Evidence map›Paper›PMID 40317171›Full record

ArticleHand (New York, N.Y.)2026

Surgical Visualization of Scaphoid Fractures: A Three-Dimensional Study Comparing Dorsal and Volar Approaches.

Scott Telfer, James N Winters, John T Heineman, Nicholas Iannuzzi

Abstract readComparative Study
In one paragraph

Article in Hand (New York, N.Y.), 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
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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.

Scott TelferUniversity of Washington, Seattle, USA.ORCID 0000-0002-0104-4027
James N WintersUniversity of Washington, Seattle, USA.
John T HeinemanUniversity of Washington, Seattle, USA.
Nicholas IannuzziUniversity of Washington, Seattle, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe optimal surgical approach for visualizing fractures of the scaphoid in different locations is often unclear. In this study, we aimed to define and quantify the observable surface areas of different surgical approaches for scaphoid fractures. In addition, we looked to demonstrate the utility of handheld 3D surface scanning for the in situ measurement of visible bone using different approaches.

methodsSix cadaveric specimens each underwent 3 surgical approaches to the scaphoid: dorsal, before and after the removal of the dorsal ridge soft tissues (DRST), and volar. Three-dimensional (3D) surface scans were taken of both the in situ surgical field and, after the approaches were completed and visible regions marked, the excised bone. The overall area and locations of the exposed bone were determined, and the area of bone measured within the surgical field scan and excised bone compared.

resultsIn terms of the overall visible surface area, the dorsal approach with DRST removed provided the most exposure, followed by the volar approach, and the dorsal approach with intact DRST. For visualization of the scaphoid waist, the volar approach was found to provide the surgeon with the greatest visible surface area. The 3D surface scanning technique was found to accurately capture in situ morphology of the exposed bone.

conclusionsThe findings from this study help inform the best surgical approach to use for fractures of the scaphoid. Three-dimensional surface scanning may be used to quantify exposed regions of bone and may be a useful tool for teaching and as part of a surgical guidance system.

Indexed as

Fractures, BoneImaging, Three-DimensionalScaphoid BoneCadaverHumansMale3D surface scanningbonescaphoid fracturesurgical approachvisualization

Identifiers

PMID40317171
PMCPMC12049360

What OpenQuestion holds

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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.