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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Detecting cognitive dysfunction in a busy multiple sclerosis clinical setting: a computer generated approach.

H Lapshin1, B Audet, A Feinstein

  • 1Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, ON, Canada; University of Toronto, Toronto, ON, Canada.

European Journal of Neurology
|November 9, 2013
PubMed
Summary
This summary is machine-generated.

A brief computerized test accurately detects cognitive differences across multiple sclerosis (MS) stages, from clinically isolated syndromes (CIS) to secondary progressive MS (SPMS). This tool aids in understanding MS cognitive progression in clinical settings.

Keywords:
clinically isolated syndromescognitive dys functioncomputerized cognitive testingmultiple sclerosisneuropsychological tests

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Area of Science:

  • Neuroscience
  • Clinical Neurology
  • Psychometrics

Background:

  • Cognitive impairment is a significant challenge in multiple sclerosis (MS).
  • Differentiating cognitive deficits across MS disease courses (CIS, RRMS, PPMS, SPMS) is crucial for patient management.
  • Existing assessment methods may be time-consuming for routine clinical use.

Purpose of the Study:

  • To evaluate a brief, computerized cognitive test battery for detecting cognitive differences in patients with various MS subtypes.
  • To assess the battery's ability to differentiate between clinically isolated syndromes (CIS), relapsing-remitting MS (RRMS), primary progressive MS (PPMS), and secondary progressive MS (SPMS).

Main Methods:

  • A cohort of 136 MS patients (CIS, RRMS, PPMS, SPMS) aged 18-63 was recruited.
  • Participants completed five validated computerized cognitive tests, including STROOP, Symbol Digit Modalities Test, and Paced Visual Serial Addition Test (PVSAT).
  • A speed of cognition index was derived from reaction time measures.

Main Results:

  • Significant cognitive differences were observed between MS groups on most tests (P < 0.01), except PVSAT 2s trial.
  • Clinically isolated syndrome (CIS) patients showed the least impairment, while secondary progressive MS (SPMS) patients exhibited the most significant deficits.
  • Relapsing-remitting MS (RRMS) and primary progressive MS (PPMS) patients presented similar cognitive profiles, falling between CIS and SPMS impairment levels.
  • These distinctions remained significant after adjusting for age and education.

Conclusions:

  • The computerized cognitive battery effectively distinguishes cognitive decline across the MS disease spectrum.
  • The test's brevity (20 minutes) and ease of administration support its clinical utility.
  • This tool enhances construct validity by demonstrating sensitivity to MS disease progression.