Evidence map›Paper›PMID 37942111›Full record

ArticleArthroscopy techniques2023

Three-Dimensional Printing of Models of Patellofemoral Joint Articular Cartilage in Patients With Patella Instability for Observing Joint Congruity.

Brian G Beitler, Kunsel Kunsel, Kristin E Yu, Annie Wang, Steven M Tommasini, Daniel H Wiznia, John P Fulkerson

Abstract read
In one paragraph

Article in Arthroscopy techniques, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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.

Brian G BeitlerDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, Connecticut, U.S.A.
Kunsel KunselDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, Connecticut, U.S.A.
Kristin E YuDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, Connecticut, U.S.A.
Annie WangDepartment of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, U.S.A.
Steven M TommasiniDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, Connecticut, U.S.A.
Daniel H WizniaDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, Connecticut, U.S.A.
John P FulkersonDepartment of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, Connecticut, U.S.A.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Three-dimensional (3D) modeling and printing are increasingly used in the field of orthopaedic surgery for both research and patient care. One area where they are particularly helpful is in improving our understanding of the patellofemoral (PF) joint. Heretofore, morphological studies that use 3D models of the PF joint have primarily been based on computed tomography imaging data and thus do not incorporate articular cartilage. Here, we describe a method for creating 3D models of the articular surfaces of the PF joint based on magnetic resonance imaging. Models created using this technique can be used to improve our understanding of the morphology of the articular surfaces of the PF joint and its relationship to joint pathologies. Of particular interest is our finding of articular congruity in printed articular cartilage surfaces of dysplastic PF joints of recurrent patella dislocators.

Identifiers

PMID37942111
PMCPMC10628265

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.