Anatomic and non‐anatomic reconstruction improves post‐operative outcomes in chronic acromio‐clavicular instability: a systematic review
Bibliographic record
Abstract
PURPOSE: To systematize the surgical outcomes of anatomic and non-anatomic reconstruction in patients with chronic acromio-clavicular joint (ACJ) instability and determine which technique is superior. METHODS: This review was conducted according to the PRISMA guidelines. PubMed and Cochrane Library databases were searched up to April 30th, 2018 for original articles that assessed the outcomes of one or more surgical techniques of anatomic and non-anatomic reconstruction in patients with chronic ACJ instability. The Methodological Index for Non-randomized Studies (MINORS) was used to assess study quality. Pre-to-post meta-analysis was performed for both anatomic and non-anatomic reconstructions. RESULTS: Twenty-eight studies were included comprising 799 patients (mean age of 36.6 years old and 84% males) with a mean follow-up of 34.6 months (range 13 to 74). Surgical techniques included anatomic (tendinous or synthetic grafts/constructs) and non-anatomic reconstruction (Weaver-Dunn or Modified Weaver-Dunn, conjoined tendon transfer, or temporary hook plate). There were significant pre-to-post improvements on the constant score with an average improvement ranging from 11.1 to 50.7 (p < 0.01). Average failure rate was 7.6% (7.5% for anatomic and 8.5% for non-anatomic reconstruction). Non-comparative studies had a mean MINORS score of 9 points (out of 16) and comparative studies 17 (out of 24) with excellent interrater agreement (k = 0.910). CONCLUSION: Both anatomic and non-anatomic ACJ reconstructions provide significant post-operative improvements, but definitive conclusions on optimal technique remain elusive. Notwithstanding, comparative studies support the use of anatomic ACJ reconstruction which should be preferably used. However, until superiority is demonstrated by robust studies, surgeons should supplement their decision-making with experience and patient preference. LEVEL OF EVIDENCE: IV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".