Evidence map›Paper›PMID 38059576›Full record

ArticleEuropean journal of physical and rehabilitation medicine2024

Clinical prediction model for interdisciplinary biopsychosocial rehabilitation in osteoarthritis patients.

Sophie Vervullens, Lissa Breugelmans, Laura Beckers, Sander M VAN Kuijk, Miranda VAN Hooff, Bjorn Winkens, Rob J Smeets

Open access · diamondAbstract read
In one paragraph

Article in European journal of physical and rehabilitation medicine, 2024. 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
1.7field-weighted citation impact, top 16% of its field
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, 7 citations in OpenAlex.

  1. Article
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

7 authors at 4 institutions in 2 countries.

Sophie VervullensMOVANT Research Group, Department of Rehabilitation Sciences and Physiotherapy (REVAKI), University of Antwerp, Wilrijk, Belgium.
Lissa BreugelmansCare and Public Health Research Institute (CAPHRI), Department of Rehabilitation Medicine, Maastricht University, Maastricht, the Netherlands.
Laura BeckersCare and Public Health Research Institute (CAPHRI), Department of Rehabilitation Medicine, Maastricht University, Maastricht, the Netherlands.
Sander M VAN KuijkDepartment of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center, Maastricht, the Netherlands.
Miranda VAN HooffDepartment of Research, Sint Maartenskliniek, Nijmegen, the Netherlands.
Bjorn WinkensCare and Public Health Research Institute (CAPHRI), Department of Methodology and Statistics, Maastricht University, Maastricht, the Netherlands.
Rob J SmeetsCare and Public Health Research Institute (CAPHRI), Department of Rehabilitation Medicine, Maastricht University, Maastricht, the Netherlands - r.smeets@maastrichtuniversity.nl.
Maastricht University · NLMeise Botanic Garden · BEPain in Motion · BERadboud University Medical Center · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOsteoarthritis (OA) is a heterogenous condition, in which different subgroups are present. Individualized interdisciplinary multimodal pain treatments (IMPT) based on the biopsychosocial model have resulted in positive improvement of pain, health and disability in OA patients. Moreover, predictive factors for treatment success of IMPT in different musculoskeletal pain populations have been examined, but a clinical prediction model which informs whether an OA patient is expected to benefit or not from IMPT is currently lacking.

aimThe aim was to develop and internally validate a clinical prediction model to inform patient-tailored care based on identified predictors for positive or negative outcomes of IMPT in patients with OA.

designLongitudinal prospective cohort study.

settingCenter for Integral Rehabilitation at six locations in the Netherlands. POPULATION: Chronic OA patients.

methodsData in this study were collected during January 2019 until January 2022. Participants underwent a 10-week IMPT program based on the biopsychosocial model. Treatment success was defined by a minimal decrease from baseline of 9 points on the Pain Disability Index (PDI). Candidate predictors were selected by experts in IMPT and literature review. Backward logistic regression analysis was performed to develop the clinical predication model and bootstrap validation was performed for internal validation.

resultsOverall, 599 OA patients were included, of which 324 experienced treatment success. Thirty-four variables were identified as possible predictors for good IMPT outcome. Age, gender, number of pain locations, PDI baseline score, maximal pain severity, use of pain medication and alcohol, work ability, brief illness perceptions questionnaire subscales timeline, consequences, identity and treatment control, pain catastrophizing scale and self-efficacy questionnaire score were found as predictors for treatment success. The internally validated model has an acceptable discriminative power of 0.71.

conclusionsThis study reports a specific clinical prediction model for good outcome of IMPT in patients with OA. The internally validated model has an acceptable discriminative power of 0.71. CLINICAL REHABILITATION IMPACT: After external validation, this model could be used to develop a clinically useful decision tool.

Indexed as

Models, StatisticalOsteoarthritisHumansPainPrognosisProspective Studies

Identifiers

PMID38059576
PMCPMC10938038
OpenAlexW4389451896

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.