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Record W4408598487 · doi:10.1016/j.arthro.2025.03.025

<i>Editorial Commentary</i> : Bone Marrow Stimulation Provides Little Benefit for Repair of Full‐Thickness Rotator Cuff Tears

2025· editorial· en· W4408598487 on OpenAlexaff
Peter Lapner

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2025
Typeeditorial
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsRotator cuffTearsMedicineStimulationBone marrowSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Rotator cuff retears remain the most frequently observed complication after arthroscopic cuff repair, with tendon nonhealing rates reported between 20% and 68%. Biological solutions to improve healing rates are needed, and bone marrow stimulation (also known as trephination, microfracture, and crimson duvet) is an elegant solution to improving healing rates, given its efficiency and low cost-if it works. Previous randomized trials have not shown any significant benefit to microfracture in the setting of cuff repair in terms of functional outcomes or healing rates compared with treatment with cuff repair alone. Recent research suggests that healing rates may be improved with bone marrow stimulation. However, strict adherence to definitions of tendon disruption is necessary and when we only consider full-thickness retears, there does not appear to be any clinical benefit to this treatment approach.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.022
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0070.004
Open science0.0050.001
Research integrity0.0220.022
Insufficient payload (model declined to judge)0.0180.018

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.285
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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