BMC Family Practice (Dec 2017)

How to choose the most appropriate cognitive test to evaluate cognitive complaints in primary care

  • Jolien Janssen,
  • Paula S. Koekkoek,
  • Eric P. Moll van Charante,
  • L. Jaap Kappelle,
  • Geert Jan Biessels,
  • Guy E. H. M. Rutten

DOI
https://doi.org/10.1186/s12875-017-0675-4
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 8

Abstract

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Abstract Background Despite the wealth of research devoted to the performance of individual cognitive tests for diagnosing cognitive impairment (including mild cognitive impairment and dementia), it can be difficult for general practitioners to choose the most appropriate test for a patient with cognitive complaints in daily practice. In this paper we present a diagnostic algorithm for the evaluation of cognitive complaints in primary care. The rationale behind this algorithm is that the likelihood of cognitive impairment -which can be determined after history taking and an informant interview- should determine which cognitive test is most suitable. Methods We distinguished three likelihoods of cognitive impairment: not likely, possible or likely. We selected cognitive tests based on pre-defined required test features for each of these three situations and a review of the literature. We incorporated the cognitive tests in a practical diagnostic algorithm. Results Based on the available literature, in patients with complaints but where cognitive impairment is considered to be unlikely the clock-drawing test can be used to rule out cognitive impairment. When cognitive impairment is possible the Montreal cognitive assessment can be used to rule out cognitive impairment or to make cognitive impairment more likely. When cognitive impairment is likely the Mini-Mental State Examination can be used to confirm the presence of cognitive impairment. Conclusions We propose a diagnostic algorithm to increase the efficiency of ruling out or diagnosing cognitive impairment in primary care. Further study is needed to validate and evaluate this stepwise diagnostic algorithm.

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