Cognitive Impairment in MRI-Negative Epilepsy: Relationship between Neurophysiological and Neuropsychological Measures

Differentiations in Illness Duration, Thyroid-Stimulating Hormone, Glucose and P300 Latency Between Drug-Naïve Unipolar and Bipolar Depression: A Comparative Cross-Sectional Study

Background

Distinguishing bipolar depression (BD) from unipolar depression (UD) remains a major clinical challenge, especially in drug-naïve patients. The present study aimed to investigate whether demographic, clinical, and biochemical parameters can help differentiate drug-naïve BD from UD.

Methods

Drug-naïve patients with UD and BD were recruited from Shandong Mental Health Center. Ninety-four inpatients (61 UD and 33 BD) were assessed using the 17-item Hamilton Depression Rating Scale (HAMD-17) and P300 latency. Fasting serum levels of free triiodothyronine (FT3), free thyroxine (FT4), thyroid-stimulating hormone (TSH), as well as fasting plasma glucose (FPG), lipid, C-reactive protein (CRP), and uric acid (UA) indicators were measured.

Results

Patients with BD had longer illness duration and P300 latency and lower FT3 levels, but higher levels of TSH and FPG than patients with UD (all P<0.05). Binary logistic regression analysis indicated illness duration, TSH, FPG, and P300 latency were significantly associated with BD. Illness duration, TSH, FPG, and P300 latency achieved an area under the ROC curve of 0.777, 0.699, 0.646, and 0.635, respectively, in discriminating unipolar and bipolar depression.

Conclusion

Increased illness duration, serum TSH and FPG levels, and P300 latency were independent risk factors for BD. Demographic, clinical, biochemical, and electrophysiological markers identified may have the potential to distinguish BD from UD.

Association between cognitive impairment and antiseizure medication adherence among people with epilepsy in Addis Ababa, Ethiopia

BACKGROUND

Cognitive impairment is one of the most common and most troublesome comorbidities among people with epilepsy (PWE). Adherent use of antiseizure medications (ASM) can control seizure episodes in 70% of the cases. However, the relationship between adherent use of ASMs and cognitive impairment in epilepsy is complex.

OBJECTIVE

To assess the association between adherence to ASMs and cognitive status among PWE.

METHODS

We performed a cross-sectional observational study with prospective data collection from PWE using translated and content-validated Amharic versions of the Montreal cognitive assessment tool (MOCA-B) and a four-item Morisky Medication Adherence Scale (Morski-4). Ordinal logistic regression analysis was performed to evaluate the potential risk factors for cognitive impairment, including ASM adherence, physical exercise, and level of education.

RESULTS

A total of 214 individuals with epilepsy were included in this study; 53.7 % were female, and the mean age was 34 years ± 12. The mean age at seizure occurrence was 19 years ± 9. The most common epilepsy type among participants was generalized epilepsy (69 %). The prevalence of poor medication adherence to ASM was 54.2 %. The prevalence of mild cognitive impairment was 65.4 %, and 18.2 % had moderate cognitive impairment, particularly affecting verbal fluency (60.8 %) and memory (43.9 %). Cognitive impairment was significantly associated with poor ASM adherence (AOR = 12.0, 95 %CI, (1.53, 93.75), lower level of physical exercise (AOR = 16.30, 95 %CI (1.24, 214.99), and poor educational attainment with both no formal education (AOR = 0.04, 95 %CI (0.02, 0.14)) and primary or secondary level education (AOR = 0.32, 95 %CI, (0.15, 0.70).

CONCLUSIONS

There is a high rate of cognitive impairment and non-adherence to ASMs in PWE living in Addis Ababa, Ethiopia. Poor ASM adherence is a possible risk factor for cognitive impairment. PWE can benefit from interventions to improve ASM adherence, physical exercise, and better educational attainment.