BMJ Neurology Open (Feb 2025)

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

  • Jon Stone,
  • Suvankar Pal,
  • Francesco Di Lorenzo,
  • Tiago Teodoro,
  • Tim Wilkinson,
  • Jan Coebergh,
  • Laura McWhirter,
  • Alan Carson,
  • Bruno Dubois,
  • Mark Edwards,
  • Jane Alty,
  • Isabel Santana,
  • Martin Rossor,
  • Miguel Tábuas-Pereira,
  • Stoyan Popkirov,
  • Rui Araújo,
  • Robert Howard,
  • Selma Aybek,
  • Jonathan Huntley,
  • Rohan Bhome,
  • Thomas Harbo,
  • Catherine M Pennington,
  • Flavio Nobili,
  • Ricardo Taipa,
  • Gaston Baslet,
  • Michele Tinazzi,
  • Martin Zeidler,
  • Harriet A Ball,
  • Lisbeth Frostholm,
  • Emer R McGrath,
  • Andrew Larner,
  • Jonathan Schott,
  • Elizabeth Mallam,
  • Verónica Cabreira,
  • João Massano,
  • Mirella Russo,
  • James Main,
  • Dane Rayment,
  • David Perez,
  • Sonja Antic,
  • Sasa R Filipovic,
  • Kristian Steen Frederiksen,
  • Bradleigh Hayhow,
  • Jeremy Darryl Isaacs,
  • Curt LaFrance,
  • Camillo Marra,
  • Isabel Portela Moreira,
  • Emmi P Scott,
  • Svetlana Tomic,
  • Sofia Toniolo,
  • Caroline Winther Tørring

DOI
https://doi.org/10.1136/bmjno-2024-000918
Journal volume & issue
Vol. 7, no. 1

Abstract

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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.Cite Now