Background & Aims

Long-term pain is a common health problem that causes disability in patients of all ages, leading to an enormous economic burden, and loss of productivity in working-age groups. (1) At any given timepoint, more than 20% of the population suffer from a long-term pain problem. (2) Currently, there are no demographics or clinical tests that predict who will develop long-term pain. (3) The overall aim of this prospective study is to predict future pain incidence from brain function, pain behavior, health status, and genetic variability.

Methods

PrePain uses a superstruct design, which entails recruiting participant from ongoing research projects. Individuals eligible for participation in PrePain were over 18 years and free of long-term pain problems, neurological disorders, severe psychiatric disorders, or substance abuse. Participants undergo a baseline visit where they provide informed consent, complete pain and health-related surveys, undergo structural and functional MRI scans, and provide a saliva sample for DNA extraction. Individual baseline measures are then followed up with health data from national registries in the years to come.

Results

In this evaluation of the first cohort in the superstruct project (2019 to 2023), we present quality-assessed data from >300 participants. The average age was 34 years, and most participants were women (75%). A majority had higher education and were currently employed. At baseline, the self-reported quality of life was above the Swedish average. Participants rated their pain sensitivity above average and reported low avoidance. Catastrophizing thoughts during painful episodes were rated as moderate. Assessments of (f)MRI data indicated generally good image quality. In this first evaluation follow-up, we found that 31 participants were on sick leave for pain-related diagnoses or mental health disorders.

Conclusions

Results indicate that a superstruct design is feasible for collecting a large number of high-quality datasets. At this preliminary evaluation, the incidence of long-term pain indicates that a sufficient cumulative number of participants have been recruited to complete the prediction analyses within the time frame of this project. PrePain is a unique prospective pain database with a fair prognosis to determine biological and demographic risk factors of long-term pain.

References

1. Cohen SP, Vase L, Hooten WM. Chronic pain: an update on burden, best practices, and new advances. Lancet 2021;397(10289):2082-2097

2. Yong RJ, Mullins PM, Bhattacharyya N. Prevalence of chronic pain among adults in the United States. Pain 2022;163(2):e328-e332.

3. Attal N, Perrot S, Fermanian J, Bouhassira D. The neuropathic components of chronic low back pain: a prospective multicenter study using the DN4 Questionnaire. J Pain 2011;12(10):1080-1087.

Presenting Author

Filip Gedin

Poster Authors

Filip Gedin, PhD

PhD

Karolinska Institute

Lead Author

E-mail

Sebastian Blomé

Karolinska Institute, Department of Clinical Neuroscience

Lead Author

E-mail

Gránit Kastrati

PhD

Clinical Neuroscience, Karolinska Institutet

Lead Author

E-mail

Maria Lalouni

Karolinska Institutet

Lead Author

E-mail

Fredrik Åhs

Professor

Psychology and Social Work, Mid Sweden University

Lead Author

E-mail

Peter Fransson

PhD

Lead Author

E-mail

Karin jensen Jensen (PhD)

Karolinska Institutet

Lead Author

E-mail

William Hedley Thompson

PhD

Department of Applied IT, University of Gothenburg

Lead Author

E-mail

Jörgen Rosén (Lic. psychologist)

Karolinska Institutet

Lead Author

E-mail

Topics

  • Epidemiology