Evidence map›Paper›PMID 30506023›Full record

ArticleRheumatology advances in practice2018

Development of a clinical risk score for pain and function following total knee arthroplasty: results from the TRIO study.

Joanna Shim, David J Mclernon, David Hamilton, Hamish A Simpson, Marcus Beasley, Gary J Macfarlane

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Rheumatology advances in practice, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 3 pooled it
5.2field-weighted citation impact, top 4% 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

12 citing papers in PubMed, 3 syntheses or guidelines pooled it, 36 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Joanna ShimEpidemiology Group, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen.
David J MclernonMedical Statistics Team, Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen.
David HamiltonDepartment of Orthopaedics & Trauma, School of Clinical Sciences, University of Edinburgh, Edinburgh, UK.
Hamish A SimpsonDepartment of Orthopaedics & Trauma, School of Clinical Sciences, University of Edinburgh, Edinburgh, UK.
Marcus BeasleyEpidemiology Group, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen.
Gary J MacfarlaneEpidemiology Group, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen.
University of Aberdeen · GBUniversity of Edinburgh · GB

Funding

Versus Arthritis 20100
6 · The paper itself

Abstract

objectivesThe aim was to develop and validate a simple clinical prediction model, based on easily collected preoperative information, to identify patients at high risk of pain and functional disability 6 months after total knee arthroplasty (TKA).

methodsThis was a multicentre cohort study of patients from nine centres across the UK, who were undergoing a primary TKA for OA. Information on sociodemographic, psychosocial, clinical and quality-of-life measures were collected at recruitment. The primary outcome measure for this analysis was the Oxford knee score (OKS), measured 6 months postoperatively by postal questionnaire. Multivariable logistic regression was used to develop the model. Model performance (discrimination and calibration) and internal validity were assessed, and a simple clinical risk score was developed.

resultsSeven hundred and twenty-one participants (mean age 68.3 years; 53% female) provided data for the present analysis, and 14% had a poor outcome at 6 months. Key predictors were poor clinical status, widespread body pain, high expectation of postoperative pain and lack of active coping. The developed model based on these variables demonstrated good discrimination. At the optimal cut-off, the final model had a sensitivity of 83%, specificity of 61% and positive likelihood ratio of 2.11. Excellent agreement was found between observed and predicted outcomes, and there was no evidence of overfitting in the model.

conclusionWe have developed and validated a clinical prediction model that can be used to identify patients at high risk of a poor outcome after TKA. This clinical risk score may be an aid to shared decision-making between patient and clinician.

Indexed as

clinical risk scoreknee painmodel calibrationmodel discriminationosteoarthritisprediction modellingtotal knee arthroplasty

Identifiers

PMID30506023
PMCPMC6251482
OpenAlexW2807623127

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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.