Hostname: page-component-89b8bd64d-n8gtw Total loading time: 0 Render date: 2026-05-06T21:41:31.043Z Has data issue: false hasContentIssue false

Psychiatric sequelae after SARS-Cov-2 infection: trajectory, predictors and associations in a longitudinal Australian cohort

Published online by Cambridge University Press:  08 September 2023

Seetal Dodd*
Affiliation:
Deakin University, IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Australia Centre for Youth Mental Health and Orygen, The National Centre of Excellence in Youth Mental Health, The University of Melbourne, Melbourne, Australia Department of Psychiatry, The University of Melbourne, Melbourne, Australia, Melbourne, Australia
Mohammedreza Mohebbi
Affiliation:
Deakin University, IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Australia Deakin University, Faculty of Health, Biostatistics Unit, Geelong, Australia
Josie O’Donohue
Affiliation:
Deakin University, IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Australia
Gail Matthews
Affiliation:
Kirby Institute, University of New South Wales, Sydney, Australia
David R. Darley
Affiliation:
Florey Institute for Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia UNSW Medicine, St Vincent’s Clinical School, The University of New South Wales, Sydney, Australia Department of Thoracic Medicine, St Vincent’s Hospital, Sydney, Australia
Michael Berk
Affiliation:
Deakin University, IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Barwon Health, Geelong, Australia Centre for Youth Mental Health and Orygen, The National Centre of Excellence in Youth Mental Health, The University of Melbourne, Melbourne, Australia Department of Psychiatry, The University of Melbourne, Melbourne, Australia, Melbourne, Australia Kirby Institute, University of New South Wales, Sydney, Australia
*
Corresponding author: S. Dodd; Email: seetald@barwonhealth.org.au
Rights & Permissions [Opens in a new window]

Abstract

A relationship between SARS-CoV-2 infection and psychiatric symptoms has been identified but is still being fully investigated. Neuropsychiatric sequalae have been reported for several infectious agents and are not unexpected for SARS-CoV-2 infection. This study follows for 12 months a sample (N = 144) of people who have had a confirmed infection of SARS-CoV-2. Medical and neuropsychiatric data and biological specimens are collected at 6 study visits. The 34-item SPHERE questionnaire, the Depression in the Medically Ill instrument, the EQ-5D-5L quality of life instrument and the visual analogue scale of fatigue were administered at multiple timepoints and associations with measures of illness and inflammatory biomarkers were investigated using the generalised estimating equation. Associations between inflammatory biomarkers and mental health measures of various effect sizes were identified. A robust inverse association was found between mental health outcomes and long covid status, but not between mental health outcomes and covid illness severity. This study suggests that long covid may be the strongest predictor of neuropsychiatric symptoms amongst people who have been infected with SARS-CoV-2.

Information

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of Scandinavian College of Neuropsychopharmacology
Figure 0

Table 1. Sociodemographic characteristics of participants at baseline

Figure 1

Table 2. Mental health measures at each follow-up

Figure 2

Table 3. GEE models for investigating associations between pre-existing comorbidities or psychological conditions baseline, C-reactive protein level, symptom severity and Long COVID status, with mental health self-report measures across follow-ups, adjusted for age, gender and smoking status

Figure 3

Table 4. GEE models for investigating associations between biomarkers and mental health self-report measures across follow-ups, adjusted for age, gender and smoking status