Nonoperative Treatment of Proximal Humerus Fractures: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Proximal humerus fractures are common in the setting of osteopenia and osteoporosis and can often be treated nonoperatively. There are few studies that evaluate the long-term outcomes of nonoperative treatment of these fractures. We performed a systematic review of the literature to examine the results of nonoperative treatment of proximal humerus fractures. METHODS: The PubMed search engine and EMBASE database were used. Inclusion criteria were: 1) proximal humerus fractures resulting from trauma; 2) age older than 18 years; 3) more than 15 patients in the study; 4) greater than 1 year follow-up; 5) at least one relevant functional outcome score; and 6) a quality outcome score of at least a 5 of 10 according to previously published scoring system. RESULTS: We identified 12 studies that included 650 patients with a mean age of 65.0 years (range, 51-75 years) and a mean follow-up of 45.7 months (range, 12-120 months). There were 317 one-part fractures, 165 two-part fractures, 137 three-part fractures, and 31 four-part fractures. The rate of radiographic union was 98% and the complication rate 13%. The average range of motion reported in five studies was 139° forward flexion, 48° external rotation, and 52° internal rotation. The average Constant score reported in six studies was 74 (range, 55-81). Varus malunion was the most common complication reported, whereas avascular necrosis was uncommon (13 cases). CONCLUSIONS: We conclude that our systematic review of the literature on the nonoperative treatment of proximal humerus fractures demonstrates high rates of radiographic healing, good functional outcomes, and a modest complication rate.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".