Cognitive dysfunction in patients with clinically isolated syndromes or newly diagnosed multiple sclerosis

2007 ◽  
Vol 13 (8) ◽  
pp. 1004-1010 ◽  
Author(s):  
BI Glanz ◽  
CM Holland ◽  
SA Gauthier ◽  
EL Amunwa ◽  
Z. Liptak ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Disease Severity ◽  
Cognitive Dysfunction ◽  
Grey Matter Volume ◽  
Lesion Volume ◽  
Disease Course ◽  
Newly Diagnosed ◽  
Matter Volume ◽  
Clinically Isolated Syndromes

Cognitive dysfunction is common in patients with multiple sclerosis (MS), and has been associated with MRI measures of lesion burden and atrophy. Little is known about the prevalence of cognitive impairment in patients with early MS. The associations between cognitive impairment and MRI measures of disease severity early in the disease course are also unclear. This study used a brief battery of cognitive tests to determine the prevalence and pattern of cognitive impairment in patients with clinically isolated syndromes or newly diagnosed MS. The associations between cognitive impairment and MRI measures of disease severity early in the disease course were also examined. Ninety-two patients with clinically isolated syndromes or the diagnosis of MS within the last 3 years participating in the CLIMB study underwent a neurologic examination, neuropsychological evaluation and MRI at 1.5T. Forty-nine percent of patients were impaired on one or more cognitive measures. There were no significant correlations between cognitive scores and MRI measures of disease severity including total T2 lesion volume, normal appearing white matter volume, grey matter volume, and brain parenchymal fraction. These findings suggest that cognitive impairment may predate the appearance of gross structural abnormalities on MRI and serve as an early marker of disease activity in MS. Multiple Sclerosis 2007; 13: 1004—1010. http://msj.sagepub.com

scholarly journals Cognitive trajectories in multiple sclerosis: a long-term follow-up study

2021 ◽  
Author(s):  
Antonio Carotenuto ◽  
Teresa Costabile ◽  
Giuseppe Pontillo ◽  
Moccia Moccia ◽  
Fabrizia Falco ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Cognitive Rehabilitation ◽  
Trajectory Analysis ◽  
Disease Onset ◽  
Disease Diagnosis ◽  
Cognitive Status ◽  
Grey Matter Volume ◽  
Disease Course

Abstract Background Cognitive impairment occurs in multiple sclerosis (MS) and undergoes a progressive worsening over disease course. However, clinicians still struggle to predict the course of cognitive function. To evaluate baseline clinical and imaging predictors of cognitive abilities worsening over time, we performed a latent trajectory analysis for cognitive performances in MS patients, up to 15 years from disease onset. Methods We collected age, sex, education, dominant and non-dominant 9-hole peg test (9HP) and timed 25-foot walk (T25-FW) as well as MRI measures (grey matter volume and lesion load) within 6 months from disease diagnosis for relapsing–remitting MS (RR-MS) patients. At diagnosis and over the follow-up, we also assessed cognitive status through the symbol digit modalities test (SDMT). Cognitive impairment was defined by applying age-, gender- and education-adjusted normative values. Group-based trajectory analysis was performed to determine trajectories, and the predictive value of clinical and imaging variables at baseline was assessed through multinomial logistic regression. Results We included 148 RR-MS (98 females and 50 males). Over 11 ± 4 year follow-up, 51.4% remained cognitively stable whereas 48.6% cognitively worsened. Cognitively worsening patients had a higher T25FW time (p = 0.004) and a reduced hippocampal volume at baseline (p = 0.04). Conclusion Physical disability as well as hippocampal atrophy might depict patients at risk of cognitive worsening over the disease course. Therefore, using such predictors, clinicians may select patients to carefully evaluate for cognitive impairment as to eventually introduce cognitive rehabilitation treatments.

