Verónica Cabreira, Jane Alty, Sonja Antic, Rui Araujo, Selma Aybek, Harriet A Ball, Gaston Baslet, Rohan Bhome, Jan Coebergh, Bruno Dubois, Mark Edwards, Sasa R Filipovic, Kristian Steen Frederiksen, Thomas Harbo, Bradleigh Hayhow, Robert Howard, Jonathan Huntley, Jeremy Darryl Isaacs, Curt LaFrance, Andrew Larner, Francesco Di Lorenzo, James Main, Elizabeth Mallam, Camillo Marra, João Massano, Emer R McGrath, Isabel Portela Moreira, Flavio Nobili, Suvankar Pal, Catherine M Pennington, Miguel Tábuas-Pereira, David Perez, Stoyan Popkirov, Dane Rayment, Martin Rossor, Mirella Russo, Isabel Santana, Jonathan Schott, Emmi P Scott, Ricardo Taipa, Tiago Teodoro, Michele Tinazzi, Svetlana Tomic, Sofia Toniolo, Caroline Winther Tørring, Tim Wilkinson, Martin Zeidler, Lisbeth Frostholm, Laura McWhirter, Jon Stone, Alan Carson
{"title":"建立功能性认知障碍与其他神经认知障碍的诊断检查表。","authors":"Verónica Cabreira, Jane Alty, Sonja Antic, Rui Araujo, Selma Aybek, Harriet A Ball, Gaston Baslet, Rohan Bhome, Jan Coebergh, Bruno Dubois, Mark Edwards, Sasa R Filipovic, Kristian Steen Frederiksen, Thomas Harbo, Bradleigh Hayhow, Robert Howard, Jonathan Huntley, Jeremy Darryl Isaacs, Curt LaFrance, Andrew Larner, Francesco Di Lorenzo, James Main, Elizabeth Mallam, Camillo Marra, João Massano, Emer R McGrath, Isabel Portela Moreira, Flavio Nobili, Suvankar Pal, Catherine M Pennington, Miguel Tábuas-Pereira, David Perez, Stoyan Popkirov, Dane Rayment, Martin Rossor, Mirella Russo, Isabel Santana, Jonathan Schott, Emmi P Scott, Ricardo Taipa, Tiago Teodoro, Michele Tinazzi, Svetlana Tomic, Sofia Toniolo, Caroline Winther Tørring, Tim Wilkinson, Martin Zeidler, Lisbeth Frostholm, Laura McWhirter, Jon Stone, Alan Carson","doi":"10.1136/bmjno-2024-000918","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":52754,"journal":{"name":"BMJ Neurology Open","volume":"7 1","pages":"e000918"},"PeriodicalIF":2.1000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11873336/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development of a diagnostic checklist to identify functional cognitive disorder versus other neurocognitive disorders.\",\"authors\":\"Verónica Cabreira, Jane Alty, Sonja Antic, Rui Araujo, Selma Aybek, Harriet A Ball, Gaston Baslet, Rohan Bhome, Jan Coebergh, Bruno Dubois, Mark Edwards, Sasa R Filipovic, Kristian Steen Frederiksen, Thomas Harbo, Bradleigh Hayhow, Robert Howard, Jonathan Huntley, Jeremy Darryl Isaacs, Curt LaFrance, Andrew Larner, Francesco Di Lorenzo, James Main, Elizabeth Mallam, Camillo Marra, João Massano, Emer R McGrath, Isabel Portela Moreira, Flavio Nobili, Suvankar Pal, Catherine M Pennington, Miguel Tábuas-Pereira, David Perez, Stoyan Popkirov, Dane Rayment, Martin Rossor, Mirella Russo, Isabel Santana, Jonathan Schott, Emmi P Scott, Ricardo Taipa, Tiago Teodoro, Michele Tinazzi, Svetlana Tomic, Sofia Toniolo, Caroline Winther Tørring, Tim Wilkinson, Martin Zeidler, Lisbeth Frostholm, Laura McWhirter, Jon Stone, Alan Carson\",\"doi\":\"10.1136/bmjno-2024-000918\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":52754,\"journal\":{\"name\":\"BMJ Neurology Open\",\"volume\":\"7 1\",\"pages\":\"e000918\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11873336/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMJ Neurology Open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1136/bmjno-2024-000918\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Neurology Open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjno-2024-000918","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Development of a diagnostic checklist to identify functional cognitive disorder versus other neurocognitive disorders.
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.
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