Within and between-day variation and associations of symptoms in Long Covid: intensive longitudinal study

BURTON, Christopher, DAWES, Helen, GOODWILL, Simon, THELWELL, Michael and DALTON, Caroline (2023). Within and between-day variation and associations of symptoms in Long Covid: intensive longitudinal study. PLOS ONE, 18 (1): e0280343.

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Link to published version:: https://doi.org/10.1371/journal.pone.0280343


Background: People with Long Covid (Post Covid-19 Condition) describe multiple symptoms which vary between and within individuals over relatively short time intervals. We aimed to describe the real-time associations between different symptoms and between symptoms and physical activity at the individual patient level. Methods and findings: Intensive longitudinal study of 82 adults with self-reported Long Covid (median duration 12–18 months). Data collection involved a smartphone app with 5 daily entries over 14 days and continuous wearing of a wrist accelerometer. Data items included 7 symptoms (Visual Analog Scales) and perceived demands in the preceding period (Likert scales). Activity was measured using mean acceleration in the 3-hour periods preceding and following app data entry. Analysis used within-person correlations of symptoms pairs and both pooled and individual symptom networks derived from graphical vector autoregression. App data was suitable for analysis from 74 participants (90%) comprising 4022 entries representing 77.6% of possible entries. Symptoms varied substantially within individuals and were only weakly autocorrelated. The strongest between-subject symptom correlations were of fatigue with pain (partial coefficient 0.5) and cognitive difficulty with light-headedness (0.41). Pooled within-subject correlations showed fatigue correlated with cognitive difficulty (partial coefficient 0.2) pain (0.19) breathlessness (0.15) and light-headedness (0.12) but not anxiety. Cognitive difficulty was correlated with anxiety and light-headedness (partial coefficients 0.16 and 0.17). Individual participant correlation heatmaps and symptom networks showed no clear patterns indicative of distinct phenotypes. Symptoms, including fatigue, were inconsistently correlated with prior or subsequent physical activity: this may reflect adjustment of activity in response to symptoms. Delayed worsening of symptoms after the highest activity peak was observed in 7 participants. Conclusion: Symptoms of Long Covid vary within individuals over short time scales, with heterogenous patterns of symptom correlation. The findings are compatible with altered central symptom processing as an additional factor in Long Covid.

Item Type: Article
Additional Information: ** From PLOS via Jisc Publications Router ** Licence for this article: http://creativecommons.org/licenses/by/4.0/ ** Acknowledgements: We would like to thank the participants who took part in this study and the people with Long Covid who gave advice on the project throughout, including advising on the study design, interpreting the findings, and critically reading the manuscript. For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. **Journal IDs: eissn 1932-6203 **Article IDs: publisher-id: pone-d-22-17123 **History: published_online 19-01-2023; collection 2023; accepted 27-12-2022; submitted 14-06-2022
Uncontrolled Keywords: Research Article, Medicine and health sciences, Computer and information sciences, Engineering and technology, Research and analysis methods
Identification Number: https://doi.org/10.1371/journal.pone.0280343
SWORD Depositor: Colin Knott
Depositing User: Colin Knott
Date Deposited: 23 Jan 2023 10:44
Last Modified: 11 Oct 2023 17:49
URI: https://shura.shu.ac.uk/id/eprint/31317

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