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.

Background: Surgical 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...

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Published in:American Journal of Sports Medicine Vol. 50; no. 13; pp. 3544 - 3557
Main Authors: Lu, Yining, Jurgensmeier, Kevin, Till, Sara E., Reinholz, Anna, Saris, Daniel B.F., Camp, Christopher L., Krych, Aaron J.
Format: research tables/charts Journal Article
Published: Sage Publications Inc. Nov2022
Online Access:View this record in EBSCOhost
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      dt: Nov2022
      vid: 50
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        atl: 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.
      aug:
        au:
          Lu, Yining
          Jurgensmeier, Kevin
          Till, Sara E.
          Reinholz, Anna
          Saris, Daniel B.F.
          Camp, Christopher L.
          Krych, Aaron J.
        affil: Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota, USA
      sug:
        subj:
          Early Intervention
          Anterior Cruciate Ligament Reconstruction
          Meniscal Injuries Risk Factors
          Risk Assessment
          Treatment Delay
          Anterior Cruciate Ligament Injuries Therapy
          Machine Learning
          Anterior Cruciate Ligament Injuries Prognosis
          Human
          Comparative Studies
          Time Factors
          Prospective Studies
          Geographic Factors
          Algorithms
          Surgical Patients
          Treatment Outcomes
          Electronic Health Records
          Body Mass Index
          Age Factors
          Sex Factors
          Socioeconomic Factors
          Functional Status
          Occupations and Professions
          Comorbidity
          Male
          Female
          Adolescence
          Adult
          Middle Age
          Descriptive Statistics
          Adolescent: 13-18 years
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Male
          Female
      ab: Background: Surgical 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 Design: Cohort study; Level of evidence, 3. Methods: A 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 c -statistic, calibration, and Brier score. Model interpretability was enhanced using global variable importance and partial dependence curves. Results: The 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 (P =.09); subgroup analysis revealed the shortest periods of meniscal survival in patients undergoing delayed ACLR. The random survival forest algorithm achieved excellent predictive performance for the ACLR cohort, with an out-of-bag c -statistic of 0.80 and a Brier score of 0.11. Significant variables for risk of meniscal tear for the ACLR cohort included time to return to sports or activity ≤350 days, time to surgery ≥50 days, age at injury ≤40 years, and high-impact or rotational landing sports, whereas those in the nonoperative cohort model included time to RTS ≤200 days, visual analog scale pain score >3 at consultation, hypermobility, and noncontact sports. Conclusion: Delayed 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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