Evidence map›Paper›PMID 32120890›Full record

ArticleJournal of clinical medicine2020

Do Knee Pain Phenotypes Have Different Risks of Total Knee Replacement?

Feng Pan, Jing Tian, Ishanka P Munugoda, Stephen Graves, Michelle Lorimer, Flavia Cicuttini, Graeme Jones

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Translating clinical and patient-reported data to tailored shared decision reports with predictive analytics for knee and hip arthritis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021
    Trial
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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 1 country.

Feng PanMenzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania 7000, Australia.ORCID 0000-0002-3403-0094
Jing TianMenzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania 7000, Australia.
Ishanka P MunugodaMenzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania 7000, Australia.
Stephen GravesAustralian Orthopaedic Association National Joint Replacement Registry (AOANJRR), Adelaide, South Australia 5000, Australia.
Michelle LorimerSouth Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia 5000, Australia.
Flavia CicuttiniDepartment of Epidemiology and Preventive Medicine, Monash University Medical School, Commercial Road, Melbourne, VIC 3181, Australia.
Graeme JonesMenzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania 7000, Australia.
University of Tasmania · AUAustralian Orthopaedic Association · AUMonash University · AUSouth Australian Health and Medical Research Institute · AU

Funding

Arthritis Foundation of Australia MRI06161National Health and Medical Research Council 302204Tasmanian Community Fund D0015018University of Tasmania Grant-Institutional Research Scheme D0015019
6 · The paper itself

Abstract

Pain is the main impetus for osteoarthritis (OA) patients to seek healthcare including joint replacement. The pain experience in OA is heterogeneous and affected by factors across multiple domains-peripheral, psychological, and neurological. This indicates the existence of homogenous subgroups/phenotypes within OA patients with pain. We recently identified three pain phenotypes using a wide spectrum of pain-related factors, including structural damage on magnetic resonance imaging (MRI), emotional problems, number of painful sites, sex, body mass index, education level and comorbidities (i.e., Class 1: high prevalence of emotional problems and low prevalence of structural damage (25%); Class 2: low prevalence of emotional problems and high prevalence of structural damage (20%); Class 3: low prevalence of emotional problems and low prevalence of structural damage (55%)). This study was to examine whether the total knee replacement (TKR) risk over 12 years was different among these three pain phenotypes. Data on 963 participants (mean age 62.8 ± 7.4 years) from a population-based cohort study were utilised. Data on socio-demographic, psychological and comorbidities were collected. MRI of the right knee structural pathology was performed. TKR history was ascertained by linking to the Australian Orthopedic Association National Joint Replacement Registry. Latent class analysis and the Cox proportional hazards model were applied for the analysis. During the follow-up period, 41 right and 44 left TKRs in 67 participants were identified. In multivariable analyses, participants in Class 1 and 2 had a higher risk of having a TKR (Class 1 vs. Class 3, HR (hazard ratio) 4.81, 95%CI (confidence interval) 2.33-9.93; Class 2 vs. Class 3, HR 9.23, 95%CI 4.66-18.30). These associations were stronger in the imaged right knee but were also significant in the left knee. Participants within distinct pain phenotypes have different risks of TKR, suggesting that the identified phenotypes reflect distinct clinical subgroups with different prognoses. The risk for TKR was higher in Class 1 than that in Class 3, suggesting that pain/emotional status is a stronger driver for TKR than structural damage, and that selecting patients for TKR needs to be optimized in clinical practice.

Indexed as

knee painknee replacementpain subgroupphenotyperisk

Identifiers

PMID32120890
PMCPMC7141124
OpenAlexW3010162780

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.