Distal rectus femoris surgery in children with cerebral palsy: Results of a Delphi consensus project
Bibliographic record
Abstract
PURPOSE: The purpose of this study was for an international panel of experts to establish consensus indications for distal rectus femoris surgery in children with cerebral palsy (CP) using a modified Delphi method. METHODS: The panel used a five-level Likert scale to record agreement or disagreement with 33 statements regarding distal rectus femoris surgery. The panel responded to statements regarding general characteristics, clinical indications, computerized gait data, intraoperative techniques and outcome measures. Consensus was defined as at least 80% of responses being in the highest or lowest two of the five Likert ratings, and general agreement as 60% to 79% falling into the highest or lowest two ratings. There was no agreement if neither threshold was reached. RESULTS: Consensus or general agreement was reached for 17 of 33 statements (52%). There was general consensus that distal rectus femoris surgery is better for stiff knee gait than is proximal rectus femoris release. There was no consensus about whether the results of distal rectus femoris release were comparable to those following distal rectus femoris transfer. Gross Motor Function Classification System (GMFCS) level was an important factor for the panel, with the best outcomes expected in children functioning at GMFCS levels I and II. The panel also reached consensus that they do distal rectus femoris surgery less frequently than earlier in their careers, in large part reflecting the narrowing of indications for this surgery over the last decade. CONCLUSION: This study can help paediatric orthopaedic surgeons optimize decision-making for, and outcomes of, distal rectus femoris surgery in children with CP. LEVEL OF EVIDENCE: V.
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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 | 0.072 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".