Patient Satisfaction with Pisiform Excision for Pisotriquetral Instability or Arthritis: A Prospective Review
Bibliographic record
Abstract
Abstract Background Pisotriquetral pain and instability is an elusive cause of ulnar-sided wrist pain. Initial treatment of chronic pisotriquetral pathology should involve a trial of nonoperative therapy such as neutral wrist splint, anti-inflammatories, and intra-articular steroid injections. The mainstay of surgical management of pisotriquetral pain is pisiform excision. Purpose This prospective study seeks to understand patient satisfaction after pisiform excision in patients with isolated pisotriquetral pathology. Patients and Methods A consecutive series of nine cases of pisiform excision was performed by the senior surgeon. The primary outcome measure was determined a priori to be the Patient-Rated Wrist Evaluation (PRWE) score. Wrist range of motion, grip strength, and QuickDASH (shortened version of Disabilities of the Arm, Shoulder and Hand) scores were also collected preoperatively and at 3 and 12 months postoperatively as secondary outcome measures. Results There was a very rapid improvement in the PRWE by 3 months, which was maintained at 12 months. The QuickDASH score was slower to improve, with a significant improvement by 12 months. There was no change in grip strength or wrist range of motion at any time point. Conclusion Pisiform excision results in a very rapid improvement of symptoms and should be considered in cases of pisotriquetral instability or arthritis that fail conservative management. Level of Evidence Level IV, case series.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".