Retrograde Intramedullary Pinning of Metacarpal Fractures Through the Collateral Recess
Bibliographic record
Abstract
There are several common types of fixations for metacarpal fractures: pins, plates, lag, and intramedullary (IM) screws. The advantages of pins are that they are ubiquitous, cost-effective, have shorter operative times, and preserve soft tissues, thereby minimizing adhesions. In this article, we describe metacarpal fracture fixation utilizing the technique of retrograde IM pinning through collateral recess access. We present the postoperative outcomes of our patients who underwent metacarpal fracture fixation utilizing this technique. Details of the fractures, patient comorbidities, demographics, and postoperative outcomes were gathered. Primary outcomes investigated were nonunion, malunion, need for revision, and range of motion (ROM). A total of 29 fractures in 14 patients were included, with multiple fractures present in 8 patients. The fractures were open in 8 cases. The orientation of the fracture was transverse in 22 cases and oblique in 7 with comminution noted in 13 fractures. Full ROM was obtained in 15 digits with 6 digits noted to have a good ROM and 6 digits still undergoing therapy. There were no nonunions noted and only one malunion. In conclusion, retrograde, double IM pinning through collateral recess access represents a reliable, cost-effective, and minimally traumatic method of metacarpal fixation, including carpometacarpal fracture dislocations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".