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...
| Published in: | American Journal of Sports Medicine Vol. 50; no. 13; pp. 3544 - 3557 |
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| Main Authors: | , , , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Sage Publications Inc.
Nov2022
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159997689&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159997689 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03635465 ASM jtl: American Journal of Sports Medicine issn: 03635465 maglogo: Y pubinfo: dt: Nov2022 vid: 50 iid: 13 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 159997689 159406377 159997689 159997689 10.1177/03635465221124258 159997689 ppf: 3544 ppct: 13 formats: tig: 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 refInfo: holdings: @attributes: islocal: N |
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