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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Validation of a modified Chinese version of Mini‐Addenbrooke's Cognitive Examination for detecting mild cognitive impairment Pan, Feng‐Feng; Cui, Liang; Li, Qing‐Jie; Guo, Qi‐Hao In: Brain Behav (2021) Abstract: BACKGROUND: For detecting mild cognitive impairment (MCI), brief cognitive screening tools are increasingly required for the advantage of time saving and no need for special equipment or trained raters. We aimed to develop a modified Chinese version of Mini‐Addenbrooke's Cognitive Examination (C‐MACE) and further evaluate its validation in detecting MCI. METHODS: A total of 716 individuals aged from 50 to 90 years old were recruited, including 431 cognitively normal controls (NC) and 285 individuals with MCI. The effect size of Cramer's V was used to explore which items in the Chinese version of Addenbrooke's Cognitive Examination‐III (ACE‐III‐CV) best associated with MCI and to form the C‐MACE. Receiver operating characteristic (ROC) analyses were carried out to explore the ability of C‐MACE, ACE‐III‐CV, Chinese version of Montreal Cognitive Assessment‐Basic (MoCA‐BC), and Mini‐Mental State Examination (MMSE) in discriminating MCI from NC. RESULTS: Five items with greatest effect sizes of Cramer's V were selected from ACE‐III‐CV to form the C‐MACE: Memory Immediate Recall, Memory Delayed Recall, Memory Recognition, Verbal Fluency Animal and Language Naming. With a total score of 38, the C‐MACE had a satisfactory classification accuracy in detecting MCI (area under the ROC curve, AUC = 0.892), superior to MMSE (AUC = 0.782) and comparable to ACE‐III‐CV (AUC = 0.901) and MoCA‐BC (AUC = 0.916). In the subgroup of Age > 70 years, Education ≤ 12 years, the C‐MACE got a highest classification accuracy (AUC = 0.958) for detecting MCI. CONCLUSION: In the Chinese‐speaking population, C‐MACE derived from ACE‐III‐CV may identify MCI with a good classification accuracy, especially in aged people with low education. Keyword: Original Articles URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785624/ http://www.ncbi.nlm.nih.gov/pubmed/34843170 https://doi.org/10.1002/brb3.2418 BASE Hide details 2 Changes in local brain function in mild cognitive impairment due to semantic dementia Cui, Liang; Chen, Keliang; Huang, Lin... In: CNS Neurosci Ther (2021) BASE Show details

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