Equino-plano-valgus foot in cerebral palsy – clinical principles and surgical techniques review (world perspective). Report from the 5th edition of the Transatlantic Orthopedic Surgery Webinar 2023
Bibliographic record
Abstract
Introduction. The fifth edition of the Transatlantic Orthopedic Surgery Webinar 2023 occurred on December 4, 2023. The webinar’s main topic was treating equino-plano-valgus foot in children with cerebral palsy (CP). The event included speakers from Austria, Australia, China, India, Canada, Germany, Poland, Sweden, Turkey, the USA and the UK. Results. The first general session presented epidemiology, biomechanics, muscle function, equinoplano- valgus foot prevention options, and the Silverskiöld test in clinical assessment. It also discussed the principles of deformation treatment, options for orthotic treatment, and pathology treatment in adults suffering from CP. The surgical sessions presented comprehensive surgical techniques for the treatment of clubfoot equinus: sliding calcaneal osteotomy, lateral column lengthening with talonavicular arthrodesis, use of an expandable cage for the lateral column lengthening, double arthrodesis with the transfer of the peroneal muscles, percutaneous soft tissue release with/without arthroereisis, lateral column lengthening with arthroereisis, Grice procedure with talonavicular arthrodesis, lateral column lengthening with medial cuneiform bone plantarflexion osteotomy, lateral column lengthening with duplication of the talonavicular capsule, talonavicular and calcaneocuboid arthrodesis, transfer of the tibialis anterior muscle to the peroneal tertius muscle. The second general session presented methods of assessing the results of clubfoot treatment and postoperative rehabilitation protocols involving upright positioning and walking. Conclusion. The most important conclusions from the event are: clinical assessment and understanding the pathophysiology of the defect is crucial for its proper treatment; non-surgical treatment is recommended under the age of 6; between the ages of 6 and 14, surgical methods that preserve joint function predominate; after the age of 14 a large percentage of patients require performing joint arthrodesis. Nevertheless, arthrodesis should be avoided to correct flexible deformities and to treat patients with high functional requirements. The webinar audience included 583 people from 50 countries. Most participants came from Poland, Spain, Turkey, and Great Britain.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".