Seasonality of presentation and birth in catatonia.

Catatonia Cosinor model Season of birth Seasonality Seasonality of presentation

Journal

Schizophrenia research
ISSN: 1573-2509
Titre abrégé: Schizophr Res
Pays: Netherlands
ID NLM: 8804207

Informations de publication

Date de publication:
16 Mar 2023
Historique:
received: 27 11 2022
revised: 06 03 2023
accepted: 07 03 2023
entrez: 18 3 2023
pubmed: 19 3 2023
medline: 19 3 2023
Statut: aheadofprint

Résumé

Catatonia is a neuropsychiatric syndrome associated with both psychiatric disorders and medical conditions. Understanding of the pathophysiology of catatonia remains limited, and the role of the environment is unclear. Although seasonal variations have been shown for many of the disorders underlying catatonia, the seasonality of this syndrome has not yet been adequately explored. Clinical records were screened to identify a cohort of patients suffering from catatonia and a control group of psychiatric inpatients, from 2007 to 2016 in South London. In a cohort study, the seasonality of presentation was explored fitting regression models with harmonic terms, while the effect of season of birth on subsequent development of catatonia was analyzed using regression models for count data. In a case-control study, the association between month of birth and catatonia was studied fitting logistic regression models. In total, 955 patients suffering from catatonia and 23,409 controls were included. The number of catatonic episodes increased during winter, with a peak in February. Similarly, an increasing number of cases was observed during summer, with a second peak in August. However, no evidence for an association between month of birth and catatonia was found. The presentation of catatonia showed seasonal variation in accordance with patterns described for many of the disorders underlying catatonia, such as mood disorders and infections. We found no evidence for an association between season of birth and risk of developing catatonia. This may imply that recent triggers may underpin catatonia, rather than distal events.

Sections du résumé

BACKGROUND BACKGROUND
Catatonia is a neuropsychiatric syndrome associated with both psychiatric disorders and medical conditions. Understanding of the pathophysiology of catatonia remains limited, and the role of the environment is unclear. Although seasonal variations have been shown for many of the disorders underlying catatonia, the seasonality of this syndrome has not yet been adequately explored.
METHODS METHODS
Clinical records were screened to identify a cohort of patients suffering from catatonia and a control group of psychiatric inpatients, from 2007 to 2016 in South London. In a cohort study, the seasonality of presentation was explored fitting regression models with harmonic terms, while the effect of season of birth on subsequent development of catatonia was analyzed using regression models for count data. In a case-control study, the association between month of birth and catatonia was studied fitting logistic regression models.
RESULTS RESULTS
In total, 955 patients suffering from catatonia and 23,409 controls were included. The number of catatonic episodes increased during winter, with a peak in February. Similarly, an increasing number of cases was observed during summer, with a second peak in August. However, no evidence for an association between month of birth and catatonia was found.
CONCLUSIONS CONCLUSIONS
The presentation of catatonia showed seasonal variation in accordance with patterns described for many of the disorders underlying catatonia, such as mood disorders and infections. We found no evidence for an association between season of birth and risk of developing catatonia. This may imply that recent triggers may underpin catatonia, rather than distal events.

Identifiants

pubmed: 36933976
pii: S0920-9964(23)00109-3
doi: 10.1016/j.schres.2023.03.015
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest MSZ declares honoraria for a lecture from Eisai Co., Ltd. All other authors declare no competing interests.

Auteurs

Tomas Mastellari (T)

University of Lille, Inserm U1172, CHU de Lille, Lille Neuroscience & Cognition (LilNCog), Lille, France; Division of Psychiatry, University College London, London, UK. Electronic address: tomas.mastellari.etu@univ-lille.fr.

Jonathan P Rogers (JP)

Division of Psychiatry, University College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK.

Mario Cortina-Borja (M)

Population, Policy and Practice Research and Teaching Department, Great Ormond Street Institute of Child Health, University College London, London, UK.

Anthony S David (AS)

Institute of Mental Health, University College London, London, UK.

Michael S Zandi (MS)

Queen Square Institute of Neurology, University College London, London, UK; National Hospital for Neurology and Neurosurgery, London, UK.

Ali Amad (A)

University of Lille, Inserm U1172, CHU de Lille, Lille Neuroscience & Cognition (LilNCog), Lille, France; Department of Neuroimaging, King's College London, London, UK.

Glyn Lewis (G)

Division of Psychiatry, University College London, London, UK.

Classifications MeSH