Aseptic Revision and Reoperation Risks After Meniscectomy at the Time of Anterior Cruciate Ligament Reconstruction

Female Sex, Older Age, Earlier Surgery, Anticoagulant Use, and Meniscal Repair Are Associated With Increased Risk of Manipulation Under Anesthesia or Lysis of Adhesions for Arthrofibrosis After Anterior Cruciate Ligament Reconstruction: A Systematic Review

PURPOSE

To determine what patient or surgical factors are associated with an increased risk of arthrofibrosis requiring manipulation under anesthesia (MUA) or lysis of adhesions (LOA) after anterior cruciate ligament reconstruction (ACLR).

METHODS

A systematic review was performed in adherence to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Cochrane, Embase, and Medline databases were searched for studies published through February 2023. Inclusion criteria were studies that identified risk factors for MUA and/or LOA after ACLR. Studies investigating arthrofibrosis after multiligamentous knee injuries or ACL repair were excluded.

RESULTS

Eleven studies including a total of 333,876 ACLRs with 4,842 subsequent MUA or LOA (1.45%) were analyzed. Increasing age was associated with an increased risk in 3 studies (P < .001, P < .05, P < .01) but was found to have no association another two. Other factors that were identified by multiple studies as risk factors for MUA/LOA were female sex (4 studies), earlier surgery (5 studies), use of anticoagulants other than aspirin (2 studies), and concomitant meniscal repair (4 studies).

CONCLUSIONS

In total, 1.45% of the patients who underwent ACLR and were included in this systematic review had to undergo a subsequent MUA/LOA to treat arthrofibrosis. Female sex, older age, earlier surgery, use of anticoagulants other than aspirin, and concomitant meniscal repair were associated with increased risk of MUA/LOA. The modifiable risks, including use of anticoagulants and time between injury and surgery, can be considered when making treatment decisions.

LEVEL OF EVIDENCE

Level IV, systematic review of Level III-IV studies.

Machine learning can accurately predict risk factors for all-cause reoperation after ACLR: creating a clinical tool to improve patient counseling and outcomes

PURPOSE

Identifying predictive factors for all-cause reoperation after anterior cruciate ligament reconstruction could inform clinical decision making and improve risk mitigation. The primary purposes of this study are to (1) determine the incidence of all-cause reoperation after anterior cruciate ligament reconstruction, (2) identify predictors of reoperation after anterior cruciate ligament reconstruction using machine learning methodology, and (3) compare the predictive capacity of the machine learning methods to that of traditional logistic regression.

METHODS

A longitudinal geographical database was utilized to identify patients with a diagnosis of new anterior cruciate ligament injury. Eight machine learning models were appraised on their ability to predict all-cause reoperation after anterior cruciate ligament reconstruction. Model performance was evaluated via area under the receiver operating characteristics curve. To explore modeling interpretability and radiomic feature influence on the predictions, we utilized a game-theory-based method through SHapley Additive exPlanations.

RESULTS

A total of 1400 patients underwent anterior cruciate ligament reconstruction with a mean postoperative follow-up of 9 years. Two-hundred and eighteen (16%) patients experienced a reoperation after anterior cruciate ligament reconstruction, of which 6% of these were revision ACL reconstruction. SHapley Additive exPlanations plots identified the following risk factors as predictive for all-cause reoperation: diagnosis of systemic inflammatory disease, distal tear location, concomitant medial collateral ligament repair, higher visual analog scale pain score prior to surgery, hamstring autograft, tibial fixation via radial expansion device, younger age at initial injury, and concomitant meniscal repair. Pertinent negatives, when compared to previous studies, included sex and timing of surgery. XGBoost was the best-performing model (area under the receiver operating characteristics curve of 0.77) and outperformed logistic regression in this regard.

