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Record W2273086159 · doi:10.12659/msm.894346

A Meta-Analysis of Arthroscopic versus Open Repair for Treatment of Bankart Lesions in the Shoulder

2015· review· en· W2273086159 on OpenAlexaboutno aff
Lei Wang, Yaosheng Liu, Xiuyun Su, Shubin Liu

Bibliographic record

VenueMedical Science Monitor · 2015
Typereview
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBankart lesionBankart repairRandomized controlled trialSurgeryRange of motionMeta-analysisAnterior shoulderLesionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The optimal treatment for Bankart lesion remains controversial. Therefore, we performed this meta-analysis to compare the clinical outcomes of patients managed with open Bankart repair versus arthroscopic Bankart repair. MATERIAL AND METHODS: After systematic review of online databases, a total of 11 trials with 1022 subjects were included. The methodological quality of randomized controlled trials (RCTs) was assessed using the PEDro critical appraisal tool, and non-RCTs were evaluated by Newcastle-Ottawa (NO) quality assessment tool. Outcomes of shoulder stability, range of motion (ROM), functional scales, and surgical times were analyzed. RESULTS: Data synthesis showed significant differences between the two strategies, with regards to stability of the shoulder (P=0.008, RR=0.94, 95% CI: 0.89 to 0.98), and ROM (P<0.001, SMD=-0.47, 95% CI: -0.72 to -0.22). CONCLUSIONS: Open Bankart repair produced a more stable shoulder but had a relatively poor shoulder motion, compared with arthroscopic Bankart repair, for the treatment of Bankart lesion.

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)0.010
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.025
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.032
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.545
GPT teacher head0.549
Teacher spread0.005 · 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 designMeta-analysis
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

Citations28
Published2015
Admission routes1
Has abstractyes

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