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Tracking Persistent Symptoms in Scotland (TraPSS): A Longitudinal Prospective Cohort Study of COVID-19 Recovery After Mild Acute Infection

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Tracking Persistent Symptoms in Scotland (TraPSS): A Longitudinal Prospective Cohort Study of COVID-19 Recovery After Mild Acute Infection. / Sculthorpe, Nicholas F.; Mclaughlin, Marie; Cerexhe, Luke et al.
In: BMJ Open, Vol. 15, No. 1, e86646, 31.01.2025.

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Harvard

Sculthorpe, NF, Mclaughlin, M, Cerexhe, L, Macdonald, E, Iacono, AD, Sanal-Hayes, NEM, Ingram, J, Meach, R, Carless, D, Ormerod, J & Hayes, L 2025, 'Tracking Persistent Symptoms in Scotland (TraPSS): A Longitudinal Prospective Cohort Study of COVID-19 Recovery After Mild Acute Infection', BMJ Open, vol. 15, no. 1, e86646. https://doi.org/10.1136/bmjopen-2024-086646

APA

Sculthorpe, N. F., Mclaughlin, M., Cerexhe, L., Macdonald, E., Iacono, A. D., Sanal-Hayes, N. E. M., Ingram, J., Meach, R., Carless, D., Ormerod, J., & Hayes, L. (2025). Tracking Persistent Symptoms in Scotland (TraPSS): A Longitudinal Prospective Cohort Study of COVID-19 Recovery After Mild Acute Infection. BMJ Open, 15(1), Article e86646. https://doi.org/10.1136/bmjopen-2024-086646

Vancouver

Sculthorpe NF, Mclaughlin M, Cerexhe L, Macdonald E, Iacono AD, Sanal-Hayes NEM et al. Tracking Persistent Symptoms in Scotland (TraPSS): A Longitudinal Prospective Cohort Study of COVID-19 Recovery After Mild Acute Infection. BMJ Open. 2025 Jan 31;15(1):e86646. Epub 2025 Jan 15. doi: 10.1136/bmjopen-2024-086646

Author

Sculthorpe, Nicholas F. ; Mclaughlin, Marie ; Cerexhe, Luke et al. / Tracking Persistent Symptoms in Scotland (TraPSS) : A Longitudinal Prospective Cohort Study of COVID-19 Recovery After Mild Acute Infection. In: BMJ Open. 2025 ; Vol. 15, No. 1.

Bibtex

@article{a05abb8ff37d48b2b47efe93cf0b7748,
title = "Tracking Persistent Symptoms in Scotland (TraPSS): A Longitudinal Prospective Cohort Study of COVID-19 Recovery After Mild Acute Infection",
abstract = "Background COVID-19 disease results in disparate responses between individuals and has led to the emergence of long coronavirus disease (Long-COVID), characterised by persistent and cyclical symptomology. To understand the complexity of Long-COVID, the importance of symptom surveillance and prospective longitudinal studies is evident.Methods A 9-month longitudinal prospective cohort study was conducted within Scotland (n=287), using a mobile app to determine the proportion of recovered individuals and those with persistent symptoms and common symptoms, and associations with gender and age.Results 3.1% of participants experienced symptoms at month 9, meeting the criteria for Long-COVID, as defined by the National Institute for Health and Care Excellence terminology. The random effects model revealed a significant time (month) effect for infection recovery (p<0.001, estimate=0.07). Fatigue, cough and muscle pain were the most common symptoms at baseline, with fatigue persisting the longest, while symptoms like cough improved rapidly. Older age increased the likelihood of reporting pain (p=0.028, estimate=0.07) and cognitive impairment (p<0.001, estimate=0.93). Female gender increased the likelihood of headaches (p=0.024, estimate=0.53) and post-exertional malaise (PEM) frequency (p=0.05, estimate=137.68), and increased time x gender effect for PEM frequency (p=0.033, estimate=18.96).Conclusions The majority of people fully recover from acute COVID-19, although often slowly. Age and gender play a role in symptom burden and recovery rates, emphasising the need for tailored approaches to Long-COVID management. Further analysis is required to determine the characteristics of the individuals still reporting ongoing symptoms months after initial infection to identify risk factors and potential predictors for the development of Long-COVID.",
author = "Sculthorpe, {Nicholas F.} and Marie Mclaughlin and Luke Cerexhe and Eilidh Macdonald and Iacono, {Antonio Dello} and Sanal-Hayes, {Nilihan E. M.} and Joanne Ingram and Rachel Meach and David Carless and Jane Ormerod and Lawrence Hayes",
year = "2025",
month = jan,
day = "31",
doi = "10.1136/bmjopen-2024-086646",
language = "English",
volume = "15",
journal = "BMJ Open",
issn = "2044-6055",
publisher = "BMJ Publishing Group Ltd",
number = "1",

}

RIS

TY - JOUR

T1 - Tracking Persistent Symptoms in Scotland (TraPSS)

T2 - A Longitudinal Prospective Cohort Study of COVID-19 Recovery After Mild Acute Infection

AU - Sculthorpe, Nicholas F.

