Patient-Reported Outcomes Improve after Hypothenar Fat Flap for the Treatment of Recurrent Carpal Tunnel Syndrome
Bibliographic record
Abstract
Background: Recalcitrant carpal tunnel syndrome (CTS) can present with persistent or recurrent symptoms after carpal tunnel release (CTR). A common aetiology for recurrent CTS is the development of perineural adhesions due to excess scarring. The hypothenar fat pad flap (HFPF) has been described to decrease the amount of scarring formed after revision CTR. Herein, we present a prospective evaluation of these patients. Methods: A prospective series of consecutive patients by a single surgeon with recurrent CTS was conducted. All patients had at least 3 months follow-up. Patients received a revision open CTR with HFPF. The primary outcome was the Boston Carpal Tunnel Questionnaire (BCTQ). Secondary outcomes included pain and satisfaction on visual analogue scale, range of motion, grip strength, patient-reported outcomes and complications. Clinical outcomes were compared between preoperative and postoperative intervals using paired t-tests, with significance defined as p < 0.05. Results: Fifteen wrists (14 patients) were recruited for the study. Patients were predominantly male (n = 9; 66%). Revision open CTR with HFPF was performed a median of 42 months (range: 4–300 months) post primary CTR. Patients demonstrated improved patient-reported outcomes with significantly improved BCTQ pain score (p < 0.01), Patient-Rated Wrist and Hand Evaluation (p < 0.01) and QuickDASH (p < 0.001). Two patients in the series reported postoperative complications; however, there was no incidence of donor site morbidity recorded. Conclusions: Revision open CTR with hypothenar fat pad flap is associated with decreased pain, high patient satisfaction and improved functional measures compared to pre-operative status. Level of Evidence: Level IV (Therapeutic)
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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 | 0.001 | 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) | 0.002 | 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".