Grey matter volume in a large cohort of MS patients: relation to MRI parameters and disability

2011 ◽  
Vol 17 (9) ◽  
pp. 1098-1106 ◽  
Author(s):  
Stefan D Roosendaal ◽  
Kerstin Bendfeldt ◽  
Hugo Vrenken ◽  
Chris H Polman ◽  
Stefan Borgwardt ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
White Matter ◽  
Physical Disability ◽  
Grey Matter ◽  
Grey Matter Volume ◽  
Lesion Volume ◽  
White Matter Volume ◽  
Matter Volume ◽  
Secondary Progressive ◽  
Relapsing Remitting

Background: Although grey matter damage in multiple sclerosis is currently recognized, determinants of grey matter volume and its relationship with disability are not yet clear. Objectives: The objectives of the study were to measure grey and white matter volumes across different disease phenotypes; identify MRI parameters associated with grey matter volume; and study grey and white matter volume as explanatory variables for clinical impairment. Methods: This is a cross-sectional study in which MRI data of 95 clinically isolated syndrome, 657 relapsing–remitting, 125 secondary-progressive and 50 primary-progressive multiple sclerosis patients from three centres were acquired. Grey and white matter volumes were determined, together with T2 and T1 lesion volumes. Physical disability was assessed with the Expanded Disability Status Scale, cognitive impairment with the Paced Auditory Serial Addition Task. Data were analysed using multiple regression. Results: Grey matter volume was lower in relapsing–remitting patients (mean [SD]: 0.80 [0.05] L) than in clinically isolated syndrome patients (0.82 [0.05] L), and even greater relative atrophy was found in secondary-progressive patients (0.77 [0.05] L). In contrast, white matter volume in secondary-progressive patients was comparable to that in relapsing–remitting patients. Grey matter volume was the strongest independent predictor of physical disability and cognitive impairment, and was associated with both T2 and T1 lesion volume. Conclusions: Our findings show that grey matter volume is lower in secondary-progressive than in relapsing–remitting disease. Grey matter volume explained physical and cognitive impairment better than white matter volume, and is itself associated with T2 and T1 lesion volume.

scholarly journals Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia

2021 ◽  
pp. jnnp-2020-323541
Author(s):  
Jessica L Panman ◽  
Vikram Venkatraghavan ◽  
Emma L van der Ende ◽  
Rebecca M E Steketee ◽  
Lize C Jiskoot ◽  
...  
Keyword(s):  
White Matter ◽  
Frontotemporal Dementia ◽  
Disease Severity ◽  
Grey Matter ◽  
Clinical Stage ◽  
Data Driven ◽  
Grey Matter Volume ◽  
Matter Volume ◽  
Mutation Carriers ◽  
Individual Disease

ObjectiveProgranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way.MethodsWe included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.ResultsLanguage functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.ConclusionDegeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage.

Cognitive impairment predicts conversion to multiple sclerosis in clinically isolated syndromes

2009 ◽  
Vol 16 (1) ◽  
pp. 62-67 ◽  
Author(s):  
Valentina Zipoli ◽  
Benedetta Goretti ◽  
Bahia Hakiki ◽  
Gianfranco Siracusa ◽  
Sandro Sorbi ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Prognostic Value ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Clinically Isolated Syndromes ◽  
Kaplan Meier ◽  
Sizable Proportion ◽  
One Year ◽  
Therapeutic Decision Making

Significant cognitive impairment has been found in 20—30% of patients with clinically isolated syndromes suggestive of multiple sclerosis. In this study we aimed to assess the prognostic value of the presence of cognitive impairment for the conversion to multiple sclerosis in patients with clinically isolated syndromes. All patients with clinically isolated syndromes consecutively referred to our centre since 2002 and who had been followed-up for at least one year underwent cognitive assessment through the Rao’s Battery and the Stroop test. Possible predictors of conversion to clinically definite multiple sclerosis were evaluated through the Kaplan Meier curves and Cox regression analysis. A total of 56 patients (41 women; age 33.2 ± 8.5 years; expanded disability scale score 1.2 ± 0.7) were recruited. At baseline, 32 patients (57%) fulfilled McDonald’s criteria for dissemination in space. During the follow-up (3.5 ± 2.3 years), 26 patients (46%) converted to a diagnosis of multiple sclerosis. In particular, 64% of patients failing ≥ 2 tests and 88% of patients failing ≥ 3 tests converted to multiple sclerosis. In the Cox regression model, the failure of at least three tests (HR 3.3; 95% CI 1.4—8.1; p = 0.003) and the presence of McDonald’s dissemination in space at baseline (HR 3.8; 95% CI 1.5—9.7; p = 0.005), were found to be predictors for conversion to multiple sclerosis. We conclude that cognitive impairment is detectable in a sizable proportion of patients with clinically isolated syndromes. In these subjects cognitive impairment has a prognostic value in predicting conversion to multiple sclerosis and may therefore play a role in therapeutic decision making.

