BJPsych open · 2017
Uncovering Capgras delusion using a large-scale medical records database.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Bell Vaughan, Marshall Caryl, Kanji Zara, Wilkinson Sam, Halligan Peter, Deeley Quinton
Аннотация
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.
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.