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Evaluating the Predictive Power of Cognitive Assessment Tools for Cortical Hypometabolism in Alzheimer’s Disease | ||
| Journal of Rehabilitation Sciences & Research | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 27 اسفند 1403 | ||
| نوع مقاله: Original Articles | ||
| شناسه دیجیتال (DOI): 10.30476/jrsr.2024.103367.1501 | ||
| نویسندگان | ||
| Mohammad Sadeghi1؛ Salimeh Jafari* 2؛ Hadi Aligholi3؛ Zahra Shayan4؛ Alireza Keshavarz Bahaqiqat5 | ||
| 1Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran | ||
| 2Department of Speech Therapy, School of Rehabilitation Sciences, Shiraz University of Medical Sciences, Shiraz, Iran | ||
| 3Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran | ||
| 4Department of Biostatistic, School of Medicine, Trauma Research Center,, Shiraz University of Medical Science | ||
| 5Psychology,Cognitive and Neuroscience research Center (cnrc), Tehran Medical Sciences, Islamic Azad University, Tehran, Iran | ||
| چکیده | ||
| Background: Alzheimer's disease (AD) is a serious progressive neurodegenerative disorder that is characterized by memory loss and cognitive performance decline. one of the theories to explain AD pathology is the emergence of abnormal hypometabolism. The current study aimed to investigate the association of cortical hypometabolism, and cognitive assessment tools in dementia spectrum. Methods: Our cross sectional/longitudinal study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including 1048 subjects with 291 cognitively normal (CN), 579 mild cognitive impairment (MCI), and 178 AD. The FDG-PET data (as an indicator for hypometabolism) and cognitive assessment scores including Alzheimer's Disease Assessment Scale (ADAS11 and ADAS13 subtests), Montreal Cognitive Assessment (MoCA), Everyday Cognition Scale (ECog), and Mini-Mental State Exam (MMSE) were gathered. ANOVA, multiple regression, ROC and AUC analyses were used to analyze data. Results: According to linear regression analysis, ADAS11, ADAS13, and MMSE predicted PET scores in the MCI group (p-values:0.002,0.002, 0.017), but MoCA predicted PET scores in the CN group (β=0.016, p=0.045). ADAS13 exhibited the greatest discriminative capacity (AUC=0.786), followed by ADAS11 (AUC=0.767), according to ROC analysis. Over time, PET scores declined significantly in all groups, with the AD group exhibiting the biggest fall. The PET scores of the CN and MCI groups were notably higher than those of the AD group at 24 months (p<0.001). Conclusion: The ADAS11 and ADAS13 tests could distinguish between normal and abnormal hypometabolism. Additionally, ADAS13 has the best discriminative ability, which is useful for clinicians and researchers for early detection and monitoring of the AD spectrum. | ||
| کلیدواژه‌ها | ||
| Alzheimer's disease؛ Mild Cognitive Impairment؛ Cortical hypometabolism؛ Cognitive assessment tools | ||
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آمار تعداد مشاهده مقاله: 145 |
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