Karolinska Institutet, Karolinska university hospital
Department of Clinical neuroscience

Author Of 2 Presentations

Prognostic Factors Poster Presentation

P0420 -  Performance on Symbol Digits Modalities Test preceding conversion to Secondary Progressive Multiple Sclerosis (ID 1254)

Speakers
Presentation Number
P0420
Presentation Topic
Prognostic Factors

Abstract

Background

In an era of emerging new therapies for SPMS, neurologist are searching for robust tools to predict and identify conversion to SPMS. Cognitive impairment is prevalent in 40-75% of MS patients and supposedly more common in SPMS as it increases with age. Symbol Digits Modalities Test (SDMT) is a sensitive, easy administrated test of information processing speed and predicts driving capacity and future income in MS populations.

Objectives

In this pilot study we test if SDMT absolute values could be used to predict SPMS conversion, hypothesizing that SPMS patients prior to conversion have lower scores on SDMT compared to age and gender matched RRMS patients.

Methods

This is a Swedish MS Registry-based study. We extracted first SDMT score and age at testing, available for MS patients included in the registry. Then we selected RRMS patients with first SDMT value at least 4 years (mean ± SD, 6.5 ± 1.98) before SPMS onset n=192 (SPMS converters) and gender matched RRMS patients (n=192) that performed their first SDMT at the same age as SPMS converters. We performed a linear regression analysis using SDMT as dependent variable and age, gender, disease course (SP convert) as independent variables.

Results

RRMS patients that later converted to SPMS, had statistically significant lower SDMT values compared to age and gender matched RRMS patients, p=3.43x10-13. Overall, SDMT decreased with age and was lower for men compared to women (p=0.0002 and p=0.024).

Conclusions

Differences in SDMT absolute values correlate with and precede SPMS conversion at the group level. High variation of inter-individual SDMT performance is likely to limit the usefulness of SDMT to predict SPMS by itself, but SDMT could be an integrated component of a more complex prediction algorithm.

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Reproductive Aspects and Pregnancy Poster Presentation

P1136 - Severe neuroinflammatory relapse after ectopic pregnancy termination: a case report on MS patient with myelin oligodendrocyte glycoproteinantibodies. (ID 757)

Speakers
Presentation Number
P1136
Presentation Topic
Reproductive Aspects and Pregnancy

Abstract

Background

Pregnancy has disease-modifying effects in MS with declined disease activity during the third trimester and increased relapse rate postpartum. A recent study indicates that abortion is associated with a clinical and radiological rebound effect 12 months post-event. MS with myelin oligodendrocyte glycoprotein (MOG) autoantibodies is a rare disease variant and the effects of pregnancy or abortion have not been studied.

Objectives

With this case rapport we want to share our experience on severe inflammatory reactivation after ectopic pregnancy and surgical abortion in MS patient who carries MOG antibodies.

Methods

This is a clinical case report on a female MS patient from Middle East, born in 1976, who moved to Sweden in 2007. She suffered from optic neuritis in 2008. In 2010, our patient got a diagnosis of MS, McDonald criteria 2005 were fulfilled. During 2011-2014 she was treated with interferon beta-1a. Due to relapses and new MRI lesionsthe treatment was changed to dimehtyl fumarate (DMF) in 2015 and the dose was halved due to side effects. In August 2019, DMF was terminated due to secondary progressive disease course. Later that month, the patient underwent a surgical abortion due to ectopic pregnancy.

Results

Post-abortion, the patient developed >50 T2 lesions and 8 Gd+ lesions on brain MRI. Cerebrospinal fluid analysis showed increased levels of neurofilament light (NFL) at 13700 ng/L (ref <890 in age group 40-60).

Conclusions

This case report illustrates a severe neuroinflammatory MS reactivation after a preterm pregnancy termination. The discontinuation of DMF just prior abortion may have contributed to the inflammatory rebound after abortion. The role of MOG antibodies in inflammatory reactivation post-abortion needs to be clarified.

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Presenter Of 1 Presentation

Prognostic Factors Poster Presentation

P0420 -  Performance on Symbol Digits Modalities Test preceding conversion to Secondary Progressive Multiple Sclerosis (ID 1254)

Speakers
Presentation Number
P0420
Presentation Topic
Prognostic Factors

Abstract

Background

In an era of emerging new therapies for SPMS, neurologist are searching for robust tools to predict and identify conversion to SPMS. Cognitive impairment is prevalent in 40-75% of MS patients and supposedly more common in SPMS as it increases with age. Symbol Digits Modalities Test (SDMT) is a sensitive, easy administrated test of information processing speed and predicts driving capacity and future income in MS populations.

Objectives

In this pilot study we test if SDMT absolute values could be used to predict SPMS conversion, hypothesizing that SPMS patients prior to conversion have lower scores on SDMT compared to age and gender matched RRMS patients.

Methods

This is a Swedish MS Registry-based study. We extracted first SDMT score and age at testing, available for MS patients included in the registry. Then we selected RRMS patients with first SDMT value at least 4 years (mean ± SD, 6.5 ± 1.98) before SPMS onset n=192 (SPMS converters) and gender matched RRMS patients (n=192) that performed their first SDMT at the same age as SPMS converters. We performed a linear regression analysis using SDMT as dependent variable and age, gender, disease course (SP convert) as independent variables.

Results

RRMS patients that later converted to SPMS, had statistically significant lower SDMT values compared to age and gender matched RRMS patients, p=3.43x10-13. Overall, SDMT decreased with age and was lower for men compared to women (p=0.0002 and p=0.024).

Conclusions

Differences in SDMT absolute values correlate with and precede SPMS conversion at the group level. High variation of inter-individual SDMT performance is likely to limit the usefulness of SDMT to predict SPMS by itself, but SDMT could be an integrated component of a more complex prediction algorithm.

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