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Development of a diagnostic checklist to identify functional cognitive disorder versus other neurocognitive disorders

Cabreira, V; Alty, J; Antic, S; Araujo, R; Aybek, S; Ball, HA; Baslet, G; Bhome, R; Coebergh, J; Dubois, B; et al. Cabreira, V; Alty, J; Antic, S; Araujo, R; Aybek, S; Ball, HA; Baslet, G; Bhome, R; Coebergh, J; Dubois, B; Edwards, M; Filipovic, SR; Frederiksen, KS; Harbo, T; Hayhow, B; Howard, R; Huntley, J; Isaacs, JD; Lafrance, C; Larner, A; Di Lorenzo, F; Main, J; Mallam, E; Marra, C; Massano, J; Mcgrath, ER; Portela Moreira, I; Nobili, F; Pal, S; Pennington, CM; Tabuas-Pereira, M; Perez, D; Popkirov, S; Rayment, D; Rossor, M; Russo, M; Santana, I; Schott, J; Scott, EP; Taipa, R; Teodoro, T; Tinazzi, M; Tomic, S; Toniolo, S; Torring, CW; Wilkinson, T; Zeidler, M; Frostholm, L; Mcwhirter, L; Stone, J; Carson, A (2025) Development of a diagnostic checklist to identify functional cognitive disorder versus other neurocognitive disorders. BMJ NEUROLOGY OPEN, 7 (1). e000918. ISSN 2632-6140 https://doi.org/10.1136/bmjno-2024-000918
SGUL Authors: Coebergh, Jan

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Abstract

Background Functional cognitive disorder (FCD) poses a diagnostic challenge due to its resemblance to other neurocognitive disorders and limited biomarker accuracy. We aimed to develop a new diagnostic checklist to identify FCD versus other neurocognitive disorders. Methods The clinical checklist was developed through mixed methods: (1) a literature review, (2) a three-round Delphi study with 45 clinicians from 12 countries and (3) a pilot discriminative accuracy study in consecutive patients attending seven memory services across the UK. Items gathering consensus were incorporated into a pilot checklist. Item redundancy was evaluated with phi coefficients. A briefer checklist was produced by removing items with >10% missing data. Internal validity was tested using Cronbach’s alpha. Optimal cut-off scores were determined using receiver operating characteristic curve analysis. Results A full 11-item checklist and a 7-item briefer checklist were produced. Overall, 239 patients (143 FCD, 96 non-FCD diagnoses) were included. The checklist scores were significantly different across subgroups (FCD and other neurocognitive disorders) (F(2, 236)=313.3, p<0.001). The area under the curve was excellent for both the full checklist (0.97, 95% CI 0.95 to 0.99) and its brief version (0.96, 95% CI 0.93 to 0.98). Optimal cut-off scores corresponded to a specificity of 97% and positive predictive value of 91% for identifying FCD. Both versions showed good internal validity (>0.80). Conclusions This pilot study shows that a brief clinical checklist may serve as a quick complementary tool to differentiate patients with neurodegeneration from those with FCD. Prospective blind large-scale validation in diverse populations is warranted.

Item Type: Article
Additional Information: © Author(s) (or their employer(s)) 2025. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group.
Keywords: DEMENTIA, COGNITION, ALZHEIMER'S DISEASE
SGUL Research Institute / Research Centre: Academic Structure > Institute of Medical, Biomedical and Allied Health Education (IMBE)
Academic Structure > Institute of Medical, Biomedical and Allied Health Education (IMBE) > Centre for Clinical Education (INMECE )
Journal or Publication Title: BMJ NEUROLOGY OPEN
ISSN: 2632-6140
Publisher License: Creative Commons: Attribution-Noncommercial 4.0
Projects:
Project IDFunderFunder ID
956673Horizon 2020https://doi.org/10.13039/501100007601
Web of Science ID: WOS:001437256200001
URI: https://openaccess.sgul.ac.uk/id/eprint/117284
Publisher's version: https://doi.org/10.1136/bmjno-2024-000918

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