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 | ||||||
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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 ) |
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Journal or Publication Title: | BMJ NEUROLOGY OPEN | ||||||
ISSN: | 2632-6140 | ||||||
Publisher License: | Creative Commons: Attribution-Noncommercial 4.0 | ||||||
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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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