Duve, K.; Petakh, P.; Oksenych, V.; Kamyshnyi, O. Predicting Cognitive Impairment in Patients with Chronic Traumatic Encephalopathy: A Single-Center Prospective Cohort Study. Preprints2024, 2024041646. https://doi.org/10.20944/preprints202404.1646.v1
APA Style
Duve, K., Petakh, P., Oksenych, V., & Kamyshnyi, O. (2024). Predicting Cognitive Impairment in Patients with Chronic Traumatic Encephalopathy: A Single-Center Prospective Cohort Study. Preprints. https://doi.org/10.20944/preprints202404.1646.v1
Chicago/Turabian Style
Duve, K., Valentyn Oksenych and Oleksandr Kamyshnyi. 2024 "Predicting Cognitive Impairment in Patients with Chronic Traumatic Encephalopathy: A Single-Center Prospective Cohort Study" Preprints. https://doi.org/10.20944/preprints202404.1646.v1
Abstract
Chronic traumatic encephalopathy (CTE) is a neurodegenerative condition caused by repeated traumatic brain injuries (TBIs) leading to cognitive, behavioral, and motor dysfunctions. This study examined the relationship between cognitive impairment and clinical syndromes among 145 CTE patients aged 18 to 75 years who underwent inpatient treatment at the Ternopil Regional Clinical Psychoneurological Hospital between 2021 and 2022. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), with results classified into four categories: normal, mild impairment, moderate impairment, and dementia. Statistical analysis revealed significant associations between cognitive impairment and specific neuroimaging changes, including ventricular dilatation. Clinical syndromes, such as cognitive disorder syndrome, also showed significant associations with cognitive impairment (p < 0.001). Using logistic regression, we developed a predictive model to estimate the probability of cognitive impairment based on various clinical features, including memory loss, attention deficits, and sleep disturbances. The model demonstrated high accuracy, with a receiver operating characteristic (ROC) curve showing a sensitivity of 91.0% and a specificity of 92.5%, yielding an area under the curve (AUC) of 0.964 (95% CI: 0.934 - 0.994). These findings suggest that specific neuroimaging and clinical features can predict cognitive impairment in CTE patients.
Medicine and Pharmacology, Neuroscience and Neurology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
