CORR Insights®: Meniscal Injury After Adolescent Anterior Cruciate Ligament Injury: How Long Are Patients at Risk?
Bibliographic record
Abstract
Where Are We Now? Compelling data support our current understanding of ACL injuries and associated pathologies in the adolescent athlete. These data confirm that among athletic adolescent patients treated nonoperatively for complete ACL tears, the frequency of meniscal and chondral damage from recurrent episodes of instability is high [1, 3-8, 16-18]. Additionally, delay in surgical treatment of as little as 12 weeks leads to increasing numbers of irreparable medial meniscus tears and lateral compartment articular cartilage injuries [11]. Historically, there has been a controversy regarding balancing the risks associated with delay in surgery with the risks of physeal injury and growth disturbance during surgical reconstruction in the skeletally immature athlete. With improvements in surgical technique and instrumentation, the risk of growth disturbance seems lower [6, 12, 13]. As a result, many investigators in this field have concluded that for this high-risk group of both skeletally immature and mature adolescent athletes, the “conservative treatment” in most patients actually is ACL reconstruction. The challenge is to define more effectively the population at risk, and to identify the small subgroup of adolescents who may benefit from nonoperative treatment. Where Do We Need To Go? We must remain cognizant of the fact that for the individual and the greater public health, the incorrect decision in this setting will lead to long-term disability and diminish the life span of the knee in this young cohort of patients. A more effective triage system within various national and international healthcare delivery systems should be developed so high-risk populations are diagnosed and treated in a timely manner. Finally, we must develop more effective return to play assessments following ACL reconstruction, as the data demonstrates unacceptably high rates of ipsilateral and contralateral injuries in this high-risk group of athletes [2, 9, 10, 14, 15]. In the paper at hand, Guenther and colleagues attempted to study longer-term patterns of meniscal tear evolution between time of MRI (average delay 77 days) and time of surgery (average delay 342 days) within the Canadian healthcare system, and its attendant delays in healthcare delivery. Guenther and colleagues concluded that medial meniscus tears, namely bucket handle tears, increased steadily in adolescent athletes even 1 year after ACL injury. One of the limitations of this paper is the relative absence of data regarding the clinical course and treatment of these adolescents during the delay between the times of injury, imaging, and surgical reconstruction. Were these adolescents braced? Did they modify their activities and refrain from field and court sports? Did they have ongoing symptoms of pain and recurrent instability? An additional limitation of this study is that as a retrospective review, the authors only included the patients who had an ACL reconstruction. We do not know what the denominator was during this time frame, specifically, how many adolescents with ACL injury did not proceed to ACL reconstruction, and how did they do? The answers to questions like these will be important in directing our future efforts on behalf of this population. How Do We Get There? One way to further refine our understanding of the natural history of ACL injuries in the adolescent would be to define what we believe might be the characteristics of a low-risk cohort (though some would argue that there is no such cohort in this population), and to follow them prospectively. In an ideal healthcare delivery system, every adolescent sustaining an acute ACL tear would be evaluated on the day of injury by a capable athletic trainer or team physician. As we know, an ACL tear (as well as associated ligament injuries) can be determined upon physical examination. These adolescents would then be placed on crutches (as most have transchondral fractures) and braced until an MRI was obtained to evaluate for associated pathology in the form of meniscus tears or articular cartilage injuries. The MRI should be obtained as soon after the injury as possible. There would be two treatment arms in the study. The first arm of the study would include adolescents determined to be at low-risk — those with isolated ACL tears and uninvolved in sports, dance and other at risk activities (or willing to forego them indefinitely), and adolescents with relatively low-grade associated injuries. This cohort would then be placed into the nonoperative arm of the study and followed for two years or until they required surgery for recurrent injury. During those 2 years, followup MRIs would be obtained at 3, 6, 9, 12, 18, and 24 months postinjury. These images would be assessed for increasing meniscal and or articular cartilage damage. This type of study would potentially identify a cohort of adolescents that may benefit from nonoperative treatment. The second arm of the study would follow those adolescents treated surgically. An ideal healthcare delivery system would provide surgical treatment following a short course of preoperative physical therapy (assuming the absence of associated pathology requiring immediate treatment — bucket handle meniscal tears and/or displaced chondral fragments). Once the adolescent is identified as a surgical candidate, the data is once again overwhelmingly supportive of treatment in a timely manner, as delay will lead to increasing rates of meniscal and articular cartilage damage. This cohort of reconstructed adolescents would be followed until at least 1 year after return to play. A validated and effective return to play assessment tool needs to be developed and would likely include objective measures such as KT 1000 test, isokinetic data, functional tests, and assessment of agility activities using qualitative video analysis paired with quantitative kinematic and kinetic data possibly obtained in a motion analysis laboratory setting.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.013 |
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".