Comparison of the clinical and radiological pictures in patients with congenital knee dislocation during treatment
Bibliographic record
Abstract
BACKGROUND: Congenital knee dislocation is a very rare musculoskeletal disease, and it occurs in approximately 1 per 100,000 live births. Many researchers note that the treatment of congenital knee dislocation should begin with conservative methods, during which various complications arise. AIM: This study aimed to compare the clinical and radiological classifications of congenital knee dislocation and show the results of the treatment of this deformation using a Von Rosen splint and plaster corrections. MATERIALS AND METHODS: The study included 58 patients (34 boys and 24 girls) with congenital knee dislocation (83 knee joints). Congenital knee dislocation with arthrogryposis and other systemic pathologies were not included in the study. Before treatment, all patients were assessed for the severity of congenital knee dislocation according to the Tarek and J. Leveuf system. To evaluate the obtained results, nonparametric statistics were used. To search for differences between groups, the KruskalWallis test and the median test were used. To search for correlations, Spearman coefficients were used. Statistica v10 was used for statistical analysis. RESULTS: Clinical and radiological data were compared. In both groups, after conservative treatment, excellent and good results were obtained in nearly 98% and satisfactory in 2%. After conservative therapy, surgical treatment was required in 2 of 37 knee joints with the initial severity of Tarek III deformity. CONCLUSIONS: The severity of the deformity according to the Tarek system makes it possible to predict the effectiveness of the conservative treatment of congenital knee dislocation at a statistically significant level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".