Outcomes of Primary Fusion vs. Reconstruction of Pediatric Cavus Foot in Charcot-Marie-Tooth Disease: A Systematic Review
Bibliographic record
Abstract
Background/Objectives: Charcot-Marie-Tooth (CMT) disease, the most common hereditary peripheral neuropathy, often causes cavovarus foot deformity in children. Surgical interventions to correct deformity or improve function can involve either primary fusion or reconstruction. However, the optimal surgical approach remains contested. This systematic review aims to present and evaluate existing data on both fusion and reconstruction surgical interventions in treating pediatric CMT cavus foot. Methods: A PRISMA-guided search of five electronic databases was conducted (from inception to 17 February 2025). Studies were eligible if they reported surgical outcomes for CMT pediatric patients (≤18 years) with cavovarus foot treated by primary fusion or reconstruction. Titles, abstracts and full texts were screened by four independent reviewers, and data were extracted on patient demographics, procedures, follow-up, functional scores, radiographic correction and complications. Results: Fourteen studies met inclusion criteria, encompassing 169 patients and 276 feet, with a mean age at surgery of ~13.5 years. Nine studies evaluated joint-sparing reconstruction, three assessed primary fusion, and two combined both reconstruction and fusion. Both interventions yielded improved outcomes post-operatively. Reconstruction generally produced high patient satisfaction and near-normal radiographic parameters but carried recurrence or reoperation rates of 10–40%. Fusion provided durable correction of rigid deformities but was associated with nonunion, adjacent joint arthritis and higher revision rates. Conclusions: Joint-sparing reconstruction is an effective first-line approach for flexible cavovarus deformities in pediatric CMT patients, while fusion should be reserved for severe, rigid or recurrent cases. A patient-specific staged approach is recommended, and higher-quality comparative studies are needed to refine surgical decision-making.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".