Application Value of Serum Metabolic Markers for Cognitive Prediction in Elderly Epilepsy

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Abstract

Background and Study Aims: Elderly epilepsy is the third most common chronic disease that affects metabolism either alone or through antiepileptic drugs (AEDs). Here, we focus on whether neurocognitive profiles in elderly epilepsy and its treatment are linked to metabolic conditions. Patients and Methods: Elderly patients with epilepsy without cognitive impairment (n = 78) and with cognitive impairment (n = 75) were enrolled. C-reactive protein (CRP) and metabolic markers (triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL-c), low-density lipoprotein (LDL-c), albumin, fasting glucose (Glu) and glycosylated hemoglobin (HbA1c)) were measured. Serum markers were modeled using logistic regression analysis. Results: TG, TC, fasting glucose, HbA1c and CRP were significantly increased (p < 0.05, 0.05, 0.001, 0.001, 0.01, respectively) in elderly epilepsy, whereas HDL-c, LDL-c and serum albumin were decreased (p < 0.001, 0.001, 0.001) in elderly epilepsy. TG, TC, fasting Glu, HbA1c and CRP were significantly elevated (p < 0.05, 0.001, 0.001, 0.001, 0.001, respectively) in epilepsy with cognitive impairment, whereas HDL-c, LDL-c and serum albumin were decreased (p < 0.001, 0.001, 0.001). The abnormal glycolipid profile was predominated in AED-treated patients. The regression model combined with TG, LDL-c, HDL-c and albumin performed better (area under the ROC curve was 0.824) in AED-treated patients. Conclusion: The relevant relationship between glycolipid profile and cognitive impairment with epilepsy was described, and the logistic regression model based on serum TG, LDL-c, HDL-c and albumin is reported and may serve as promising diagnostic markers for elderly epilepsy with cognitive impairment. Additionally, a specific emphasis on the complex role of altered lipid metabolism and AEDs is made.

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Wei, H., Liu, D., Geng, L., Liu, Y., Wang, H., & Yan, F. (2022). Application Value of Serum Metabolic Markers for Cognitive Prediction in Elderly Epilepsy. Neuropsychiatric Disease and Treatment, 18, 2133–2140. https://doi.org/10.2147/NDT.S371751

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