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Uncovering Capgras delusion using a large-scale medical records database

BACKGROUND: Capgras delusion is scientifically important but most commonly reported as single case studies. Studies analysing large clinical records databases focus on common disorders but none have investigated rare syndromes. AIMS: Identify cases of Capgras delusion and associated psychopathology,...

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Autores principales: Bell, Vaughan, Marshall, Caryl, Kanji, Zara, Wilkinson, Sam, Halligan, Peter, Deeley, Quinton
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal College of Psychiatrists 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5541249/
https://www.ncbi.nlm.nih.gov/pubmed/28794897
http://dx.doi.org/10.1192/bjpo.bp.117.005041
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author Bell, Vaughan
Marshall, Caryl
Kanji, Zara
Wilkinson, Sam
Halligan, Peter
Deeley, Quinton
author_facet Bell, Vaughan
Marshall, Caryl
Kanji, Zara
Wilkinson, Sam
Halligan, Peter
Deeley, Quinton
author_sort Bell, Vaughan
collection PubMed
description BACKGROUND: Capgras delusion is scientifically important but most commonly reported as single case studies. Studies analysing large clinical records databases focus on common disorders but none have investigated rare syndromes. AIMS: Identify cases of Capgras delusion and associated psychopathology, demographics, cognitive function and neuropathology in light of existing models. METHOD: Combined computational data extraction and qualitative classification using 250 000 case records from South London and Maudsley Clinical Record Interactive Search (CRIS) database. RESULTS: We identified 84 individuals and extracted diagnosis-matched comparison groups. Capgras was not ‘monothematic’ in the majority of cases. Most cases involved misidentified family members or close partners but others were misidentified in 25% of cases, contrary to dual-route face recognition models. Neuroimaging provided no evidence for predominantly right hemisphere damage. Individuals were ethnically diverse with a range of psychosis spectrum diagnoses. CONCLUSIONS: Capgras is more diverse than current models assume. Identification of rare syndromes complements existing ‘big data’ approaches in psychiatry. DECLARATION OF INTERESTS: V.B. is supported by a Wellcome Trust Seed Award in Science (200589/Z/16/Z) and the UCLH NIHR Biomedical Research Centre. S.W. is supported by a Wellcome Trust Strategic Award (WT098455MA). Q.D. has received a grant from King’s Health Partners. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.
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spelling pubmed-55412492017-08-09 Uncovering Capgras delusion using a large-scale medical records database Bell, Vaughan Marshall, Caryl Kanji, Zara Wilkinson, Sam Halligan, Peter Deeley, Quinton BJPsych Open Paper BACKGROUND: Capgras delusion is scientifically important but most commonly reported as single case studies. Studies analysing large clinical records databases focus on common disorders but none have investigated rare syndromes. AIMS: Identify cases of Capgras delusion and associated psychopathology, demographics, cognitive function and neuropathology in light of existing models. METHOD: Combined computational data extraction and qualitative classification using 250 000 case records from South London and Maudsley Clinical Record Interactive Search (CRIS) database. RESULTS: We identified 84 individuals and extracted diagnosis-matched comparison groups. Capgras was not ‘monothematic’ in the majority of cases. Most cases involved misidentified family members or close partners but others were misidentified in 25% of cases, contrary to dual-route face recognition models. Neuroimaging provided no evidence for predominantly right hemisphere damage. Individuals were ethnically diverse with a range of psychosis spectrum diagnoses. CONCLUSIONS: Capgras is more diverse than current models assume. Identification of rare syndromes complements existing ‘big data’ approaches in psychiatry. DECLARATION OF INTERESTS: V.B. is supported by a Wellcome Trust Seed Award in Science (200589/Z/16/Z) and the UCLH NIHR Biomedical Research Centre. S.W. is supported by a Wellcome Trust Strategic Award (WT098455MA). Q.D. has received a grant from King’s Health Partners. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license. The Royal College of Psychiatrists 2017-08-03 /pmc/articles/PMC5541249/ /pubmed/28794897 http://dx.doi.org/10.1192/bjpo.bp.117.005041 Text en © 2017 The Royal College of Psychiatrists http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Paper
Bell, Vaughan
Marshall, Caryl
Kanji, Zara
Wilkinson, Sam
Halligan, Peter
Deeley, Quinton
Uncovering Capgras delusion using a large-scale medical records database
title Uncovering Capgras delusion using a large-scale medical records database
title_full Uncovering Capgras delusion using a large-scale medical records database
title_fullStr Uncovering Capgras delusion using a large-scale medical records database
title_full_unstemmed Uncovering Capgras delusion using a large-scale medical records database
title_short Uncovering Capgras delusion using a large-scale medical records database
title_sort uncovering capgras delusion using a large-scale medical records database
topic Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5541249/
https://www.ncbi.nlm.nih.gov/pubmed/28794897
http://dx.doi.org/10.1192/bjpo.bp.117.005041
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