ArticleThe American journal of sports medicine2022
Early ACLR and Risk and Timing of Secondary Meniscal Injury Compared With Delayed ACLR or Nonoperative Treatment: A Time-to-Event Analysis Using Machine Learning.
Article in The American journal of sports medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.
- Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy performance: a systematic review.BMC musculoskeletal disorders · 2025Pooled it
- Optimal Timing of Anterior Cruciate Ligament Reconstruction in Patients With Anterior Cruciate Ligament Tear: A Systematic Review and Meta-analysis.JAMA network open · 2022Pooled it
- High failure rate in meniscal repair when preceding anterior cruciate ligament reconstruction: An analysis of two-stage surgery for concomitant ACL injury and traumatic meniscus tear.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
- No difference in ACL revision rates between hamstring and patellar tendon autograft in patients with ACL-R and a concurrent meniscal injury irrespective of meniscal treatment.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
- More knee reinjuries after ACL reconstruction compared to nonsurgical treatment of the ACL. A 2-year follow-up of the NACOX prospective cohort study.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
- Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis.British journal of sports medicine · 2025Article
- Return to Sport Following Anterior Cruciate Ligament Reconstruction: A Scoping Review of Criteria Determining Return to Sport Readiness.Current reviews in musculoskeletal medicine · 2025Article
- Factors Affecting Outcomes and Complications of Primary Anterior Cruciate Ligament Reconstruction: A Retrospective Study of 110 Patients.Orthopaedic journal of sports medicine · 2024Article
- Concomitant Popliteomeniscal Fascicles Tears Are Found in 21% of Professional Soccer Players With Acute Anterior Cruciate Ligament Injuries.Arthroscopy, sports medicine, and rehabilitation · 2024Article
- Graft Failure and Contralateral ACL Injuries After Primary ACL Reconstruction: An Analysis of Risk Factors Using Interpretable Machine Learning.Orthopaedic journal of sports medicine · 2024Article
- Graft failure within 2 years of isolated anterior cruciate ligament reconstruction is associated with increased risk of secondary meniscus tears.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2023Article
- IL-6 induces periostin production in human ACL remnants: a possible mechanism causing post-traumatic osteoarthritis.Journal of orthopaedic surgery and research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundSurgical and nonoperative management of anterior cruciate ligament (ACL) injuries seek to mitigate the risk of knee instability and secondary meniscal injury. However, the associated risk and timing of secondary meniscal tears have not been completely elucidated. PURPOSE: To compare risk and timing of secondary meniscal injury between patients receiving nonoperative management, delayed ACL reconstruction (ACLR), and early ACLR using a machine learning survival analysis. STUDY
designCohort study; Level of evidence, 3.
methodsA geographic database was used to identify and review records of patients with a diagnosis of ACL rupture between 1990 and 2016 with minimum 2-year follow-up. Patients undergoing ACLR were matched 1:1 with nonoperatively treated controls. Rate and time to secondary meniscal tear were compared using random survival forest algorithms; independent models were developed and internally validated for predicting injury-free duration in both cohorts. Performance was measured using out-of-bag
resultsThe study included 1369 patients who underwent ACLR and 294 patients who had nonoperative treatment. After matching, no significant differences in rates of secondary meniscal tear were found (
conclusionDelayed ACLR demonstrated the greatest long-term risk of meniscal injury compared with nonoperative treatment or early ACLR. Risk factors for decreased meniscal survival after ACLR included increased time to surgery, shorter time to return to sports or activity, older age at injury, and involvement in high-impact or rotational landing sports. Pending careful external validation, these models may be deployed in the clinical space to provide real-time insights and enhance decision making.
Indexed as
Identifiers
What OpenQuestion holds
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.