Evidence map›Paper›PMID 40641893›Full record

ArticleThe archives of bone and joint surgery2025

3D Printed Models of Periarticular Fractures of the Shoulder and Elbow Improve Surgical Decision Making in Orthopedic Trainees.

Pedro Beredjiklian, Brianna Fram, Jason Core, Joshua I Ng, Robert Pugliese, Stephanie A Kwan, Michael Rivlin

Abstract read
In one paragraph

Article in The archives of bone and joint surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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.

Pedro Beredjiklian
Brianna Fram
Jason Core
Joshua I Ng
Robert Pugliese
Stephanie A Kwan
Michael Rivlin

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Periarticular fractures of the shoulder and elbow are spatially complex injuries that may be challenging to interpret on radiographs and advanced imaging. As three-dimensional (3D) printing technology has become less expensive and more available, 3D printed fracture models have gained attention for use in surgical preparation. In this study, we evaluated the effects of 3D printed fracture models on orthopedic trainee surgical planning and injury understanding for injuries of the shoulder and elbow. Methods: Models of periarticular fractures of the shoulder and elbow were manufactured by 3D printing at the medical school design lab. Eleven Orthopedic trainees viewed X-rays and computed tomography (CT) scans for each injury, and completed a preoperative questionnaires. They were then given access to the 3D model of each injury, in addition to the previously viewed imaging. They again completed a preoperative plan and questionnaire. Preoperative plans were graded for feasibility by a preestablished template. Results were compared for each participant with and without the 3D models. Results: Within all trainees and fractures, trainees were more likely to have feasible preoperative plans when given a 3D model, compared to access to x-rays and CT scans alone (74% vs. 62%). In all cases where preoperative plans were changed after handling the 3D models (46/77 changed, 60%), they stayed static or improved in feasibility. Participants reported significantly improved understanding of injury anatomy (P<0.0001), increased confidence in choosing operative positioning and surgical approaches (P<0.0001), desired implants (P=0.011), and better conceptualization of how to perform fracture reduction (P=0.0038). Conclusion: Orthopedic trainees benefit from 3D printed fracture models when performing preoperative planning of complex periarticular shoulder and elbow injuries. Given the rarity and difficulty of these injuries, use of this technology could allow for shortened learning curves and improved surgical results in the field of orthopedic fracture care.

Indexed as

3D printingEducationElbow fractureOrthopedic surgeryPreoperative planningProximal humerus fracture

Identifiers

PMID40641893
PMCPMC12238857

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Registered trials

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