Tarsal coalition: Systematic review of arthroscopic management
Bibliographic record
Abstract
INTRODUCTION: The standard of care in the treatment of symptomatic tarsal coalitions is open surgery. However, certain limitations exist with open surgery, which include limited visualization leading to an incomplete resection and possible recurrence of the tarsal coalition. Arthroscopic tarsal coalition resection (TCR) is an alternative that is gaining traction, primarily as the safety profile of posterior ankle and subtalar arthroscopy is more well understood. This study provides a systematic review of the outcomes of arthroscopic TCR. METHODS: PubMed and Embase were searched independently by 2 reviewers for relevant articles based on predetermined criteria. The subject heading "tarsal coalition" and its related key terms were used. RESULTS: A total of 416 studies were revealed by the initial search, out of which only 6 met our predetermined inclusion criteria. A total of 42 patients (average age: 17.6 years) were treated with arthroscopic TCR. Thirty-three (78.6%) and 9 (21.4%) patients had talocalcaneal and calcaneonavicular coalitions, respectively. The follow-up period ranged from 6 to 60 months (mean: 26 months), and no recurrence of the tarsal coalition was detected (0.0%). Complications occurred in two (4.8%) patients only, with one developing complex regional pain syndrome (CRPS), and another patient developing hyperesthesia on the medial aspect of the calcaneus. CONCLUSION: Arthroscopic TCR is a feasible and effective surgery for both CNC and TCC with minimal complications and no disease recurrence at an average of 26 months follow-up. Future high-level of evidence studies are needed to compare the outcomes of open versus arthroscopic TCR.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".