Intra-Articular Cytokine Levels in Adolescent Patients after Anterior Cruciate Ligament Tear
Bibliographic record
Abstract
The treatment of anterior cruciate ligament (ACL) injuries in children and adolescents is challenging. Preclinical and clinical studies investigated ACL repairing techniques in skeletally immature subjects. However, intra-articular bioenvironment following ACL tear has not yet been defined in skeletally immature patients. The aim of this study was to measure cytokine concentrations in the synovial fluid in adolescent population. Synovial levels of IL-1 β , IL-1ra, IL-6, IL-8, IL-10, and TNF- α were measured in 17 adolescent patients (15 boys) with ACL tears who underwent ACL reconstruction including acute (5), subacute (7), and chronic (5) phases. Femoral growth plates were classified as “open” in three patients, “closing” in eight, and “closed” in six. Eleven patients presented an ACL tear associated with a meniscal tear. The mean Tegner and Lysholm scores (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi mathvariant="normal">m</mml:mi><mml:mi mathvariant="normal">e</mml:mi><mml:mi mathvariant="normal">a</mml:mi><mml:mi mathvariant="normal">n</mml:mi><mml:mo>±</mml:mo><mml:mi mathvariant="normal">S</mml:mi><mml:mi mathvariant="normal">D</mml:mi></mml:math>) of all patients were 8 ± 1 and 50.76 ± 26, respectively. IL-8, TNF- α , and IL-1 β levels were significantly greater in patients with “open” physes. IL-1ra and IL-1 β levels were significantly higher in patients with ACL tear associated with a meniscal tear. Poor Lysholm scores were associated with elevated IL-6 and IL-10 levels. IL-10 levels positively correlated with IL-6 and IL-8 levels, whereas TNF- α concentration negatively correlated with IL-6 levels. Skeletally immature patients with meniscal tears and open growth plates have a characteristic cytokine profile with particularly elevated levels of proinflammatory cytokines including IL-8, TNF- α , and IL-1 β . This picture suggests that the ACL tear could promote an intra-articular catabolic response in adolescent patients greater than that generally reported for adult subjects. The study lacks the comparison with synovial samples from healthy skeletally immature knees due to ethical reasons. Overall, these data contribute to a better knowledge of adolescent intra-articular bioenvironment following ACL injuries.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".