scholarly journals The Reliability and Validity of Clock Drawing Test as a Screening Tool for Cognitive Impairment in Clients after Cerebrovascular Accident

2012 ◽  
Vol 13 (10) ◽  
pp. 4612-4618
Author(s):  
Sang-Heon Lee
Keyword(s):  
Cognitive Impairment ◽  
Cerebrovascular Accident ◽  
Screening Tool ◽  
Reliability And Validity ◽  
Clock Drawing Test ◽  
Clock Drawing ◽  
Drawing Test

Is the Clock Drawing Test a screening tool for the diagnosis of mild cognitive impairment? A systematic review

2009 ◽  
Vol 22 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Lena Ehreke ◽  
Melanie Luppa ◽  
Hans-Helmut König ◽  
Steffi G. Riedel-Heller
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Literature Search ◽  
Screening Tool ◽  
Cognitive Screening ◽  
Clock Drawing Test ◽  
Clock Drawing ◽  
Drawing Test ◽  
Diagnosis Of Dementia ◽  
Mean Differences

ABSTRACTBackground:The clock drawing test (CDT) is a common and widely used cognitive screening instrument for the diagnosis of dementia. However, it has remained unclear whether it is a suitable method to identify mild cognitive impairment (MCI). The aim of this paper is to review systematically the studies concerning the utility of the CDT in diagnosing MCI.Method:A systematic literature search was conducted. All studies dealing with utility of CDT in diagnosing MCI regardless of the applied CDT scoring system and MCI concept were selected.Results:Nine relevant studies were identified. The majority of the studies compared average CDT scores of cognitively healthy and mildly impaired subjects, and four of them identified significant mean differences. If reported, sensitivity and specificity have been mostly unsatisfactory.Conclusion:CDT should not be used for MCI-screening.

The clock drawing test as a screening tool in mild cognitive impairment and very mild dementia: a new brief method of scoring and normative data in the elderly

2016 ◽  
Vol 37 (6) ◽  
pp. 867-873 ◽  
Author(s):  
Monica Ricci ◽  
Martina Pigliautile ◽  
Valeria D’Ambrosio ◽  
Sara Ercolani ◽  
Cinzia Bianchini ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Normative Data ◽  
Screening Tool ◽  
The Elderly ◽  
Mild Dementia ◽  
Clock Drawing Test ◽  
Clock Drawing ◽  
Drawing Test

scholarly journals Use of the Freund Clock Drawing Test within the Mini-Cog as a screening tool for cognitive impairment in elderly patients with or without cancer

2013 ◽  
Vol 4 (2) ◽  
pp. 174-182 ◽  
Author(s):  
Lore Ketelaars ◽  
Lies Pottel ◽  
Michelle Lycke ◽  
Laurence Goethals ◽  
Véronique Ghekiere ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Elderly Patients ◽  
Screening Tool ◽  
Clock Drawing Test ◽  
Clock Drawing ◽  
Drawing Test

scholarly journals An AI-assisted Online Tool for Cognitive Impairment Detection Using Images from the Clock Drawing Test

2021 ◽  
Author(s):  
Samad Amini ◽  
Lifu Zhang ◽  
Boran Hao ◽  
Aman Gupta ◽  
Mengting Song ◽  
...  
Keyword(s):  
Deep Learning ◽  
Cognitive Impairment ◽  
Screening Tool ◽  
Learning Algorithm ◽  
Cost Effective ◽  
Clock Drawing Test ◽  
Clock Drawing ◽  
Deep Learning Algorithm ◽  
Drawing Test ◽  
Deployable Mechanism

AbstractBackgroundWidespread early dementia detection could drastically increase clinical trial candidates and enable early interventions. Since the Clock Drawing Test (CDT) can be potentially used for diagnosing dementia related diseases, it can be leveraged to devise a computer-aided screening tool.ObjectiveThis work aims to develop an online screening tool by leveraging Artificial Intelligence and the CDT.MethodsImages of an analog clock drawn by 3, 263 cognitively intact and 160 impaired subjects were used. First, we processed the images from the CDT by a deep learning algorithm to obtain dementia scores. Then, individuals were classified as belonging to either category by combining CDT image scores with the participant’s age.ResultsWe have evaluated the performance of the developed models by applying 5-fold cross validation on 20% of the dataset. The deep learning model generates dementia scores for the CDT images with an Area Under the ROC Curve (AUC) of 81.3% ± 4.3%. A composite logistic regression model using age and the generated dementia scores, yielded an average AUC and average weighted F1 score of 92% ± 0.8% and 94.4% ± 0.7%, respectively.DiscussionCDT images were subjected to distortion consistent with an image drawn on paper and photographed by a cell phone. The model offers a cost-effective and easily deployable mechanism for detecting cognitive impairment online, without the need to visit a clinic.

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