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Record W4408974321 · doi:10.1016/j.arthro.2025.03.048

Allograft Resorption Following Arthroscopic Anatomic Glenoid Reconstruction Is Part of Remodeling to Restore the Native Glenoid Size and Shape 6.9 Months Postoperatively

2025· article· en· W4408974321 on OpenAlexaff
Nick Dawe, Jie Ma, Ivan Wong

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsNova Scotia HospitalNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsMedicineResorptionSurgeryPathology

Abstract

fetched live from OpenAlex

Purpose To determine if the distal tibia allograft (DTA) remodels after arthroscopic anatomic glenoid reconstruction (AAGR) to restore the native glenoid size and shape postoperatively. Methods This is a retrospective study on patients who underwent AAGR with DTA between 2013 and 2022 using screw fixation who have completed postoperative clinical follow‐up for a minimum of 2 years and have an available postoperative computed tomography (CT) scan. Glenoid width (anterior‐posterior) and height (superior‐inferior) were measured using Horos and Meshmixer on an en face view. The measured glenoid width was compared to the predicted glenoid width based on height using the following equation: Width (mm) = 2.53 mm + 0.71 ∗ Height (mm) , and the difference between the 2 variables was calculated. Data analysis used a paired t test, Pearson correlation, and receiver operating characteristic curve at a .05 significance level. Results In 109 patients included in this study, the mean ± SD age at surgery was 28.2 ± 9.6 years, mean ± SD body mass index was 26.1 ± 5.0, and mean ± SD CT follow‐up was 1.0 ± 1.1 years, including 73 primary surgeries (67%), 81 men (74%), and 52 right‐sided operative shoulders (48%). In all 109 patients, the predicted glenoid width (28.5 ± 2.5 mm) was significantly smaller than the measured glenoid width (30.7 ± 4.2 mm) ( P < .001). A significant negative correlation was found between CT follow‐up time and the difference between measured and predicted glenoid width (i.e., measured and predicted glenoid width became more similar as time passed postoperatively). A cutoff time of 6.9 months was identified for graft remodeling (area under the curve, 0.759; P < .001). In patients with ≥6.9 months between surgery and postoperative CT (n = 65), there was no difference between predicted and measured postoperative glenoid width (28.6 ± 2.6 mm, 29.4 ± 3.7 mm, respectively; P = .099). In patients with <6.9 months between surgery and postoperative CT (n = 44), the predicted glenoid width was significantly smaller than the measured glenoid width (28.4 ± 2.3 mm, 32.7 ± 3.9 mm, respectively; P < .001). Conclusions Predicted and measured postoperative glenoid width did not differ significantly in patients who had undergone AAGR with at least 6.9 months between surgery and postoperative CT. These findings support the hypothesis that the allograft remodels following AAGR with DTA to restore the native glenoid size and architecture. Clinical Relevance These findings will help direct the size of bone blocks used in AAGR with DTA in the future to optimize surgical outcomes.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.287
Teacher spread0.274 · 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 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

Citations6
Published2025
Admission routes1
Has abstractyes

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