Early outcomes of augmented glenoid components in anatomic total shoulder arthroplasty: a systematic review
Bibliographic record
Abstract
Background: The objective was to evaluate the short-term clinical and radiological outcomes following augmented anatomic total shoulder arthroplasty in patients with posterior glenoid deficiency. Methods: An electronic search of EMBASE, MEDLINE, and PubMed identified studies reporting clinical and radiographic outcomes following augmented anatomic total shoulder arthroplasty among patients with posterior glenoid deficiency. Results: Nine studies including 312 shoulders underwent anatomic total shoulder arthroplasty using an augmented glenoid implant between 2015 and 2020. A statistically significant improvement in range of motion (ROM), visual analog scale (VAS), American Shoulder & Elbow Surgeons (ASES), Constant, University of California - Los Angeles and Simple Shoulder Test (SST) scores was demonstrated at mean follow-up of 37.1 months. Glenoid retroversion improved from 21.8° to 9.5°. At final follow-up, radiolucency was reported in 35.1% of shoulders. The 16° full-wedge augment led to higher and more severe radiographic lucency, while high peg perforation rates (44%) were observed among 5-mm augment stepped implants. The overall rate of complication was 2.6%. Rate of revision surgery was 1.9%. Conclusions: Overall, early- to mid-term outcomes following augmented anatomic total shoulder arthroplasty for posterior glenoid deficiency demonstrate good to excellent overall clinical results. More radiographic and clinical failures were reported in larger full wedge (16°) augments and stepped augments (5 mm). Prospective studies examining mid- and long-term outcomes will help further elucidate safety and efficacy of these relatively new implants.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".