Radiocarpal and midcarpal joint congruency after perilunate dislocations and fracture-dislocations: a cross-sectional study
Bibliographic record
Abstract
The purpose of this study was to evaluate carpal joint contact patterns after perilunate injuries and potential associations between functional and radiographic outcomes. Twenty-two patients with a computed tomography (CT) scan at least 2 years postoperatively were reviewed (mean follow-up 15 years). Assessment of carpal degenerative changes was done using Kellgren–Lawrence grading and CT-derived joint space area, which was calculated as the total area with interbone distance less than 2 mm. Increased joint space area signified a greater area with joint space narrowing and cartilage loss. Fifteen patients had severe joint space narrowing at the scaphocapitate and capitolunate joints. Nine and seven patients had severe narrowing at the radiolunate and radioscaphoid joints, respectively. Degenerative changes did not follow a typical scapholunate advanced collapse pattern. Increased scaphocapitate joint space area was associated with worse Patient Rated Wrist Evaluation scores ( r = −0.47, p = 0.02) and visual analogue scale pain scores ( r = −0.44, p = 0.03). This study suggests that patients with more severe degenerative changes after perilunate injuries may have worse functional outcomes. Level of evidence: IV
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".