The Effect of Socioeconomic Factors on Outcomes of Distal Radius Fractures: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Socioeconomic factors are known to affect outcomes for both medical and surgical conditions. The purpose of this systematic review was to assess the current evidence regarding the effect of socioeconomic factors such as income, geographic location, educational level, and occupation on clinical outcomes after distal radius fractures. METHODS: A systematic search strategy was performed to identify studies commenting on the effect of socioeconomic factors on clinical outcomes following open or closed distal radius fracture repair. Abstract and full-text screening was performed by 2 independent reviewers, and articles were evaluated by Structured Effectiveness Quality Evaluation Scale (SEQES). Treatment outcomes of interest included, but were not limited to, pain, function, range of motion, and grip strength. RESULTS: There were 1745 studies that met our inclusion and exclusion criteria for abstract screening. Of these, 48 studies met our inclusion criteria for full-text screening and 20 studies met our criteria for quality analysis with the SEQES score. There were 3 studies of high quality, 16 of moderate quality, and 1 of low quality. Meta-analyses were not possible due to the variability in outcomes of interest across papers. CONCLUSIONS: Patient factors indicative of socioeconomic status are relevant predictors of functional outcome after distal radius fractures. There is currently limited evidence in this area of research, and further examination should be considered to improve outcomes from a patient and system standpoint.
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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".