ArticleFrontiers in surgery2018
Current Strategies and Future Directions to Optimize ACL Reconstruction in Adolescent Patients.
Article in Frontiers in surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- All-epiphyseal anterior cruciate ligament reconstruction produces good functional outcomes and low complication rates in pediatric patients: a systematic review.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2020Pooled it
- Article
- The Double-Edged Sword: Anterior Cruciate Ligament Reconstructions on Adolescent Patients-Growth Plate Surgical Challenges and Future Considerations.Journal of clinical medicine · 2024Review
- Reconstruction of chronic anterior cruciate ligament rupture using the ligament advanced reinforcement system artificial ligament-comparisons between patients over 50 years and under 50 years.Annals of translational medicine · 2023Article
- A Review on Finite Element Modeling and Simulation of the Anterior Cruciate Ligament Reconstruction.Frontiers in bioengineering and biotechnology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The incidence of anterior cruciate ligament (ACL) injuries in the pediatric population has risen in recent years. These injuries have historically presented a management dilemma in skeletally immature patients with open physes and significant growth remaining at time of injury. While those nearing skeletal maturity may be treated with traditional, transphyseal adult techniques, these same procedures risk iatrogenic damage to the growth plates and resultant growth disturbances in younger patients with open physes. Moreover, conservative management is non-optimal as significant instabilities of the knee remain. Despite the development of physeal-sparing reconstructive techniques for younger patients, there remains debate over which procedure may be most suitable on a patient to patient basis. Meanwhile, the drivers behind clinical and functional outcomes following ACL reconstruction remain poorly understood. Therefore, current strategies are not yet capable of optimizing surgical ACL reconstruction on an individualized basis with absolute confidence. Instead, aims to improve surgical treatment of ACL tears in skeletally immature patients will rely on additional approaches in the near future. Namely, finite element models have emerged as a tool to model complex knee joint biomechanics. The inclusion of several individualized variables such as bone age, three dimensional geometries around the knee joint, tunnel positioning, and graft tension collectively present a possible means of better understanding and even predicting how to enhance surgical decision-making. Such a tool would serve surgeons in optimizing ACL reconstruction in the skeletally immature individuals, in order to improve clinical outcomes as well as reduce the rate of post-operative complications.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.