Systematic Review of the Best Evidence in Intramedullary Fixation for Metacarpal Fractures
Bibliographic record
Abstract
BACKGROUND: Intramedullary (IM) fixation has been described as a reliable method of treatment for certain fracture patterns but has not been widely adopted into practice. The purpose of this study was to evaluate the literature comparing IM fixation to other forms of treatment for metacarpal fractures. METHODS: A systematic review was performed to identify studies investigating the treatment of metacarpal fractures using IM fixation. Inclusion and exclusion criteria were predetermined. Two reviewers independently identified appropriate articles for review based on the criteria. Primary outcome measures were range of motion (ROM) (Styf et al., Rev Chir Orthop Reparatrice Appar Mot 74(Suppl 2):268-270, 2008) and complications. Secondary outcomes included loss of reduction, grip strength, Disabilities of arm, shoulder and hand (DASH) scores, radiographic measures and pain scores. RESULTS: Eight studies were eligible for review. Studies were of level II-IV evidence, and captured a total of 435 patients. The ROM post-operatively was found to be greater in the IM group in half of the studies. IM fixation trended toward higher complication rates in one study, but no differences were statistically significant. IM fixation fared similarly or superiorly to its competitor in each of the secondary outcomes. A formal meta-regression analysis was not possible given the heterogeneity of studies. CONCLUSIONS: IM fixation may have a role in the treatment of certain metacarpal fractures. No conclusive recommendations can be made based on the available studies included in this literature search. Further study of this technique and its applications using high level evidence is warranted.
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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 | 0.022 | 0.095 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.011 |
| Bibliometrics | 0.024 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".