Dataset Information

Deciphering Depressive Mood in Relapsing-Remitting and Progressive Multiple Sclerosis and Its Consequence on Quality of Life.

ABSTRACT:

Background

Depressive mood and other emotional symptoms are common in multiple sclerosis (MS). The patient-reported outcome version of the "Echelle d'Humeur Dépressive" (EHD-PRO) aims to differentiate between two dimensions of depressive mood in people living with MS (PwMS).

Objectives

First, to compare EHD-PRO assessment and its two dimensions, lack of emotional control and emotional blunting, between a large sample of healthy controls (HCs) and two samples of PwMS, relapsing-remitting MS (RRMS) and primary progressive MS (PPMS); and second, to analyse the relationships between EHD-PRO scores with neurological disability, cognitive function, fatigue and health-related quality of life (HR-QOL).

Results

Regardless of their phenotype, PwMS had significantly higher EHD-PRO scores than HCs. EHD-PRO scores did not differ between the two MS groups. EHD-PRO scores did not correlate with disability and fatigue scores, disease duration or cognitive z scores. In RRMS, the lack of emotional control was independently associated with a decrease in HR-QOL.

Conclusion

The EHD-PRO is able to easily detect depressive mood and to differentiate between two clinical dimensions, emotional blunting and lack of emotional control. The scale is sensitive and seems robust to confounding factors. Lack of emotional control seems to contribute significantly to altered HR-QOL in RRMS.

SUBMITTER: Lamargue Hamel D

PROVIDER: S-EPMC4640551 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Deciphering Depressive Mood in Relapsing-Remitting and Progressive Multiple Sclerosis and Its Consequence on Quality of Life.

Lamargue Hamel Delphine D Deloire Mathilde M Ruet Aurélie A Charré-Morin Julie J Saubusse Aurore A Ouallet Jean-Christophe JC Brochet Bruno B

PloS one 20151110 11

<h4>Background</h4>Depressive mood and other emotional symptoms are common in multiple sclerosis (MS). The patient-reported outcome version of the "Echelle d'Humeur Dépressive" (EHD-PRO) aims to differentiate between two dimensions of depressive mood in people living with MS (PwMS).<h4>Objectives</h4>First, to compare EHD-PRO assessment and its two dimensions, lack of emotional control and emotional blunting, between a large sample of healthy controls (HCs) and two samples of PwMS, relapsing-rem ...[more]

PMID: 26555230

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Project description:BackgroundThe mechanisms driving primary progressive and relapsing-remitting multiple sclerosis (PPMS/RRMS) phenotypes are unknown. Magnetic resonance imaging (MRI) studies support the involvement of gray matter (GM) in the degeneration, highlighting its damage as an early feature of both phenotypes. However, the role of GM microstructure is unclear, calling for new methods for its decryption.PurposeTo investigate the morphometric and microstructural GM differences between PPMS and RRMS to characterize GM tissue degeneration using MRI.Study typeProspective cross-sectional study.SubjectsForty-five PPMS (26 females) and 45 RRMS (32 females) patients.Field strength/sequence3T scanner. Three-dimensional (3D) fast field echo T1-weighted (T1-w), 3D turbo spin echo (TSE) T2-w, 3D TSE fluid-attenuated inversion recovery, and spin echo-echo planar imaging diffusion MRI (dMRI).AssessmentT1-w and dMRI data were employed for providing information about morphometric and microstructural features, respectively. For dMRI, both diffusion tensor imaging and 3D simple harmonics oscillator based reconstruction and estimation models were used for feature extraction from a predefined set of regions. A support vector machine (SVM) was used to perform patients' classification relying on all these measures.Statistical testsDifferences between MS phenotypes were investigated using the analysis of covariance and statistical tests (P < 0.05 was considered statistically significant).ResultsAll the dMRI indices showed significant microstructural alterations between the considered MS phenotypes, for example, the mode and the median of the return to the plane probability in the hippocampus. Conversely, thalamic volume was the only morphometric feature significantly different between the two MS groups. Ten of the 12 features retained by the selection process as discriminative across the two MS groups regarded the hippocampus. The SVM classifier using these selected features reached an accuracy of 70% and a precision of 69%.Data conclusionWe provided evidence in support of the ability of dMRI to discriminate between PPMS and RRMS, as well as highlight the central role of the hippocampus.Level of evidence2 TECHNICAL EFFICACY STAGE: 3.

Dataset Information

Deciphering Depressive Mood in Relapsing-Remitting and Progressive Multiple Sclerosis and Its Consequence on Quality of Life.

Background

Objectives

Results

Conclusion

Publications

Deciphering Depressive Mood in Relapsing-Remitting and Progressive Multiple Sclerosis and Its Consequence on Quality of Life.

Similar Datasets

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