seizure Type and Cerebral Small Vessel Disease Neuroimaging Markers in Patients with Late-Onset Epilepsy of Unknown Origin.

INTRODUCTION: Cognitive impairment (CI) is a common comorbidity in patients with late-onset epilepsy of unknown origin (LOEU). However, limited data are available on effective screening methods for CI at an early stage. We aimed to develop and internally validate a nomogram for identifying patients with LOEU at risk of CI and investigate the potential moderating effect of education on the relationship between periventricular white matter hyperintensities (PVHs) and cognitive function.

METHODS: We retrospectively reviewed the clinical data of 61 patients aged ≥ 55 years diagnosed with LOEU. The main outcome was CI, reflected as an adjusted Montreal Cognition Assessment score of < 26 points. A nomogram based on a multivariable logistic regression model was constructed. Its discriminative ability, calibration, and clinical applicability were tested using calibration plots, the area under the curve (AUC), and decision curves. Internal model validation was conducted using the bootstrap method. The moderating effect of education on the relationship between PVH and cognitive function was examined using hierarchical linear regression.

RESULTS: Forty-four of 61 (72.1%) patients had CI. A nomogram incorporating seizure type, total cerebral small vessel disease burden score, and PVH score was built to identify the risk factors for CI. The AUC of the model was 0.881 (95% confidence interval: 0.771-0.994) and 0.78 (95% confidence interval: 0.75-0.8) after internal validation. Higher educational levels blunted the negative impact of PVH on cognitive function.

CONCLUSION: Our nomogram provides a convenient tool for identifying patients with LOEU who are at risk of CI. Moreover, our findings demonstrate the importance of education for these patients.