scholarly journals Evaluation of the effects of group psychotherapy on cognitive function in patients with multiple sclerosis with cognitive dysfunction and depression

2015 ◽  
Vol 73 (2) ◽  
pp. 90-95 ◽  
Author(s):  
Emine Bilgi ◽  
Hasan Hüseyin Özdemir ◽  
Ayhan Bingol ◽  
Serpil Bulut
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Cognitive Function ◽  
Group Psychotherapy ◽  
Cognitive Dysfunction ◽  
Beck Depression Inventory ◽  
Neuropsychological Tests ◽  
Depression Severity ◽  
Group Members ◽  
Repeatable Battery

Objective This study will evaluate how decreasing depression severity via group psychotherapy affects the cognitive function of patients with multiple sclerosis (MS) who are also diagnosed with depression and cognitive dysfunction. Method MS patients completed the Brief Repeatable Battery of Neuropsychological Tests and Beck Depression Inventory (BDI). The group members diagnosed with depression and cognitive dysfunction underwent group psychotherapy for 3 months. Upon completion of psychotherapy, both tests were readministered. Results Depression and cognitive dysfunction were comorbid in 15 (13.9%) of patients. Although improvement was detected at the end of the 3-month group psychotherapy intervention, it was limited to the BDI and the Paced Auditory Test. Conclusion Group psychotherapy might decrease cognitive impairment in MS patients.

scholarly journals Short Report: Prevalence of Cognitive Impairment in Newly Diagnosed Relapsing-Remitting Multiple Sclerosis

2018 ◽  
Vol 20 (4) ◽  
pp. 153-157 ◽  
Author(s):  
Giulia DiGiuseppe ◽  
Mervin Blair ◽  
Sarah A. Morrow
Keyword(s):  
Multiple Sclerosis ◽  
Cognitive Impairment ◽  
Processing Speed ◽  
Clinical Population ◽  
Clinical Event ◽  
Routine Practice ◽  
Short Report ◽  
Newly Diagnosed ◽  
Mood Symptoms ◽  
Relapsing Remitting

Abstract Background: Cognitive impairment is common in multiple sclerosis (MS) and can manifest early in the disease process, sometimes as early as the first demyelinating event. However, the frequency of cognitive impairment in a newly diagnosed MS population has not been evaluated comprehensively in a clinical population. We sought to examine the prevalence of cognitive impairment in relapsing-remitting MS (RRMS) within a year of diagnosis in a clinic where cognitive testing at diagnosis is part of routine practice. Methods: A retrospective medical record review of persons with RRMS assessed in a cognitive MS clinic identified 107 patients assessed by the Minimal Assessment of Cognitive Function in Multiple Sclerosis battery within 1 year of a confirmed RRMS diagnosis. Results: The cohort was predominantly female (n = 82 [76.6%]) and white (n = 93 [86.9%]). Only 36 patients (33.6%) were diagnosed as having RRMS based on a second clinical event. Processing speed was the most frequently impaired domain (n = 38 [35.5%]). Only 37 patients (34.6%) were within normal limits on all cognitive domains. Regarding mood symptoms, 25 patients (23.4%) were positive for depressive symptoms; 59 (55.1%), for anxiety. Severe fatigue was correlated with a lower score on the Symbol Digit Modalities Test (SDMT) (r = −0.380, P < .001), and higher depressive scores were correlated with lower performance on the SDMT (r = −0.397, P < .001) and the Paced Auditory Serial Addition Test (r = −0.254, P = .009). Conclusions: Cognitive impairment, specifically processing speed, and mood symptoms are frequently present in persons with newly diagnosed RRMS.

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