CONCLUSIONS

All-cause reoperation after anterior cruciate ligament reconstruction occurred at a rate of 16%. Machine learning models outperformed traditional statistics and identified diagnosis of systemic inflammatory disease, distal tear location, concomitant medial collateral ligament repair, higher visual analog scale pain score prior to surgery, hamstring autograft, tibial fixation via radial expansion device, younger age at initial injury, and concomitant meniscal repair as predictive risk factors for reoperation. Pertinent negatives, when compared to previous studies, included sex and timing of surgery. These models will allow surgeons to tabulate individualized risk for future reoperation for patients undergoing anterior cruciate ligament reconstruction.

LEVEL OF EVIDENCE

III.

Risk Factors for Revision or Rerupture After Anterior Cruciate Ligament Reconstruction: A Systematic Review and Meta-analysis

BACKGROUND

The rerupture or need for revision after anterior cruciate ligament reconstruction (ACLR) is a serious complication. Preventive strategies that target the early identification of risk factors are important to reduce the incidence of additional surgery.

PURPOSE

To perform a systematic review and meta-analysis to investigate risk factors for revision or rerupture after ACLR.

STUDY DESIGN

Systematic review and meta-analysis; Level of evidence, 4.

METHODS

Literature searches were performed in PubMed, Embase, and Web of Science from database inception to November 2021 and updated in January 2022. Quantitative, original studies reporting potential adjusted risk factors were included. Odds ratios (ORs) were calculated for potential risk factors.

RESULTS

A total of 71 studies across 13 countries with a total sample size of 629,120 met the inclusion criteria. Fifteen factors were associated with an increase in the risk of revision or rerupture after ACLR: male sex (OR, 1.27; 95% CI, 1.14-1.41), younger age (OR, 1.07; 95% CI, 1.05-1.08), lower body mass index (BMI) (OR, 1.03; 95% CI, 1.00-1.06), family history (OR, 2.47; 95% CI, 1.50-4.08), White race (OR, 1.32; 95% CI, 1.08-1.60), higher posterolateral tibial slope (OR, 1.15; 95% CI, 1.05-1.26), preoperative high-grade anterior knee laxity (OR, 2.30; 95% CI, 1.46-3.64), higher baseline Marx activity level (OR, 1.07; 95% CI, 1.02-1.13), return to a high activity level/sport (OR, 2.03; 95% CI, 1.15-3.57), an ACLR within less than a year after injury (OR, 2.05; 95% CI, 1.81-2.32), a concomitant medial collateral ligament (MCL) injury (OR, 1.62; 95% CI, 1.31-2.00), an anteromedial portal or transportal technique (OR, 1.36; 95% CI, 1.22-1.51), hamstring tendon (HT) autografts (vs bone-patellar tendon-bone [BPTB] autografts) (OR, 1.60; 95% CI, 1.40-1.82), allografts (OR, 2.63; 95% CI, 1.65-4.19), and smaller graft diameter (OR, 1.21; 95% CI, 1.05-1.38). The other factors failed to show an association with an increased risk of revision or rerupture after ACLR.

CONCLUSION

Male sex, younger age, lower BMI, family history, White race, higher posterolateral tibial slope, preoperative high-grade anterior knee laxity, higher baseline Marx activity level, return to a high activity level/sport, an ACLR within less than a year from injury, a concomitant MCL injury, an anteromedial portal or transportal technique, HT autografts (vs BPTB autografts), allografts, and smaller graft diameter may increase the risk of revision or rerupture after ACLR. Raising awareness and implementing effective preventions/interventions for risk factors are priorities for clinical practitioners to reduce the incidence of revision or rerupture after ACLR.

Scoping Review on ACL Surgery and Registry Data

Purpose of Review

To present an overview of registry-based anterior cruciate ligament (ACL) research, as well as provide insight into the future of ACL registries.

Recent Findings

During the past decades, the ACL registries have had an important role in increasing our understanding of patients with ACL injuries and their treatment. The registry data has deepened our understanding of factors that have been associated with an increased risk of sustaining an ACL injury and for evaluation of treatment factors and their impact on patient-related outcomes. Recently, registry-based ACL research using artificial intelligence (AI) and machine learning (ML) has shown potential to create clinical decision-making tools and analyzing outcomes. Thus, standardization of collected data between the registries is needed to facilitate the further collaboration between registries and to facilitate the interpretation of results and subsequently improve the possibilities for implementation of AI and ML in the registry-based research.

