MétaCan
Menu
Back to cohort
Record W4416207468 · doi:10.1302/1358-992x.2025.13.117

WHICH DERMAL ALLOGRAFT SHOULD I USE FOR ROTATOR CUFF TEARS? A COMPARATIVE STUDY WITH TWO-YEAR MINIMUM FOLLOW-UP

2025· article· en· W4416207468 on OpenAlexaffabout
Amanda Chidiac, Devan Pancura, Reza Ojaghi, Ivan Wong

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRotator cuffTearsCuffBridging (networking)Retrospective cohort studyGold standard (test)Magnetic resonance imaging

Abstract

fetched live from OpenAlex

Rotator cuff tears are notoriously difficult to manage with high rates of failure following repair. Dermal acellular allografts can be used to perform bridging reconstruction with greater success than maximal repair (i.e., the current gold standard); however, research comparing allograft types for the bridging technique in large to massive rotator cuff tears is lacking. Allograft availability is subject to change, therefore, knowing whether different grafts provide different healing outcomes helps to inform on best practice. This study's purpose was to compare healing and patient-reported outcomes following bridging rotator cuff repair in patients who received an AlloPatch dermal allograft to those who received a GraftJacket dermal allograft with a minimum of two-years follow-up. This was a retrospective study of 117 consecutive patients who underwent bridging repair using either an AlloPatch or GraftJacket dermal allograft for large to massive rotator cuff tears from 2012-2021. All patients had a minimum of two-years follow-up. Data collected included demographic information, pre- and post-operative magnetic resonance images (MRIs), Western Ontario Rotator Cuff (WORC) Index, and the Disabilities of the Arm, Shoulder, and Hand (DASH) scores. The primary outcome measure was healing, determined via MRI, with secondary outcome measures of patient-reported outcomes. There were no significant demographic differences between groups. The mean time from surgery was 8.09 ± 1.66 years for the GraftJacket group (n= 75), and 3.29 ± 1.03 years for the AlloPatch group (n= 40). Graft healings were comparable in the two groups at the minimum 2-year follow-up (GraftJacket: 70% healed, 19% partial tears, 11% complete tears, vs AlloPatch: 60% healed, 20% partial tears, 20% complete tears; p= 0.445). Pre-operatively, there was no difference in either the WORC or DASH scores between groups (p= 0.541 and p= 0.253, respectively), and both groups had similar pre- to post-operative improvements in WORC and DASH scores at two-years follow-up (p= 0.381 and p= 0.570, respectively). AlloPatch and GraftJacket dermal allografts result in similar healing and patient-reported outcomes following bridging reconstruction for rotator cuff tears at two-years post-operative. These findings provide evidence that GraftJacket and AlloPatch dermal allografts offer comparable outcomes for treatment of large to massive rotator cuff tears.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.341
Teacher spread0.295 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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 routes2
Has abstractyes

Explore more

Same venueOrthopaedic ProceedingsSame topicShoulder Injury and TreatmentFrench-language works237,207