Ulnar Shortening Versus Distal Radius Corrective Osteotomy in the Management of Ulnar Impaction After Distal Radius Malunion
Bibliographic record
Abstract
BACKGROUND: Distal radius malunions lead to functional deficits. This study compares isolated ulnar shortening osteotomy (USO) to distal radius osteotomy (DRO) for the treatment of ulnar impaction syndrome following distal radius malunion. METHODS: We retrospectively reviewed 11 patients with extra-articular distal radius malunions treated for ulnar impaction with isolated USO. This group was compared to a 1:1 age- and sex-matched cohort treated with isolated DRO for the same indication. Pain visual analog scale (VAS), wrist motion, grip strength, radiographic parameters, and perioperative complications were analyzed. Mean follow-up was 14.8 months. RESULTS: VAS scores improved. Wrist range of motion improved in both cohorts with the exception of radial deviation, pronation, and supination in the USO cohort, which decreased from a mean of 17°-16°, 67°-57°, and 54°-52°, respectively. There was no significant difference between groups in regard to change in pain or range of motion, with the exception of pronation and ulnar deviation. The mean tourniquet time was shorter in the USO group. The final ulnar variance was 1.8 mm negative in the USO group and 1.1 mm positive in the DRO group. There was 1 reoperation following USO for painful nonunion, while there were 2 reoperations following DRO for persistent ulnar impaction. CONCLUSIONS: An improvement in range of motion, grip strength, and VAS with restoration of the radioulnar length relationship was observed in both cohorts. USO is a simpler procedure with a shorter tourniquet time that can be an attractive alternative to DRO for ulnar impaction syndrome after distal radius malunions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.000 |
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".