Evidence map›Paper›PMID 42571476›Full record

ArticleJournal of shoulder and elbow arthroplasty2026

Estimating minimal clinically important differences in primary elective total elbow arthroplasty using distribution-based methods.

Dimitris Challoumas, Tin-Ning Wong, Neal Millar, Christopher A Peach

Abstract read
In one paragraph

Article in Journal of shoulder and elbow arthroplasty, 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

4 authors.

Dimitris ChalloumasWrightington Upper Limb Unit, Wrightington, Wigan & Leigh NHS Foundation Trust, Wigan, UK.
Tin-Ning WongSchool of Infection and Immunity, University of Glasgow, Glasgow, UK.
Neal MillarSchool of Infection and Immunity, University of Glasgow, Glasgow, UK.
Christopher A PeachTrauma & Orthopaedics, Manchester University Foundation Trust, Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Minimal clinically important differences (MCIDs) following primary total elbow arthroplasty (TEA) remain undefined, limiting interpretation of clinical benefit. This study aimed to determine TEA-specific distribution-based MCIDs from baseline variability in primary elective TEA cohorts and identify previously published MCIDs across elbow conditions. Methods: A systematic search identified primary elective TEA studies reporting baseline variability statistics. Pooled standard deviations (SD) estimated MCIDs via the half-SD method (all measures) and the one standard error of measurement method (multi-item scales). A scoping review identified published anchor- or distribution-based MCIDs. Outcomes assessed: pain visual analog scale, Mayo Elbow Performance Score (MEPS), Disabilities of Arm, Shoulder and Hand, Quick Disabilities of Arm, Shoulder and Hand, Oxford Elbow Score, and elbow range of motion. Results: Fifty-six studies contributed to baseline data. Half-SD-derived MCIDs were 1.0 point for pain visual analog scale, 11 points for MEPS, 15° for flexion-extension arc, and 20° for pronation-supination arc; the one-standard error of measurement-derived MCID for MEPS was 16 points. The scoping review identified no TEA-specific MCID studies and 9 across other elbow conditions, with wide variability. Conclusion: These TEA-specific, distribution-based MCID estimates for pain, function, and range of motion offer a pragmatic framework for outcome interpretation, shared decision-making, and future research.

Indexed as

Clinical significanceElbow replacementFunctionMCIDPROMROM

Identifiers

PMID42571476
PMCPMC13452322

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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.