Research Paper: Mild Cognitive Impairment Using the Montreal Cognitive Assessment Instrument

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SCREENING for MILD COGNITIVE IMPAIRMENT USING MoCA

Geriatric Assessment

The Montreal Cognitive Assessment (MoCA) tool was recently developed as a screening tool for mild cognitive impairment (MCI) (Doerflinger, 2012). Until its introduction, gerontologists and neurologists relied on neuropsychological testing and standardized instruments to diagnose and evaluate a patient's cognitive state. This process was time-consuming, expensive, and left clinicians without a good, quick, and easy that could be used in the primary or urgent care setting. In addition, the Mini-Mental State Examination (MMSE), the gold standard screening tool for cognitive impairment, appears to be comparatively insensitive to the subtle cognitive changes that define MCI. For these reasons, the MoCA instrument was developed for clinical use.

MoCA is one page in length, can be completed in 10 minutes, and is administered in the clinic setting with the clinician providing verbal instructions (Nasreddine, 2010). There are eight domains that are evaluated by the 30-point test: (1) short-term memory recall, (2) visuospatial abilities, (3) executive functioning, (4) attention, (5) concentration, (6) working memory, (7) language, and (8) orientation to time. A person with normal cognition would obtain a score between 26 and 30, but if a patient is suffering from MCI they would be expected to score between 19 and 25.2 (Doerflinger, 2012).

Clinical Problem: MCI

MCI is generally considered to represent a transitional stage between normal cognitive functioning and dementia (Kremen et al., 2013). What is probably the most common definition of MCI is scoring 1.5 standard deviations below the population mean on at least one cognitive measure similar to those listed in the previous section. The possible outcomes include progression to dementia, cognitive stability, or reversion to normal cognitive functioning.

A more practical definition of MCI has been provided by the Alzheimer's Association (2012). Based on this definition, the line between MCI and dementia is that the former will not significantly impair a person's ability to manage self-care activities, while the latter does. MCI is also broken down into different classifications depending on the main cognitive deficits being experienced. A person would have amnestic MCI if their primary cognitive deficits involve atypical memory problems, such as remembering the content of a conversation that occurred recently. In contrast, a patient with nonamnestic MCI has trouble with their reasoning skills, including remaining aware of the passage of time, prioritizing and making decisions, and processing visual information.

The prevalence of MCI depends on which definition is used to define this condition (Kremen et al., 2013). Using what are probably the most common criteria, the prevalence of single and multiple domains MCI was estimated to be 30 and 50%, respectively, in a sample of Vietnam Era veterans between the ages of 51 and 59. As Kremen and colleagues (2013) point out, however, if MCI is a reliable predictor of dementia onset then the prevalence of dementia would predict MCI prevalence. According to the Alzheimer's Association (2013), 5.2 million Americans suffered from Alzheimer's disease in 2013. Of these, 5.0 million were over the age of 65. For Americans over the age of 71, an estimated 14% suffer from dementia. Based on these estimates, more than 5 million Americans are probably suffering from MCI because not everyone who develops MCI will progress to dementia. Detecting and quantifying MCI is important because several studies have revealed that acetylcholinesterase inhibitors can delay dementia onset for as much as 3 years (Doerflinger, 2012).

MCI can also be caused by strokes, other forms of vascular disease, and trauma (Cumming, Bernhardt & Linden, 2011). According to the U.S. Centers for Disease Control and Prevention (CDC, 2014), close to 800,000 Americans suffer a stroke each year. Stroke is also the fourth leading cause of death in the U.S. And a common cause of disability. Among these disabilities is cognitive impairment, which afflicts between 35 and 91% of stroke victims depending on the severity of ischemia (Toglia, Fitzgerald, O'Dell, Mastrogiovanni, & Lin, 2011). Unfortunately, cognitive impairment has been largely ignored in stroke intervention trials and the trials that have examined cognitive outcomes used instruments insensitive to subtle changes in executive function. There is thus a need for a clinical evaluation tool that can screen stroke victims for MCI.

