Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-10T05:10:57.085Z Has data issue: false hasContentIssue false

Identifying functional cognitive disorder: a proposed diagnostic risk model

Published online by Cambridge University Press:  17 September 2021

Laura McWhirter*
Affiliation:
Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
Craig Ritchie
Affiliation:
Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
Jon Stone
Affiliation:
Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
Alan Carson
Affiliation:
Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, United Kingdom
*
*Author for correspondence: L. McWhirter Email: laura.mcwhirter@ed.ac.uk

Abstract

Background

Functional cognitive disorders (FCD) are an important differential diagnosis of neurodegenerative disease. The utility of suggested diagnostic features has not been prospectively explored in “real world” clinical populations. This study aimed to identify positive clinical markers of FCD.

Methods

Adults with cognitive complaints but not dementia were recruited from memory, neurology, and neuropsychiatry clinics. Participants underwent structured interview, Mini International Neuropsychiatric Interview, Montreal Cognitive Assessment, Luria 3-step, interlocking fingers, digit span and Medical Symptom Validity Test, Patient Health Questionnaire 15, Hospital Anxiety and Depression Scale, Multifactorial Memory Questionnaire, and Pittsburgh Sleep Quality Inventory. Potential diagnostic variables were tested against expert consensus diagnosis using logistic regression.

Results

FCD were identified in 31/49 participants. Participants with FCD were younger, spoke for longer when prompted “Tell me about the problems you’ve been having,” and had more anxiety and depression symptoms and psychiatric diagnoses than those without FCD. There were no significant differences in sex, education, or cognitive scores. Younger age and longer spoken response predicted FCD diagnosis in a model which explained 74% of diagnostic variability and had an area under the curve (AUC) of 94%.

Conclusions

A detailed description of cognitive failure is a sensitive and specific positive feature of FCD, demonstrating internal inconsistency between experienced and observed function. Cognitive and performance validity tests appear less helpful in FCD diagnosis. People with FCD are not “worried well” but often perform poorly on tests, and have more anxiety, depression, and physical symptoms than people with other cognitive disorders. Identifying diagnostic profiles is an important step toward parity of esteem for FCDs, as differential diagnoses of neurodegenerative disease and an independent target for clinical trials.

Type
Original Research
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bell, S, Harkness, K, Dickson, JM, Blackburn, D. A diagnosis for £55: what is the cost of government initiatives in dementia case finding. Age Ageing. 2015;44(2):344345.CrossRefGoogle ScholarPubMed
Menon, R, Larner, AJ. Use of cognitive screening instruments in primary care: the impact of national dementia directives (NICE/SCIE, National Dementia Strategy). Fam Pract. 2011;28(3):272276.CrossRefGoogle ScholarPubMed
Ball, H, McWhirter, L, Ballard, C, et al. Functional cognitive disorder: dementia’s blind spot. Brain. 2020;143(10):28952903.CrossRefGoogle ScholarPubMed
Teodoro, T, Edwards, MJ, Isaacs, JD. A unifying theory for cognitive abnormalities in functional neurological disorders, fibromyalgia and chronic fatigue syndrome: systematic review. J Neurol Neurosurg Psychiatry. 2018;89(12):13081319.CrossRefGoogle ScholarPubMed
Stone, J, Pal, S, Blackburn, D, Reuber, M, Thekkumpurath, P, Carson, A. Functional (psychogenic) cognitive disorders: a perspective from the neurology clinic. J Alzheimer’s Dis. 2015;48(S1):S5S17.CrossRefGoogle ScholarPubMed
McWhirter, L, Ritchie, C, Stone, J, Carson, A. Functional cognitive disorders: a systematic review. Lancet Psychiatry. 2020;7(2):191207.CrossRefGoogle ScholarPubMed
Espay, AJ, Aybek, S, Carson, A, et al. Current concepts in diagnosis and treatment of functional neurological disorders. JAMA Neurol. 2018;75(9):11321141.CrossRefGoogle ScholarPubMed
Bharambe, V, Larner, AJ. Functional cognitive disorders: demographic and clinical features contribute to a positive diagnosis. Neurodegener Dis Manag. 2018;8(6):377383.CrossRefGoogle ScholarPubMed
Larner, AJ. Screening utility of the “attended alone” sign for subjective memory impairment. Alzheimer Dis Assoc Disord. 2014;28(4):364365.CrossRefGoogle ScholarPubMed
Larner, AJ. Dementia screening: a different proposal. Future Neurol. 2018;13(4):177179.CrossRefGoogle Scholar
Randall, A, Larner, AJ. La maladie du petit papier: A sign of functional cognitive disorder? Int J Geriatr Psychiatry. 2018;33(5):800.CrossRefGoogle Scholar
Bhome, R, McWilliams, A, Huntley, JD, Fleming, SM, Howard, RJ. Metacognition in functional cognitive disorder—a potential mechanism and treatment target. Cogn Neuropsychiatry. 2019;24(5):311321.CrossRefGoogle ScholarPubMed
Reuber, M, Blackburn, DJ, Elsey, C, et al. An interactional profile to assist the differential diagnosis of neurodegenerative and functional memory disorders. Alzheimer Dis Assoc Disord. 2018;32(3):197206.CrossRefGoogle ScholarPubMed
Jones, D, Drew, P, Elsey, C, et al. Conversational assessment in memory clinic encounters: interactional profiling for differentiating dementia from functional memory disorders. Aging Ment Health. 2016;20(5):500509.CrossRefGoogle ScholarPubMed
McKhann, GM, Knopman, DS, Chertkow, H, et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7(3):263269.CrossRefGoogle ScholarPubMed
Paradise, MB, Glozier, NS, Naismith, SL, Davenport, TA. Subjective memory complaints, vascular risk factors and psychological distress in the middle-aged: a cross-sectional study. BMC Psychiatry. 2011;11(1):108.CrossRefGoogle ScholarPubMed
Moo, LR, Slotnick, SD, Tesoro, MA, Zee, DS, Hart, J. Interlocking finger test: a bedside screen for parietal lobe dysfunction. J Neurol Neurosurg Psychiatry. 2003;74(4):530532.CrossRefGoogle Scholar
Green, P. Medical Symptom Validity Test (MSVT) for Microsoft Windows: User’s Manual; 2004.Google Scholar
Troyer, AK, Rich, JB. Multifactorial Memory Questionnaire. Baycrest; 2018. Accessed April 26, 2021. www.baycrest.org Google Scholar
Fraser, KC, Meltzer, JA, Rudzicz, F. Linguistic features identify Alzheimer’s disease in narrative speech. J Alzheimer’s Dis. 2015;49(2):407422.CrossRefGoogle Scholar
Wakefield, SJ, Blackburn, DJ, Harkness, K, Khan, A, Reuber, M. Distinctive neuropsychological profiles differentiate patients with functional memory disorder from patients with amnestic-mild cognitive impairment. Acta Neuropsychiatr. 2018;30(2):9096.CrossRefGoogle ScholarPubMed
Diniz, BS, Butters, MA, Albert, SM, Dew, MA, Reynolds, CF. Late-life depression and risk of vascular dementia and Alzheimer’s disease: systematic review and meta-analysis of community-based cohort studies. Br J Psychiatry. 2013;202(5):329335.CrossRefGoogle ScholarPubMed
Becker, E, Lorena, C, Rios, O, et al. Anxiety as a risk factor of Alzheimer’s disease and vascular dementia. Published online 2018;213(5):654660.CrossRefGoogle Scholar
Supplementary material: File

McWhirter et al. supplementary material

Figure S1

Download McWhirter et al. supplementary material(File)
File 20.6 KB