Evidence map›Paper›PMID 40936548›Full record

ArticleArthroscopy techniques2025

Suture Anchor Onlay Technique: Peroneus Longus Autograft Augmentation for Arthroscopic Irreparable Massive Rotator Cuff Tear Reconstruction.

Yi Li, Wenbo Yang, Fashuai Wu, Yizhong Peng, Chunqing Meng, Hong Wang, Wei Huang

Abstract read
In one paragraph

Article in Arthroscopy techniques, 2025. 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

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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

7 authors.

Yi LiDepartment of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, China.
Wenbo YangDepartment of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, China.
Fashuai WuDepartment of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, China.
Yizhong PengDepartment of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, China.
Chunqing MengDepartment of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, China.
Hong WangDepartment of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, China.
Wei HuangDepartment of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rotator cuff tears (RCTs) are common injuries, and treatments for irreparable massive RCTs are still controversial. Among the various treatment options for irreparable massive RCTs, rotator cuff reconstruction is considered a reasonable approach, yet there is no consensus on the optimal reconstruction technique. In this article, we introduce a suture anchor onlay technique for rotator cuff reconstruction. In our technique, the peroneus longus tendon is harvested and prepared as an autograft, and on the lateral side, a suture anchor is implanted to fix the autograft on the greater tuberosity surface. The key steps of our technique are performing anchor implantation to ensure that the autografts are fixed tightly on the greater tuberosity surface, knotting the sutures from the medial-row anchors that we pre-implanted at the midsubstance of the autograft to provide additional fixation, and finally, achieving "onlay" fixation of the autografts. Our technique can effectively reduce surgical time, simplify the reconstruction procedure, and has good clinical application value.

Identifiers

PMID40936548
PMCPMC12420613

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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.