Developing an easy and fast clinical instrument that can measure subtle changes in cognition would not only help researchers quantify stroke outcomes, but also help clinicians diagnose, follow, and provide appropriate treatment (Toglia et al., 2011). The potential benefits would include reduced patient disability and increased quality of life, in addition to informing best practice guidelines for stroke rehabilitation. As mentioned above, the MMSE is a widely used, quick and easy instrument that can evaluate a patient's level of cognitive functioning. For patients that have suffered severe cognitive impairment due to stroke, the MMSE is a valuable instrument; however, for stroke patients who have suffered mild cognitive impairment the MMSE is too insensitive to be clinically useful. For this reason, researchers interested in quantifying cognitive outcomes following stroke have become interested in the possible utility of MoCA (Toglia et al., 2011; Cumming et al., 2012).

MoCA Efficacy

Clinical Guidelines for Cognitive Impairment

Current clinical guidelines for evaluating cognitive function can be broken down into two steps: screening and monitoring (AHRQ, 2013). The recommended screening instruments include the MMSE, Mini-Cog, or Sweet 16, while information about onset, duration, and functional outcomes can be collected using the Informant Questionnaire on Cognitive Decline (IQCDE). The MMSE and Mini-Cog can be used to track a patient's progress as well. These instruments should be administered when the patient is admitted, discharged, transferred, giving consent, changing medications, and during initial provider visits, follow-ups, and inpatient care. More generally, a diagnosis of MCI will depend on a patient's medical history, neurological examination, loss of daily functioning, MMSE score, and the perceptions of close family members and friends (Alzheimer's Association, 2012). The MCI risk factors are similar to those for Alzheimer's disease, including age, genetic predisposition, and cardiovascular disease risk factors (e.g., obesity, diabetes, hypertension). Although MoCA is not currently best practice for evaluating a patient for MCI, the American Academy of Neurology had begun revising their recommendations in 2012 (Doerflinger, 2012).

Research Article 1

The obvious strategy for determining whether MoCA can measure subtle changes in cognitive performance is to directly compare scores with the scores obtained from MMSE. Stewart and colleagues (2012) did just that in a recent study that compared the MoCA, MMSE, and Saint Louis Mental Status Examination (SLUMS) scores among 40 individuals with documented cognitive impairment. The age range was 48 to 89, but the diversity of psychiatric diagnoses ranged from alcohol-induced dementia and mood/affective disorders to schizophrenia and dementia. Study participants were administered all three instruments by trained mental health clinicians. The MMSE cutoff score for dementia is 24 and all participants who obtained a score below this point also obtained clinically-significant scores on the other instruments. This represented two thirds of the participants and provides evidence of good agreement between all three instruments.

The findings of Stewart and colleagues (2012) become more interesting, however, when the scores were compared for those participants who obtained an MMSE score of 24 or above (N = 13). By comparison, only 1 of these participants achieved a score in the normal range on the MoCA instrument. The mean age of these individuals was 61.4 (SD = 9.7), with a mean academic achievement of 12.2 years (SD = 1.6). The SLUMS scores revealed six participants scoring in the MCI range and another six scoring in the dementia range. There was thus good agreement between MoCA and SLUMS. The relationship between the different instruments was analyzed using Pearson multiple correlation, two-tailed, and the coefficients obtained reveal strong agreement between all three instruments (MMSE vs. MoCA, r = .90, p < .001; MMSE vs. SLUMS, r = .83, p < .001; MoCA vs. SLUMS, r = .91, p < .001).

The order in which the instruments were administered was randomized to control for confounding factors related to repeat cognitive testing (Stewart et al., 2012). The main purpose of the study was to evaluate the level of agreement between the three instruments, thereby providing some indication of cross-validation and predictive power; however, more importantly the study evaluated whether the MoCA and SLUMS instruments appeared to be sensitive to more subtle gradations in cognitive impairment. Using the pyramid of evidence provided by Schmidt and Brown (2012) this study would fit within quasi-experimental designs due to the lack of randomization. This is a diagnostic accuracy study using a cross-sectional design (Aslam, Georgiev, Mehta, & Kumar, 2012).

Research Study 2

A similar study was conducted using mild stroke patients, but with a slightly larger sample (N = 72, Mage = 70±17) and more controls (Toglia et al., 2011). Stroke severity was evaluated using the National Institutes of Health Stroke Scale (NIHSS) and the MMSE, which were administered by psychiatrists. The MoCA was administered by occupational therapists and all instruments were administered within 48 hours of admission. In addition, the relevant domains within the Functional Independence Measure (FIM) were used… [END OF PREVIEW]

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