144 Good results of surgically treated pediatric knee ligament injuries in Denmark 2011–20 at one-year follow-up
Bibliographic record
Abstract
Introduction Prospective data on treatment outcome from unselected cohorts of children with anterior cruciate ligament (ACL) injury are sparse. Since 2011 the surgical treatment of children with ACL injury in Denmark has been concentrated at two centers. The aim was to present one-year results after pediatric ACL-reconstruction in Denmark for the period 2011–20. Materials and Methods Consecutive children (< 16 years old) who had an ACL-reconstruction were prospectively followed with patient reported outcome measure Pedi-IKDC, pivot shift and instrumented laxity before surgery and one year later. One-year follow-ups were performed by independent observers. Results A total of 518 children had an ACL-reconstruction. Median age: 14.6 years (range 8–16) and 45% were girls. A quadruple semitendinosus or a doubled semitendinosus-gracilis autologous tendon was used as graft in all but one child. Pedi-IKDC score was 57.0 preoperatively and 85.7 at 1-year (maximum score 92). Side-to-side difference of instrumented anterior laxity was 4.25 mm preoperatively and 1.3 mm at follow-up. Pivot-shift was preoperatively/at 1-year: no pivot: 3/22%, grade 1: 20/56%, grade 2: 74/21%, and grade 3: 3/1%. Two (0.3%) had an operatively treated deep infection, 3 (0.5%) were treated for reduced range of motion, 2 (0.3%)% for a cyclops, and 4 (0.7%) had a rupture of the graft. Conclusion ACL reconstruction resulted in a large increase in Pedi-IKDC score, a large decrease of instrumented laxity, and a reduction of pivot shift. Complication rate was low and 1-year re-rupture rate was 0.7%.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".