Evidence map›Paper›PMID 41857779›Full record

ArticlePerioperative medicine (London, England)2026

Development of risk prediction model for chronic pain after knee replacement surgery: protocol for an individual patient data meta-analysis.

Behnam Sadeghirad, Malahat Khalili, Jason W Busse, Wael Abdelkader, Farid Foroutan, Lawrence Mbuagbaw, Ian Gilron, James Khan, Kim Madden, Daniel Tushinski and 16 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Perioperative medicine (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

26 authors.

Behnam SadeghiradMichael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, ON, Canada. sadeghb@mcmaster.ca.
Malahat KhaliliMichael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, ON, Canada.
Jason W BusseMichael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, ON, Canada.
Wael AbdelkaderDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
Farid ForoutanDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
Lawrence MbuagbawDepartment of Anesthesia, McMaster University, Hamilton, ON, Canada.
Ian GilronDepartment of Anesthesiology & Perioperative Medicine, Queen's University, Kingston, ON, Canada.
James KhanDepartment of Anesthesiology and Pain Medicine, University of Toronto, Toronto, ON, Canada.
Kim MaddenMichael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, ON, Canada.
Daniel TushinskiDepartment of Surgery, McMaster University, Hamilton, ON, Canada.
Eric BohmConcordia Joint Replacement Group, 310-1155 Concordia Avenue, Winnipeg, MB, Canada.
Maaike G J GademanDepartment of Orthopaedics, Leiden University Medical Center, Leiden, The Netherlands.
Rudolf W PoolmanDepartment of Orthopaedic Surgery, Joint Research OLVG Amsterdam, Amsterdam, The Netherlands.
Anthony AdiliDepartment of Surgery, McMaster University, Hamilton, ON, Canada.
Anthony V PerruccioInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Y Raja RampersaudSchroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
Christiaan RigholtCollege of Pharmacy, University of Manitoba, 750 McDermot Avenue, Winnipeg, MB, Canada.
Harsha ShanthannaDepartment of Anesthesia, McMaster University, Hamilton, ON, Canada.
Maram KhaledMichael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, ON, Canada.
Ben GabbottBone and Joint Health Department, Queen Mary University London, London, UK.
Maura MarcucciDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
Paul ZalzalDepartment of Surgery, McMaster University, Hamilton, ON, Canada.
Xavier GriffinBone and Joint Health Department, Queen Mary University London, London, UK.
Emil SchemitschDepartment of Surgery, Western University, London, ON, Canada.
Alfonso IorioDepartment of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
McMaster-PROSPER Investigators

Funding

AHSC AFP Innovation Fund HAH-24-009CIHR 497408
6 · The paper itself

Abstract

backgroundChronic post-surgical pain (CPSP) impacts approximately one in four patients following total knee arthroplasty (TKA) and is associated with reduced function and quality of life. We will conduct a systematic review of prospective studies to identify eligible data and establish an international repository of individual patient data (IPD) on prognostic factors for chronic pain after TKA. This repository will be then used to develop and validate a prediction model for CPSP following TKA.

methodsWe will identify eligible studies through a search of MEDLINE, CINAHL, EMBASE, and Cochrane CENTRAL from January 2005 to August 2025. We will include prospective studies that: (1) enrolled adults undergoing elective TKA, (2) assessed perioperative risk factors for CPSP, and (3) measured knee pain longitudinally at least 3 months post-surgery. Pairs of reviewers will independently screen titles and abstracts of retrieved citations and review the full texts of potentially eligible studies. We will reach out to principal investigators or authors of eligible studies to notify them of our initiative and request to receive their IPD into a secured repository, based on a data sharing agreement. We will use a one-stage approach for IPD meta-analysis of factors associated with CPSP following TKA, and development of a risk prediction model. DISCUSSION: We will use anonymized de-identified data for our IPD meta-analysis. This protocol was reviewed and approved by the Hamilton Integrated Research Ethics Board (HiREB). We will develop an online calculator to support our risk assessment model for research and clinical use. This IPD meta-analysis will facilitate the development of a robust prognostic model to guide clinical decisions or enrolment in interventional studies, with the ultimate goal of identifying pathways to effective CPSP prevention strategies after TKA.

trial registrationCRD42024591329.

Indexed as

Chronic post-surgical painIndividual patient data meta-analysisKnee arthroplastyPrediction modelPrognosis

Identifiers

PMID41857779
PMCPMC13214424

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.