Outcomes of anatomic versus reverse shoulder arthroplasty for B2 & B3 glenoids with an intact rotator cuff: An updated systematic review and proportional meta-analysis
Bibliographic record
Abstract
Background: It is unclear whether anatomic total shoulder arthroplasty (aTSA) or reverse total shoulder arthroplasty (rTSA) produces better outcomes in patients with Walch type B2 and B3 glenoids. The purpose of this systematic review was to examine the clinical and functional outcomes of anatomic and reverse shoulder arthroplasty in patients with B2 or B3 glenoids and preserved rotator cuff musculature. Methods: A comprehensive literature search of MEDLINE, EMBASE, and COCHRANE library was performed from the database inception through November 12, 2023. Results: There were 36 studies included in the final analysis. A total of 1349 shoulders underwent aTSA, while 478 shoulders underwent rTSA. The mean active range of motion improvements for patients undergoing aTSA and rTSA were similar, as were improvements in American Shoulder and Elbow Surgeons, Constant and Visual Analogue Scale scores. The pooled complication rate for aTSA was 7.8% (95% CI, 4.7%-11.4%) and for rTSA was 4.4% (95% CI, 2.8%-6.9%). For revision rates, aTSA had a pooled rate of 5.2% (95% CI, 3.3%-7.1%) whereas rTSA had a revision rate of 1.6% (95%CI, 1.1%-3.8%). Discussion: Based on the available data, both aTSA and rTSA effectively improved range of motion and patient-reported outcomes in patients with Walch B2 and B3 glenoids. However, aTSA demonstrated a higher complication rate (7.8% vs 4.5%) and a higher revision rate (5.2% versus 1.6%) compared to rTSA. Given the potential for bias in the included studies, these findings should be interpreted with caution. Level of Evidence: III.
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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 | 0.008 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".