A scoping review of the proximal humerus fracture literature
Bibliographic record
Abstract
BACKGROUND: Proximal humerus fractures are a common fragility fracture that significantly affects the independence of older adults. The outcomes of these fractures are frequently disappointing and previous systematic reviews are unable to guide clinical practice. Through an integrated knowledge user collaboration, we sought to map the breadth of literature available to guide the management of proximal humerus fractures. METHODS: We utilized a scoping review technique because of its novel ability to map research activity and identify knowledge gaps in fields with diverse treatments. Through multiple electronic database searches, we identified a comprehensive body of proximal humerus fracture literature that was classified into eight research themes. Meta-data from each study were abstracted and descriptive statistics were used to summarize the results. RESULTS: 1,051 studies met our inclusion criteria with the majority of research being performed in Europe (64%). The included literature consists primarily of surgical treatment studies (67%) and biomechanical fracture models (10%). Nearly half of all clinical studies are uncontrolled case series of a single treatment (48%). Non-randomized comparative studies represented 12% of the literature and only 3% of the studies were randomized controlled trials. Finally, studies with a primary outcome examining the effectiveness of non-operative treatment or using a prognostic study design were also uncommon (4% and 6%, respectively). CONCLUSIONS: The current study provides a comprehensive summary of the existing proximal humerus fracture literature using a thematic framework developed by a multi-disciplinary collaboration. Several knowledge gaps have been identified and have generated a roadmap for future research priorities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.123 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.091 | 0.071 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".