Evidence map›Paper›PMID 37440927›Full record

ReviewFrontiers in surgery2023

Present situation and development prospects of the diagnosis and treatment of rotator cuff tears.

Tianjun Zhou, Chang Han, Xisheng Weng

Registry-linked trialAbstract readReview
In one paragraph

Review in Frontiers in surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07659600 (Performance of Autologous Platelet-rich Plasma Injection for Tendon Regeneration in Partial Supraspinatus Tears), which is not on this map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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.

NCT07659600 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Performance of Autologous Platelet-rich Plasma Injection for Tendon Regeneration in Partial Supraspinatus Tears

TypeinterventionalSponsorUniversidade Nova de LisboaRan2026 to 2029Enrolled100ConditionsPartial Supraspinatus Tear, Rotator Cuff Tears (RCTs), Rotator Cuff InjuryArmsPlatelet-Rich Plasma (PRP) Injections
3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. [Development of a nomogram prediction model for re-tear after arthroscopic repair of massive rotator cuff tears].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2026
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  9. Ginsenoside Rb1 affects mitochondrial CaMolecular medicine (Cambridge, Mass.) · 2024
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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

3 authors.

Tianjun ZhouDepartment of Orthopedic, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Chang HanDepartment of Orthopedic, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xisheng WengDepartment of Orthopedic, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rotator cuff tears are an important cause of shoulder pain and are caused by degeneration or trauma of the shoulder tendon at the anatomical neck of the humeral head. The understanding and research of rotator cuff tears have a history of hundreds of years, and their etiology, diagnosis, and treatment have a complete system, but some detailed rules of diagnosis and treatment still have room for development. This research paper briefly introduces the diagnosis and treatment of rotator cuff tears. The current situation and its valuable research direction are described.

Indexed as

arthroscopyglucocorticoidminimally invasive surgerymusculoskeletal ultrasoundrotator cuff tear

Identifiers

PMID37440927
PMCPMC10333593

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Registered trials

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.