Evidence map›Paper›PMID 42246018›Full record

ArticleThe archives of bone and joint surgery2026

Defining the Era of Shoulder Arthroscopy 2.0: A Perspective on Integrating Precision, Biology, and Smart Technology.

Kang Qin, Can Liu, Geng Peng, Yucheng Song, Liang Zhao, Yijun Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The archives of bone and joint surgery, 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

6 authors.

Kang QinDepartment of Shoulder and Elbow Surgery, Center for Orthopedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Can LiuDepartment of Shoulder and Elbow Surgery, Center for Orthopedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Geng PengDepartment of Shoulder and Elbow Surgery, Center for Orthopedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Yucheng SongDepartment of Shoulder and Elbow Surgery, Center for Orthopedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Liang ZhaoDepartment of Shoulder and Elbow Surgery, Center for Orthopedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
Yijun WangDepartment of Shoulder and Elbow Surgery, Center for Orthopedic Surgery, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past four decades, shoulder arthroscopy has advanced from diagnostic exploration to sophisticated therapeutic procedures. However, current techniques remain limited in addressing complex pathologies. We propose the concept of the Era of Shoulder Arthroscopy 2.0 (ESA2.0)-defined by surgical precision, biological integration, and digital innovation. Technologies such as three-dimensional (3D) imaging, augmented reality, and robotics are being explored to enhance accuracy and reproducibility. Concurrently, biological strategies, including platelet-rich plasma, stem cells, and scaffold-based techniques, may improve healing. Smart systems, including AI-assisted diagnosis and wearable rehabilitation tools, support more personalized treatment and optimize outcomes. This paradigm may define a future standard in arthroscopic care, offering solutions to challenges previously deemed intractable.

Indexed as

Biological augmentationPrecision surgeryShoulder arthroscopySmart technologies

Identifiers

PMID42246018
PMCPMC13231256

What OpenQuestion holds

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LicenceCC BY-NC
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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.