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The following is a summary of “Predictive Ability of Previous Pain and Disease Conditions on the Presentation of Post-COVID Pain in a Danish Cohort of Adult COVID-19 Survivors,” published in the April 2025 issue of European Journal of Pain by Ebbesen et al. 

Researchers conducted a retrospective study to analyze predictive profiles of identified risk factors for post-COVID pain development.  

They collected data using 2 questionnaires on demographics, pre-existing medical conditions, pain history, and post-COVID pain experience. Socioeconomic data and the coronavirus disease 2019 (COVID-19) reverse transcription-polymerase chain reaction (RT-PCR) results were obtained. The study included 68,028 individuals, divided into those with pre-COVID pain (n = 9,090) and without pre-COVID pain (n = 55,938). Forward-selection prediction models identified predictor profiles for post-COVID pain in the full cohort (Model 1) and in groups with (Model 2) and without (Model 3) pre-COVID pain from 58 potential risk factors.  

The results showed that Model 1 achieved a 5-fold cross-validated area under the curves (cvAUC) of 0.68, with pain medication use, stress, high income, age, female gender, and weight contributing to 97% of model performance. Model 2 (cvAUC = 0.69) identified pain medication use, breathing pain, stress, height, physical activity, and weight as top predictors, accounting for 98.6% of predictive performance. Model 3 (cvAUC = 0.65) highlighted stress, female gender, weight, higher education, age, high income, and physical activity as key predictors, contributing to 98.5% of performance. Height was unique to Model 2, while female gender and high income were specific to Model 3.  

Investigators concluded that the study highlighted potential important predictors requiring further detailed research and that the results might be relevant to understanding post-viral pain sequelae after other viral infections. 

Source: onlinelibrary.wiley.com/doi/10.1002/ejp.70021