AU - Mclaughlin, Marie

AU - Cerexhe, Luke

AU - Macdonald, Eilidh

AU - Iacono, Antonio Dello

AU - Sanal-Hayes, Nilihan E. M.

AU - Ingram, Joanne

AU - Meach, Rachel

AU - Carless, David

AU - Ormerod, Jane

AU - Hayes, Lawrence

PY - 2025/1/31

Y1 - 2025/1/31

N2 - Background COVID-19 disease results in disparate responses between individuals and has led to the emergence of long coronavirus disease (Long-COVID), characterised by persistent and cyclical symptomology. To understand the complexity of Long-COVID, the importance of symptom surveillance and prospective longitudinal studies is evident.Methods A 9-month longitudinal prospective cohort study was conducted within Scotland (n=287), using a mobile app to determine the proportion of recovered individuals and those with persistent symptoms and common symptoms, and associations with gender and age.Results 3.1% of participants experienced symptoms at month 9, meeting the criteria for Long-COVID, as defined by the National Institute for Health and Care Excellence terminology. The random effects model revealed a significant time (month) effect for infection recovery (p<0.001, estimate=0.07). Fatigue, cough and muscle pain were the most common symptoms at baseline, with fatigue persisting the longest, while symptoms like cough improved rapidly. Older age increased the likelihood of reporting pain (p=0.028, estimate=0.07) and cognitive impairment (p<0.001, estimate=0.93). Female gender increased the likelihood of headaches (p=0.024, estimate=0.53) and post-exertional malaise (PEM) frequency (p=0.05, estimate=137.68), and increased time x gender effect for PEM frequency (p=0.033, estimate=18.96).Conclusions The majority of people fully recover from acute COVID-19, although often slowly. Age and gender play a role in symptom burden and recovery rates, emphasising the need for tailored approaches to Long-COVID management. Further analysis is required to determine the characteristics of the individuals still reporting ongoing symptoms months after initial infection to identify risk factors and potential predictors for the development of Long-COVID.

AB - Background COVID-19 disease results in disparate responses between individuals and has led to the emergence of long coronavirus disease (Long-COVID), characterised by persistent and cyclical symptomology. To understand the complexity of Long-COVID, the importance of symptom surveillance and prospective longitudinal studies is evident.Methods A 9-month longitudinal prospective cohort study was conducted within Scotland (n=287), using a mobile app to determine the proportion of recovered individuals and those with persistent symptoms and common symptoms, and associations with gender and age.Results 3.1% of participants experienced symptoms at month 9, meeting the criteria for Long-COVID, as defined by the National Institute for Health and Care Excellence terminology. The random effects model revealed a significant time (month) effect for infection recovery (p<0.001, estimate=0.07). Fatigue, cough and muscle pain were the most common symptoms at baseline, with fatigue persisting the longest, while symptoms like cough improved rapidly. Older age increased the likelihood of reporting pain (p=0.028, estimate=0.07) and cognitive impairment (p<0.001, estimate=0.93). Female gender increased the likelihood of headaches (p=0.024, estimate=0.53) and post-exertional malaise (PEM) frequency (p=0.05, estimate=137.68), and increased time x gender effect for PEM frequency (p=0.033, estimate=18.96).Conclusions The majority of people fully recover from acute COVID-19, although often slowly. Age and gender play a role in symptom burden and recovery rates, emphasising the need for tailored approaches to Long-COVID management. Further analysis is required to determine the characteristics of the individuals still reporting ongoing symptoms months after initial infection to identify risk factors and potential predictors for the development of Long-COVID.

U2 - 10.1136/bmjopen-2024-086646

DO - 10.1136/bmjopen-2024-086646

M3 - Journal article

VL - 15

JO - BMJ Open

JF - BMJ Open

SN - 2044-6055

IS - 1

M1 - e86646

ER -