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Record W2996703378 · doi:10.1136/jisakos-2019-000388

Arthroscopic anatomic glenoid reconstruction demonstrates its safety with short-term to medium-term results for anteroinferior shoulder instability: a systematic review

2019· review· en· W2996703378 on OpenAlexaff
Daniel McNeil, Matthew T. Provencher, Ivan Wong

Bibliographic record

VenueJournal of ISAKOS Joint Disorders & Orthopaedic Sports Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineIliac crestSurgerySystematic reviewRange of motionOrthopedic surgerySoft tissueAnterior shoulderMEDLINE

Abstract

fetched live from OpenAlex

What is already known► Arthroscopic anatomic glenoid reconstruction (AAGR) is a relatively recently described surgical treatment option for patients with shoulder instability and bone loss.► There are numerous technique papers and several studies with short-term to medium-term results.What are the new findings ► This study summarises the techniques that have been described in the literature for AAGR.► It also provides critical analysis of the results available to date.► It demonstrates that this is a safe procedure with results that encourage long-term study.► The observations from this review could help to guide future studies, particularly in terms of graft selection and fixation techniques in this evolving technique for managing shoulder instability.AbSTrACT Importance Glenoid bone loss can be associated with recurrent anterior shoulder instability and can lead to unsuccessful stabilisation procedures if not addressed.Objective The purpose of this study was to review the currently described techniques for arthroscopic anatomic glenoid reconstruction (AAGR) for anteroinferior shoulder instability and to analyse the results available to date.Evidence review A systematic literature search of three databases (PubMed, Embase and Scopus) was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify relevant articles.Any article describing a surgical technique and/or presenting results related to this technique was included.Quality appraisal was performed using the Risk Of Bias In Non-randomised Studies-of Interventions tool and the Institute of Health Economics Quality Appraisal of Case Series Studies Checklist.Findings Twenty-seven studies published between 2008 and 2019 were identified for inclusion.Clinical results were available for a total of 237 patients across all studies, with age range 16-67.Iliac crest autograft was used in 60% of patients.Iliac crest allograft and distal tibia allograft were used in 22% and 18% of patients, respectively.Distal clavicle autograft, lateral femoral autograft, glenoid allograft and synthetic graft were also described in cadaveric studies or technique papers without results.Capsuloligamentous repair was performed with suture anchors in 95% of patients, while 5% had no soft-tissue repair.Patient satisfaction was high (90%), with low rates of instability (5%).Clinical exam demonstrated satisfactory range of motion, with good outcomes when functional scores were assessed, including Rowe score, constant score, Walch-Duplay score, Western Ontario Shoulder Instability Index (WOSI)and subjective shoulder value.Radiographic evaluation revealed high union rates (97%), but also high rates of resorption.Graft resorption rates averaged between 10% and 32%.Conclusions Current evidence demonstrates that AAGR is a safe procedure with good short-term to mediumterm results that is worthy of further study. Level of evidence Level IV, systematic review of level III and IV studies.Were patients recruited consecutively?Unclear Unclear Yes

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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.044
GPT teacher head0.350
Teacher spread0.306 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations11
Published2019
Admission routes1
Has abstractyes

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