The Clock Drawing Test – a simple pencil and paper test – has been used for more than 50 years as a screening tool to differentiate normal individuals from those with cognitive impairment, and has proven useful in helping to diagnose cognitive dysfunction associated with neurological disorders such as Alzheimer’s disease, Parkinson’s disease, and other dementias and conditions. We have been administering the test using a digitizing ballpoint pen that reports its position with considerable spatial and temporal precision, making available far more detailed data about the subject’s performance. Using pen stroke data from these drawings categorized by our software, we designed and computed a large collection of features, then explored the tradeoffs in performance and interpretability in classifiers built using a number of different subsets of these features and a variety of different machine learning techniques. We used traditional machine learning methods to build prediction models that achieve high accuracy. We operationalized widely used manual scoring systems so that we could use them as benchmarks for our models. We worked with clinicians to define guidelines for model interpretability, and constructed sparse linear models and rule lists designed to be as easy to use as scoring systems currently used by clinicians, but more accurate. While our models will require additional testing for validation, they offer the possibility of substantial improvement in detecting cognitive impairment earlier than currently possible, a development with considerable potential impact in practice.

In a previous article we described a 10-point scoring system (i.e., scale 1) to grade clock drawings to command and copy with hands set for "ten after 11" among demented patients. Alzheimer's subjects (AD) improved from the command to copy conditions, whereas subjects with ischaemic vascular dementia (IVD) did not. To investigate the underlying cognitive deficits responsible for this profile, an additional scale was developed (scale 2) that tallied errors in graphomotor functioning, hand/number placement, and executive control. On an independent sample of subjects, AD subjects, again, made significant improvement on scale 1 from the command to copy condition, whereas no such improvement occurred among the IVD subjects. On scale 2, IVD subjects made more graphomotor errors in the command condition, and more executive control and more total errors in the copy conditions than AD subjects. A number of positive correlations were noted between tests of language and memory on scale 1. By contrast, scores on tests of executive control declined as scale 2 errors increased. In addition, a principal component analysis indicated that scale 2 test performance loaded on a factor with other tests related to executive control. These results suggest that impairment in frontal systems functioning may explain why IVD subjects do not improve from the command to copy conditions on scale 1. Such a pattern of performance in clock drawing may also be helpful in making a differential diagnosis between AD and IVD.

Clock drawing has recently been shown to lie useful in differentiating Alzieimer's disease patients from normal controls. Our procedure for clock drawing differed from other published reports in that a copy condition was employed and patients were asked to set clock hands to read "ten after eleven". We found both clock drawing procedures to be correlated with tests related to executive and visuospatial functioning. In both conditions, nondemented controls performed significantly better than demented patients. In the command condition there was no difference between Alzheimer patients and patients with cerebrovascular dementia. In the copy condition, patients with cerebrovascular dementia performed significantly worse than Alzheimer patients. The inclusion of a copy condition appears to greatly expand the utility of this test. Although our scoring system did not differentiate between various dementing disorders in the command condition, if clock drawing is used as a screening instrument, lack of improvement in the copy condition in comparison to the command condition may be a sign of a vascular involvement.

No abstract

Alzheimer's disease (AD) and vascular dementia (VaD) are the two most common types of dementia. Although the combination of these disorders, called 'mixed' dementia, is recognized, the prevailing clinical and research perspective continues to consider AD and VaD as independent disorders. A review of recent neuropathological and neuropsychological literature reveals that these two disorders frequently co-occur and so-called 'pure' AD or VaD is comparatively rare. In addition, recent research shows that vascular dysfunction not only potentiates AD pathology, but that pathological changes in AD may subsequently induce vascular disorders. On the basis of these data, we propose that the neurobiological underpinnings underlying AD/VaD dementia and their neuropsychological phenotypes are best understood as existing along a clinical/pathological continuum or spectrum. We further propose that in conjunction with current diagnostic criteria, statistical modeling techniques using neuropsychological test performance should be leveraged to construct a system to classify AD/VaD spectrum dementia in order to test hypotheses regarding how mechanisms related to AD and VaD pathology interact and influence each other.