Evidence map›Paper›PMID 38800824›Full record

ArticleOsteoarthritis and cartilage open2024

Head-to-head comparison of appropriate use criteria for knee arthroplasty: A multicenter cohort study.

Daniel L Riddle, Levent Dumenci

Abstract read
In one paragraph

Article in Osteoarthritis and cartilage open, 2024. 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

2 authors.

Daniel L RiddleDepartments of Physical Therapy, Orthopaedic Surgery and Rheumatology, 900 East Leigh Street, Room 4:100, Virginia Commonwealth University, Richmond, VA, USA.
Levent DumenciCollege of Public Health, Department of Epidemiology and Biostatistics, Temple University, Philadelphia, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To determine, in a head-to-head comparison, which of two RAND-based knee replacement appropriateness criteria is optimal based on comparison to an externally validated method of judging good versus poor outcome. Design: Longitudinal data from the Osteoarthritis Initiative (OAI) and the Multicenter Osteoarthritis Study (MOST) were combined to produce a dataset of 922 persons with knee arthroplasty, 602 of which had adequate data for RAND classification and had their surgery within one year prior to a study visit. Data were used to determine appropriateness classification (i.e., Appropriate, Inconclusive, Rarely Appropriate) using modified versions of the first-generation and second-generation Escobar system. Growth curve analyses and multivariable regression were used to compare the two systems. Results: Neither system associated with the gold standard measure of good versus poor outcome. Distributions of appropriateness categories for the second-generation system were inconsistent with current evidence for knee arthroplasty outcome. For example, 16% of participants were classified as Appropriate and 64% as Rarely Appropriate for pain outcome. Distributions for the first-generation system aligned with current evidence. Conclusion: The first-generation modified version of the Escobar appropriateness system is superior to the newer version but neither version associated with our gold standard growth curve analyses. Both systems only differentiate between patient classification groups preoperatively and up to ten months following surgery. Reliance on appropriateness criteria to inform long-term outcome is not warranted.

Indexed as

AppropriatenessArthroplastyClassificationKnee

Identifiers

PMID38800824
PMCPMC11126850

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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.