Summary

Several studies have been based on the current ACL registries providing an insight into the epidemiology of ACL injuries as well as outcomes following ACL reconstruction. However, the current ACL registries are facing future challenges, and thus, new methods and techniques are needed to ensure further good quality and clinical applicability of study findings based on ACL registry data.

Minimizing the risk of graft failure after anterior cruciate ligament reconstruction in athletes. A narrative review of the current evidence

Anterior cruciate ligament (ACL) tear is one of the most common sport-related injuries and the request for ACL reconstructions is increasing nowadays. Unfortunately, ACL graft failures are reported in up to 34.2% in athletes, representing a traumatic and career-threatening event. It can be convenient to understand the various risk factors for ACL failure, in order to properly inform the patients about the expected outcomes and to minimize the chance of poor results. In literature, a multitude of studies have been performed on the failure risks after ACL reconstruction, but the huge amount of data may generate much confusion.The aim of this review is to resume the data collected from literature on the risk of graft failure after ACL reconstruction in athletes, focusing on the following three key points: individuate the predisposing factors to ACL reconstruction failure, analyze surgical aspects which may have significant impact on outcomes, highlight the current criteria regarding safe return to sport after ACL reconstruction.

Patient-Reported Outcome, Return to Sport, and Revision Rates 7-9 Years After Anterior Cruciate Ligament Reconstruction: Results From a Cohort of 2042 Patients

BACKGROUND

Long-term patient-reported outcome measures (PROMs), rates of return to sport, and revision risk after anterior cruciate ligament (ACL) reconstruction (ACLR) are not well understood.

PURPOSE

To provide long-term follow-up of PROMs, return-to-sport rates, and revision rates after ACLR and to identify predictors for poor outcome.

STUDY DESIGN

Case-control study; Level of evidence, 3.

METHODS

A total of 2042 patients were included in an institutional ACL registry (2009-2013) and longitudinally followed. PROMs were completed preoperatively and at all follow-up time points. Questions regarding return to sport and knee stability were completed at final follow-up. Predictors for poor outcome on the International Knee Documentation Committee (IKDC) score were estimated in a regression model incorporating risk factors such as patient characteristics, graft choice, and concomitant injuries. Revision rates and risk of subsequent non-ACL surgeries were calculated.

RESULTS

Autografts were used in 76% of the patients (patellar tendon, 62%; hamstring grafts, 38%). Allografts were used in 24% of patients. The questionnaires were returned by 1045 (51.2%) patients at a mean of 7.2 years (range, 5.0-9.8 years) after surgery. Improvements in IKDC score of >30 points were sustained for all patient categories. The strongest predictor for lesser improvement in IKDC score was a cartilage lesion >2 cm2 identified during surgery. Male sex and college education completion were associated with improved IKDC scores. Meniscal lesions did not predict change) in the IKDC score. A total of 69% of patients had returned to sport after 8.1 years (range, 6.7-9.8 years). The main reason for not returning to sport was fear of reinjury. The revision rate was 7.2% after 9 years (range, 8-11 years), 13% of patients needed subsequent ipsilateral non-ACL surgery, and 6% underwent contralateral ACLR. The absence of a meniscal tear, younger age, and male sex were predictors for revision. Graft choice did not predict PROM results or revision risk.

CONCLUSION

Improvements in IKDC scores were sustained 7 years after ACLR. The strongest predictor for poor outcome was a cartilage lesion >2 cm2. Patients can expect a 70% return-to-sport rate and an 87% chance of their knee feeling stable during daily and athletic activities after 8 years. Young male patients have better PROM scores but a higher risk of revision. There is a 26% chance of subsequent knee surgery within 9 years, including a revision rate of 7%, subsequent non-ACL surgery to the operated knee in 13%, and a 6% chance of contralateral ACLR.