Brain atrophy and clinical characteristics predicting SDMT performance in multiple sclerosis: A 10-year follow-up study

Objectives To identify Magnetic Resonance Imaging (MRI), clinical and demographic biomarkers predictive of worsening information processing speed (IPS) as measured by Symbol Digit Modalities Test (SDMT). Methods Demographic, clinical data and 1.5 T MRI scans were collected in 76 patients at time of inclusion, and after 5 and 10 years. Global and tissue-specific volumes were calculated at each time point. For the primary outcome of analysis, SDMT was used. Results Worsening SDMT at 5-year follow-up was predicted by baseline age, Expanded Disability Status Scale (EDSS), SDMT, whole brain volume (WBV) and T2 lesion volume (LV), explaining 30.2% of the variance of SDMT. At 10-year follow-up, age, EDSS, grey matter volume (GMV) and T1 LV explained 39.4% of the variance of SDMT change. Conclusion This longitudinal study shows that baseline MRI-markers, demographic and clinical data can help predict worsening IPS. Identification of patients at risk of IPS decline is of importance as follow-up, treatment and rehabilitation can be optimized.publishedVersio

Speech and pause characteristics in multiple sclerosis: A preliminary study of speakers with high and low neuropsychological test performance

This preliminary study investigated how cognitive-linguistic status in multiple sclerosis (MS) is reflected in two speech tasks (i.e. oral reading, narrative) that differ in cognitive-linguistic demand. Twenty individuals with MS were selected to comprise High and Low performance groups based on clinical tests of executive function and information processing speed and efficiency. Ten healthy controls were included for comparison. Speech samples were audio-recorded and measures of global speech timing were obtained. Results indicated predicted differences in global speech timing (i.e. speech rate and pause characteristics) for speech tasks differing in cognitive-linguistic demand, but the magnitude of these task-related differences was similar for all speaker groups. Findings suggest that assumptions concerning the cognitive-linguistic demands of reading aloud as compared to spontaneous speech may need to be re-considered for individuals with cognitive impairment. Qualitative trends suggest that additional studies investigating the association between cognitive-linguistic and speech motor variables in MS are warranted. © 2013 Informa UK Ltd

Influence of cognitive function on speech and articulation rate in multiple sclerosis

We examined cognitive predictors of speech and articulation rate in 50 individuals with multiple sclerosis (MS) and 23 healthy controls. We measured speech and articulation rate from audio-recordings of participants reading aloud and talking extemporaneously on a topic of their choice (i.e., self-generated speech). Articulation rate was calculated for each speech sample by removing lexically irrelevant vocalizations and pauses of \u3e200 ms. Speech rate was similarly calculated including pauses. Concurrently, the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) battery, as well as standardized tests of sentence intelligibility and syllable repetition were administered. Analysis of variance showed that MS patients were slower on three of the four rate measures. Greater variance in rate measures was accounted for by cognitive variables for the MS group than controls. An information processing speed composite, as measured by the Symbol Digit Modalities Test (SDMT) and the Paced Auditory Serial Addition Test (PASAT), was the strongest predictor among cognitive tests. A composite of memory tests related to self-generated speech, above and beyond information processing speed, but not to oral reading. Self-generated speech, in this study, was not found to relate more strongly to cognitive tests than simple reading. Implications for further research are discussed. © 2012 INS. Published by Cambridge University Press

Impact of Cognitive Impairment and Dysarthria on Spoken Language in Multiple Sclerosis

Objective: To investigate the impact of cognitive impairment on spoken language produced by speakers with multiple sclerosis (MS) with and without dysarthria. Method: Sixty speakers comprised operationally defined groups. Speakers produced a spontaneous speech sample to obtain speech timing measures of speech rate, articulation rate, and silent pause frequency and duration. Twenty listeners judged the overall perceptual severity of the samples using a visual analog scale that ranged from no impairment to severe impairment (speech severity). A 2 × 2 factorial design examined main and interaction effects of dysarthria and cognitive impairment on speech timing measures and speech severity in individuals with MS. Each speaker group with MS was further compared to a healthy control group. Exploratory regression analyses examined relationships between cognitive and biopsychosocial variables and speech timing measures and perceptual judgments of speech severity, for speakers with MS. Results: Speech timing was significantly slower for speakers with dysarthria compared to speakers with MS without dysarthria. Silent pause durations also significantly differed for speakers with both dysarthria and cognitive impairment compared to MS speakers without either impairment. Significant interactions between dysarthria and cognitive factors revealed comorbid dysarthria and cognitive impairment contributed to slowed speech rates in MS, whereas dysarthria alone impacted perceptual judgments of speech severity. Speech severity was strongly related to pause duration. Conclusions: The findings suggest the nature in which dysarthria and cognitive symptoms manifest in objective, acoustic measures of speech timing and perceptual judgments of severity is complex

Brain atrophy and clinical characteristics predicting SDMT performance in multiple sclerosis: A 10-year follow-up study

Objectives To identify Magnetic Resonance Imaging (MRI), clinical and demographic biomarkers predictive of worsening information processing speed (IPS) as measured by Symbol Digit Modalities Test (SDMT). Methods Demographic, clinical data and 1.5 T MRI scans were collected in 76 patients at time of inclusion, and after 5 and 10 years. Global and tissue-specific volumes were calculated at each time point. For the primary outcome of analysis, SDMT was used. Results Worsening SDMT at 5-year follow-up was predicted by baseline age, Expanded Disability Status Scale (EDSS), SDMT, whole brain volume (WBV) and T2 lesion volume (LV), explaining 30.2% of the variance of SDMT. At 10-year follow-up, age, EDSS, grey matter volume (GMV) and T1 LV explained 39.4% of the variance of SDMT change. Conclusion This longitudinal study shows that baseline MRI-markers, demographic and clinical data can help predict worsening IPS. Identification of patients at risk of IPS decline is of importance as follow-up, treatment and rehabilitation can be optimized