Evidence map›Paper›PMID 34383105›Full record

ArticleInternational orthopaedics2021

Simulation in shoulder arthroplasty education using three-dimensional planning software: the role of guidelines and predicted range of motion.

Marc-Olivier Gauci, Pierre-Emmanuel Chammas, Tyler Robert Johnston, Mikael Chelli, Jean Chaoui, François Boux de Casson, Laurent Blasco, Pascal Boileau

Abstract read
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In one paragraph

Article in International orthopaedics, 2021. 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
0.2field-weighted citation impact, top 46% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

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

8 authors at 3 institutions in 2 countries.

Marc-Olivier GauciInstitut Universitaire Locomoteur & Sport (IULS), Unité de Recherche Clinique Côte d'Azur (UR2CA), Hôpital Pasteur 2 CHU de Nice, Université Côte D'Azur, 30 voie Romaine, 06000, Nice, France. marcoliviergauci@gmail.com.ORCID 0000-0003-2228-7084
Pierre-Emmanuel ChammasUnité de Chirurgie du Membre Supérieur, de la Main et des Nerfs PériphériquesDépartement de Chirurgie Orthopédique, CHU de Lapeyronie, Montpellier, France.
Tyler Robert JohnstonDivision of Sports Medicine, Department of Orthopaedic Surgery, University of California at Irvine, Irvine, CA, USA.
Mikael ChelliInstitut Universitaire Locomoteur & Sport (IULS), Unité de Recherche Clinique Côte d'Azur (UR2CA), Hôpital Pasteur 2 CHU de Nice, Université Côte D'Azur, 30 voie Romaine, 06000, Nice, France.
Jean ChaouiSociété IMASCAP, Plouzané, France.
François Boux de CassonSociété IMASCAP, Plouzané, France.
Laurent BlascoInstitut Universitaire Locomoteur & Sport (IULS), Unité de Recherche Clinique Côte d'Azur (UR2CA), Hôpital Pasteur 2 CHU de Nice, Université Côte D'Azur, 30 voie Romaine, 06000, Nice, France.
Pascal BoileauInstitut Universitaire Locomoteur & Sport (IULS), Unité de Recherche Clinique Côte d'Azur (UR2CA), Hôpital Pasteur 2 CHU de Nice, Université Côte D'Azur, 30 voie Romaine, 06000, Nice, France.
Centre Hospitalier Universitaire de Nice · FRHôpital Lapeyronie · FRUniversity of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo demonstrate how reverse shoulder arthroplasty (RSA) planning software could be used to improve how the trainees position glenoid and humeral implants and obtain optimal simulated range of motion (ROM).

methodsWe selected four groups of five various level participants: medical student (MS), junior resident (JR), senior resident (SR), and shoulder expert (SE). Thereafter, the 20 participants planned five cases of arthritic shoulders for a RSA on a validated planning software following three phases: (1) no guidelines and no ROM feedback, (2) guidelines but no ROM feedback, and (3) guidelines and ROM feedback. We evaluated the final simulated impingement-free ROM, the choice of the implant (baseplate size, graft, glenosphere), and the glenoid implant positioning.

resultsMS planning were significantly improved by the ROM feedback only. JR took the best advantage of both guidelines and ROM in final results. SR planning were less performant than SE into phase 1 regarding flexion, external rotation, and adduction (respectively - 10°, p = 0.03; - 11°, p = 0.003; and - 3°, p = 0,03), but reached similar results into phase 3 (respectively - 2°, p = 0.329; - 4°, p = 0.44; - 2°, p = 0.319). For MS, JR, and SR, we observed a systematic improvement in the agreement over the study course. The glenoid diameter remained highly variable even for SE. Comparing glenoid implant position to SE, the distance error decreased with advancing phases.

conclusionPlanning software can be used as a simulation training tool to improve implant positioning in shoulder arthroplasty procedures.

Indexed as

Arthroplasty, Replacement, ShoulderGlenoid CavityShoulder JointHumansRange of Motion, ArticularSoftware3D planningEducationGuidelinesRange of motionReverse shoulder arthroplastySimulationTrainees

Identifiers

PMID34383105
OpenAlexW3190499284

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Textmetadata
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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.