Outcomes in Multidisciplinary Team-based Approach in Geriatric Hip Fracture Care: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: This systematic review analyzes the literature on the treatment of geriatric hip fractures by a multidisciplinary hip fracture service including geriatricians/internists and orthopaedic surgeons and what impact this has on patient outcomes. METHODS: A systematic review of several databases was conducted according to PRISMA guidelines. Studies comparing an orthopaedic-led care model versus a coordinated orthogeriatrics care model or a geriatrics-led care model to treat hip fractures with reported outcomes for time to surgery, length of stay, readmission rates, and postoperative mortality were included. RESULTS: Seventeen articles fitting the inclusion criteria were included. Differences between the results of an orthopaedic-led care model versus a coordinated orthogeriatrics care model or a geriatrics-led care model were assessed using chi-squared tests. With patients admitted under a coordinated orthogeriatrics care model or a geriatrics-led care model, there is a statistically significant decrease in time to surgery (P = 0.045), length of stay (P = 0.0036), and postoperative mortality rates (P = 0.0034). CONCLUSIONS: Although a heterogeneous group of studies, the aggregate data from several studies using an orthogeriatrics care model or a geriatrics-led care model trend toward improvements across several clinical and cost-related outcome measures: decreased time to surgery, shorter length of stay, improved postoperative clinical outcomes, decreased mortality, and lower cost.
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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 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".