BMC neurology · 2022
Limits on using the clock drawing test as a measure to evaluate patients with neurological disorders.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Heyrani Raheleh, Sarabi-Jamab Atiye, Grafman Jordan, Asadi Nesa, Soltani Sarvenaz, Mirfazeli Fatemeh Sadat, Almasi-Dooghaei Mostafa, Shariat Seyed Vahid, Jahanbakhshi Amin, Khoeini Tara, Joghataei Mohammad Taghi
Аннотация
BACKGROUND: The Clock Drawing Test (CDT) is used as a quick-to-conduct test for the diagnosis of dementia and a screening tool for cognitive impairments in neurological disorders. However, the association between the pattern of CDT impairments and the location of brain lesions has been controversial. We examined whether there is an association between the CDT scores and the location of brain lesions using the two available scoring systems.
METHOD: One hundred five patients with brain lesions identified by CT scanning were recruited for this study. The Montreal Cognitive Assessment (MoCA) battery including the CDT were administered to all partcipants. To score the CDT, we used a qualitative scoring system devised by Rouleau et al. (1992). For the quantitative scoring system, we adapted the algorithm method used by Mendes-Santos et al. (2015) based on an earlier study by Sunderland et al. (1989). For analyses, a machine learning algorithm was used.
RESULTS: Remarkably, 30% of the patients were not detected by the CDT. Quantitative and qualitative errors were categorized into different clusters. The classification algorithm did not differentiate the patients with traumatic brain injury 'TBI' from non-TBI, or the laterality of the lesion. In addition, the classification accuracy for identifying patients with specific lobe lesions was low, except for the parietal lobe with an accuracy of 63%.
CONCLUSION: The CDT is not an accurate tool for detecting focal brain lesions. While the CDT still is beneficial for use with patients suspected of having a neurodegenerative disorder, it should be cautiously used with patients with focal neurological disorders.
METHOD: One hundred five patients with brain lesions identified by CT scanning were recruited for this study. The Montreal Cognitive Assessment (MoCA) battery including the CDT were administered to all partcipants. To score the CDT, we used a qualitative scoring system devised by Rouleau et al. (1992). For the quantitative scoring system, we adapted the algorithm method used by Mendes-Santos et al. (2015) based on an earlier study by Sunderland et al. (1989). For analyses, a machine learning algorithm was used.
RESULTS: Remarkably, 30% of the patients were not detected by the CDT. Quantitative and qualitative errors were categorized into different clusters. The classification algorithm did not differentiate the patients with traumatic brain injury 'TBI' from non-TBI, or the laterality of the lesion. In addition, the classification accuracy for identifying patients with specific lobe lesions was low, except for the parietal lobe with an accuracy of 63%.
CONCLUSION: The CDT is not an accurate tool for detecting focal brain lesions. While the CDT still is beneficial for use with patients suspected of having a neurodegenerative disorder, it should be cautiously used with patients with focal neurological disorders.