Exploring the relationship between manual dexterity and cognition in people with multiple sclerosis: 9-hole peg and multiple cognitive functions.

AIM AND RATIONALE: Problems with manual dexterity and cognition impact the everyday performance of people with multiple sclerosis (PwMS). Accumulated findings point to the relationship between deficits in manual dexterity and auditory domains of cognition with a lack of evidence on visuospatial and verbal aspects of cognitive functioning. Therefore, this study explores the relationship between manual dexterity and cognition in a cohort of PwMS. METHOD: This cross-sectional study collected data from 63 PwMS aged 22 to 55 through a convenient sampling method. Participants were diagnosed with relapsing-remitting multiple sclerosis (RRMS). Cognition was measured using a multi-domain computerized cognitive testing, NeuroTrax, and manual dexterity was measured using a 9-hole peg assessment. Spearman correlation was used to identify the correlation among cognition subtests as well as with manual dexterity. Linear regression analysis was also conducted to identify whether manual dexterity predicts cognitive functioning. RESULTS: A significant negative correlation was found between 9-hole peg scores and global cognitive scores (GCS), r = -0.34, p = 006. The manual dexterity scores were also shown to predict GCS, R2= 0.165, p = 0.001. CONCLUSION: Manual dexterity was found to not only predict cognitive dysfunction but was also associated with multiple cognitive domains. Understanding the relationship between manual dexterity and cognition and the inferred progression of deficits can assist clinicians to provide interventions at earlier stages of disease progression to potentially increase daily functioning and quality of life (QoL).

Cognitive impairment in people with multiple sclerosis: Perception vs. performance - factors that drive perception of impairment differ for patients and clinicians.

BACKGROUND: Neurologists' perceptions of the presence of cognitive impairment (CI) in people with multiple sclerosis (PwMS) may not always align with findings of objective cognitive assessment. The accuracy of self-reported CI in PwMS can also be highly variable across individuals, and may not align with objective measurement of cognitive disturbances. Research suggests that additional factors impact perceived cognitive ability, such as depression and fatigue. Objective cognitive screening regardless of patient or neurologist perception has been recommended but still is often limited in routine care. Moreover, comprehensive neuropsychological assessment is even less routinely done. OBJECTIVE: To explore how neurologists' perceptions of PwMS' CI compare to the perception of the patient by determining whether PwMS and their clinicians are accurate in detecting the presence and degree of CI as defined by a multi-domain validated computerized test battery in PwMS, as well as investigate what factors influence perception of CI in each group. METHODS: PwMS completed a computerized multi-domain cognitive testing battery, and self-reported measures of disease impact (MSIS-29), fatigue (MFIS), and depression (BDI-II). Disability was assessed by the clinician using the Expanded Disability Status Scale (EDSS). Clinicians and patients also provided an estimation of cognitive deficits along a Likert scale. RESULTS: In this cohort of PwMS (N=202, age range: 20 to 88, gender: 71% female), their level of accuracy in detecting attention deficits (k = -.028, p = .010) was low but statistically significant. In contrast, clinicians' accuracy in detecting global CI (k = -.037, p < .001) and a number of specific domain deficits was moderate. Fatigue (p < .001) and cognitive performance (p = .012) significantly predicted patient perceived cognitive deficits. Clinician perceived cognitive performance was significantly predicted by multiple factors: cognitive scores (p < .001), physical disability (p = .011), age (p = .021), and depression (p = .038). CONCLUSION: The need to objectively screen for CI in PwMS, regardless of perception, can be aided by a better understanding of the agreement and discrepancies between the patient and clinician regarding perceived cognitive disturbances and the presence of CI defined by a multi-dimensional objective screening battery.

Multiple sclerosis and quality of life: The role of cognitive impairment on quality of life in people with multiple sclerosis.

BACKGROUND: Multiple Sclerosis (MS), a chronic disease of the central nervous system (CNS), affects functional ability and quality of life (QoL). Depression, fatigue, and disability status are among the many factors that have been shown to impact QoL in people with MS, but the extent to which MS-related cognitive impairment is related to QoL is understudied in the literature. OBJECTIVE: The purpose of this study was to determine relevant predictors of QoL from a wide list of symptoms including physical disability, and a multi-dimensional computerized cognitive assessment battery (CAB), depression, fatigue, and demographic variables (including employment status). In addition, the unique predictive power of cognitive impairment on QoL was explored in relation to other common factors of disease impact. METHODS: 171 people with MS (PwMS) were evaluated with a computerized assessment battery (CAB), EDSS examination, and validated Patient Reported Outcome (PRO) measures (Multiple Sclerosis Impact Scale, MSIS-29; Beck Depression Inventory - Second Edition BDI-2; and the Modified Fatigue Impact Scale, MFIS). RESULTS: 171 PwMS were included [Age: 46.02 years ± 9.85, 124 (72.5%) female]. Depression and fatigue scores were highly correlated with MSIS-29. EDSS, unemployment, memory, executive functioning, and motor skills were moderately correlated with MSIS-29. Predictors of QoL were EDSS, depression, fatigue, executive functioning, and attention. Attention and executive functioning were predictive of QoL even after controlling for demographic variables, fatigue, depression, and physical disability status. CONCLUSION: Findings indicate the need for comprehensive and quantified evaluation of all factors associated with disease burden, which will ultimately serve to improve the QoL in PwMS through more targeted and patient-centered care.