Management of Proximal Humeral Fractures in Adults: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: Differences in function, pain, and reoperation rates were compared between the following treatment options: (1) operative vs. nonoperative treatment and (2) various surgical treatments including open reduction internal fixation, intramedullary nail, hemiarthroplasty (HA), and reverse shoulder arthroplasty (RSA). DATA SOURCES: MEDLINE, Embase, and Cochrane were searched through February 1, 2022. All English-language randomized trials comparing operative and nonoperative treatment of proximal humeral fractures with a control group in patients 18 years or older were included. DATA EXTRACTION: Demographic data, functional and pain scores and re-operation rates were extracted. Study quality was determined with the Cochran risk of bias tool and the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE). Heterogeneity was determined with the I-squared statistic. DATA SYNTHESIS: Meta-analysis of included studies using mean difference and odds ratios where appropriate. CONCLUSIONS: Surgical treatment with either locked plates or HA results in similar functional scores and pain outcomes as nonoperative treatment, although plates were associated with higher reoperation rates in 3-part and 4-part fractures. In 3-part and 4-part fractures, RSA results in higher function and pain scores compared with HA. Further high-quality trials should focus on RSA, and further study is required to better define the role of open reduction internal fixation in the younger patient population. LEVEL OF EVIDENCE: Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.006 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".