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Record W4244081730 · doi:10.1177/2325967117s00275

Outcomes of Latarjet versus Distal Tibial Allograft for Anterior Shoulder Instability Repair: A Prospective Matched Cohort Analysis

2017· article· en· W4244081730 on OpenAlexaboutno aff
Rachel M. Frank, Jae Kim, Patrick Joseph O’Donnell, Michael J. O’Brien, Jonathan Newgren, Nikhil N. Verma, Gregory P. Nicholson, Brian J. Cole, Anthony A. Romeo, Matthew T. Provencher

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLatarjet procedureSurgeryAnterior shoulderProspective cohort studyCohortElbowInternal medicine

Abstract

fetched live from OpenAlex

Objectives: Recently, the use of fresh distal tibia allograft (DTA) for glenoid reconstruction in anterior shoulder instability has been described, with encouraging short-term outcomes, however, there is little available comparative data to the Latarjet procedure, long considered the gold standard for bone loss treatment. Thus, the purpose of this study was to determine the clinical outcomes for patients undergoing DTA compared to a matched cohort of patients undergoing Latarjet. Methods: A review of prospectively collected data of patients with a minimum 15% anterior glenoid bone loss who underwent shoulder stabilization with either DTA or Latarjet with a minimum follow-up of 2 years was conducted. Consecutive patients undergoing DTA were matched by age, body mass index, and number of previous ipsilateral shoulder surgeries to patients undergoing Latarjet in a 1-to- 1 format. Patients were evaluated preoperatively and at a minimum 2 years post operatively with American Shoulder and Elbow Surgeons (ASES), Single Assessment Numeric Evaluation (SANE), and Western Ontario Shoulder Instability Index (WOSI) outcomes assessments. Complications, reoperations, and episodes of recurrent instability were also analyzed. Statistical analysis was performed with student T-tests, with P<0.05 considered significant. Results: A total of 60 patients (30 Latarjet, 30 DTA) with an average age of 26.5±7.8 years were analyzed at an average 46±17 months (range, 24-87) following surgery. Twenty-two patients (73%) in each group underwent prior ipsilateral shoulder surgery (range, 1 to 3 surgeries) prior to Latarjet or DTA. There were no statistical differences in age, BMI, or number of prior surgeries between the groups. There were no differences between the groups in regards to recurrent instability events, subluxation, or apprehension on final examination (P>0.8). Patients in both groups experienced significant improvements in all outcomes scores following surgery (P>0.05 for all). When comparing final outcomes of Latarjet versus DTA, no significant differences were found in postoperative ASES, WOSI or SANE scores between the groups (P>0.05 for all). In the Latarjet group, 1 patient underwent reoperation (3.3%) with arthroscopic debridement with subacromial decompression for persistent anterolateral shoulder pain. In the DTA group, 1 patient (3.3%) underwent reoperation with DTA revision for asymptomatic hardware failure. There were no cases of neurovascular injuries or other complications in either cohort. Conclusion: At an average follow-up of nearly 4 years, fresh DTA reconstruction for recurrent anterior shoulder instability results in a clinically stable joint with similar clinical outcomes and recurrence rates compared to Latarjet. Longer-term studies are needed to determine if these results are maintained over time.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.347
Teacher spread0.320 · 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".

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Citations3
Published2017
Admission routes1
Has abstractyes

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