Failure of Split Posterior Tibial Tendon Transfer in Cerebral Palsy Complex Foot Deformities: A Review of Failure Definitions and Risk Factors for Failure
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review examines variability in failure and recurrence rates following split posterior tibial tendon transfer (SPOTT) for spastic equinovarus deformity (SED) in children with cerebral palsy (CP). It evaluates patient-specific and surgical risk factors contributing to poor outcomes and assesses the inconsistent definitions of failure across the literature. RECENT FINDINGS: Across the seven included studies, failure was more common in patients under the age of 8, non-ambulatory individuals, and those with quadriplegic CP. Surgical contributors included poor tendon tensioning, residual spasticity, over- or under-correction, and untreated bony deformities. Although modified techniques demonstrated improved outcomes, the risk of recurrence was not completely eliminated. All studies consistently lacked standardized definitions of surgical failure and recurrence, limiting cross-study comparability. Postoperative management strategies-particularly structured bracing protocols and delaying surgery until after age 8-were associated with more favorable outcomes. SPOTT remains a viable surgical option for dynamic SED in children with CP, but long-term success is highly dependent on careful patient selection, surgical expertise, and consistent postoperative care. Inconsistent definitions of recurrence and failure remain a major barrier to improving clinical outcomes and conducting meaningful comparative research. To enhance clinical decision-making and guide future studies, a standardized grading system should be urgently developed and adopted in the field.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".