Evidence map›Paper›PMID 39611566›Full record

ArticleMolecular pain

Predicting long-term pain by combining brain imaging, genetics and health questionnaire data with Swedish national registries using a prospective superstruct design.

Filip Gedin, Sebastian Blomé, Granit Kastrati, Maria Lalouni, Fredrik Åhs, Peter Fransson, Jörgen Rosén, William Hedley Thompson, Karin Jensen

Abstract read
In one paragraph

Article in Molecular pain. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Filip GedinDepartment of Clinical Neuroscience, Karolinska Institutet, Stockhom, Sweden.ORCID 0000-0002-8408-5106
Sebastian BloméDepartment of Clinical Neuroscience, Karolinska Institutet, Stockhom, Sweden.
Granit KastratiDepartment of Clinical Neuroscience, Karolinska Institutet, Stockhom, Sweden.
Maria LalouniDepartment of Clinical Neuroscience, Karolinska Institutet, Stockhom, Sweden.
Fredrik ÅhsDepartment of Psychology and Social Work, Mid University Sweden, Östersund, Sweden.
Peter FranssonDepartment of Clinical Neuroscience, Karolinska Institutet, Stockhom, Sweden.
Jörgen RosénDepartment of Clinical Neuroscience, Karolinska Institutet, Stockhom, Sweden.
William Hedley ThompsonDepartment of Clinical Neuroscience, Karolinska Institutet, Stockhom, Sweden.
Karin JensenDepartment of Clinical Neuroscience, Karolinska Institutet, Stockhom, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLong-term pain is a common health problem that results in disability for patients of all ages, leading to an enormous economic burden. Over 20% of the population suffer from long-term pain. Unfortunately, there are no clinical tests that predicts who will develop long-term pain. The overall aim is to predict future pain incidence based on brain function, pain behavior, health status, and genetic variability.

methodPrePain utilizes a superstruct design, which involves recruiting participants from ongoing research projects. Eligible individuals for participation in PrePain were over 18 years old and free from long-term pain. During the baseline visit, participants provide pain and health-related questionnaires, undergo structural and functional MRI scans, and provide a saliva sample for DNA extraction. Individual baseline measures are then routinely followed-up via national registries.

resultWe present quality-assessed data from over 300 participants. The average age was 34 years, and most participants were women (75%). 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 follow-up, we found that 45 participants had a pain-related diagnoses.

conclusionResults indicate that a superstruct design is feasible for collecting a large number of high-quality data. The incidence of long-term pain indicates that a sufficient number of participants have been recruited to complete the prediction analyses. PrePain is a unique prospective pain database with a fair prognosis to determine risk factors of long-term pain.

Indexed as

BrainMagnetic Resonance ImagingRegistriesAdultChronic PainFemaleHumansMaleMiddle AgedPainPain MeasurementProspective StudiesSurveys and QuestionnairesSwedenYoung Adultdemographyfunctional magnetic resonance imagingneuroimagingPainrisk factors

Identifiers

PMID39611566
PMCPMC11605748

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.