Background & Aims

The large number of persistent symptoms following SARS-CoV-2 infection, termed long-COVID or post-COVID-19 condition is well documented1. Among these symptoms, post-COVID pain is a major contributor2. However, while symptoms of post-COVID pain are well documented, the reasons why some people develop pain and others do not are still largely unknown3. Existing literature that utilized large datasets about COVID-19 symptoms, including pain, is more frequent but analysis for predictors of pain has not been conducted4 which still lacks in the literature.
This study aimed to apply a prediction model to data collected from a large national cohort of COVID-19 survivors to investigate potential predictive factors that contribute to the development of persistent pain.

Methods

The dataset used for the prediction modeling analysis consisted of a Danish Cohort of 65,028 individuals with at least one prior positive reverse transcription polymerase chain reaction test, (RT-PCR) between March 2020, and December 2021. Data was collected on average 20 months post-infection via a peer-reviewed survey (SurveyXact, Rambøll Management Consulting A/S) and distributed via Digital Post (a secure governmental digital post). The survey collected data about the prevalence, type, and intensity of new pain, existing medical conditions, and worsening of existing pain, and pain medicine. Registered socio-economic data about income, education, and living status was collected from Statistics Denmark. The predictors were included in a logistic forward-selection scheme, which selected the variables based on p-values. The 20 most important variables were investigated based on univariate and multivariate AUC, and a 5-fold cross-validated AUC for the final model was calculated.

Results

The results from the univariate analysis of the prediction model revealed an area under the curve (AUC) of 0.68. The top five variables in the model contributing to the predictive value were Prior use of pain medicine (OR 6.27, 95%CI 5.79-6.78), Stress as a comorbidity (OR 2.46, 95%CI 2.29-2.64), High-income (OR 0.55, 95%CI 0.52-0.58), Age [40-60] (OR 1.36, 95%CI 1.30-1.41), and Female sex (OR 1.62, 95%CI 1.55-1.69).
The cohort was stratified into ‘No new pain’ and ‘New Pain’ with the cohort demographics describing the cohort being Female sex (No pain: 55.6%, versus with pain: 67%), Age at infection (No pain: 56.8 years versus with pain: 55.1 years), and Body Mass Index (No pain: 25.7 versus with pain: 27.1). Cohort levels of pain before the infection were stratified into ‘No new pain’ (No pain: 88.7%, Pain without medicinal intake: 9.0%, Pain with medicinal intake: 12.7%) and ‘New pain’ (No pain: 73.4%, Pain without medicinal intake: 13.9%, Pain with medicinal intake: 12.7%).

Conclusions

With an AUC of 0.68, in a large national cohort, the prediction model was able to identify 20 factors each contributing to the predictive value for the outcome ‘development of pain’ versus ‘no pain’ (Ranked: Prior use of pain medication, Stress, 4th quartile high-income, Age [40-60], Female sex, Weight, Higher education, Physical activity, Height, Asthma, Breathing pain, Back pain, Anxiety, Medium education, Age [60-80], BMI [40+], Neurological symptoms, Type II diabetes, Stomach pain, and Non-mild liver disease). The identified variables provide an insight into what can cause some to develop persistent pain while others who suffered from a COVID-19 infection do not.

References

1: Alkodaymi, MS, Omrani, OA, Fawzy, NA, Shaar, BA, Almamlouk, R, Riaz, M, Obeidat, M, Obeidat, Y, Gerberi, D, Taha, RM, Kashour, Z, Kashour, T, Berbari, EF, Alkattan, K, Tleyjeh, IM. Prevalence of post-acute COVID-19 syndrome symptoms at different follow-up periods: A systematic review and meta-analysis. Clinical Microbiology and Infection 2022, 28(5), 657-666. https://doi.org/10.1016/j.cmi.2022.01.014
2: Castaldo M., Ebbesen BD, Fernández-de-las-Peñas C, Arendt-Nielsen L, Giordano R. COVID-19 and musculoskeltal pain: an overview of the current knowledge. Minerva Anestesiologica 2023 December;89(12):1134-42. https://doi.org/10.23736/S0375-9393.23.17471-2
3: Kerzhner, O, Berla, E, Har-Even, M, Ratmansky, M, Goor-Aryeh, I. Consistency of inconsistency in long-COVID-19 pain symptoms persistency: A systematic review and meta-analysis. Pain Practice 2024, 24(1), 120-159. https://doi.org/10.1111/papr.13277
4: Sørensen, AI, Spiliopoulos, L, Bager, P, Nielsen, NM, Hansen, JV, Koch, A, Meder, IK, Ethelberg, S, Hviid, A. A nationwide questionnaire study of post-acute symptoms and health problems after SARS-CoV-2 infection in Denmark. Nature Communications 2022, 13(1), 1-8. https://doi.org/10.1038/s41467-022-31897-x

Presenting Author

Brian Duborg Ebbesen

Poster Authors

Brian Ebbesen

MSc

Aalborg University

Lead Author

E-mail

Jakob Nebeling Hedegaard

MSc

Aalborg University, Aalborg, Denmark

Lead Author

E-mail

Rocco Giordano

Center for Neuroplasticity and Pain, HST, Faculty of Medicine, Aalborg University, Aalborg, DK

Lead Author

E-mail

Juan Antonio Valera-Calero

Ph D

Universidad Complutense de Madrid, Madrid, Spain

Lead Author

E-mail

César Fernández-de-las-Peñas

dr med sci

Universidad Rey Juan Carlos (URJC), Madrid, Spain

Lead Author

E-mail

Lars Arendt-Nielsen

PhD

Aalborg University

Lead Author

E-mail

Topics

  • Epidemiology