ISAKOS Congress 2021

2021 ISAKOS Biennial Congress ePoster

 

Practice Patterns For Revision Anterior Cruciate Ligament Reconstruction In An Integrated Health Care System

Christopher M. Gibbs, MD, Pittsburgh, PA UNITED STATES
Jonathan D Hughes, MD, Allison Park, Pennsylvania UNITED STATES
Maya Muenzer, BS, Pittsburgh, Pennsylvania UNITED STATES
Philipp Wilhelm Winkler, MD, Linz AUSTRIA
Bryson P. Lesniak, MD, Presto, Pennsylvania UNITED STATES
Volker Musahl, MD, Prof., Pittsburgh, Pennsylvania UNITED STATES

University of Pittsburgh, Pittsburgh, Pennsylvania, UNITED STATES

FDA Status Not Applicable

Summary

Practice patterns for revision ACL reconstruction differ amongst surgeons of different surgical volume.

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Abstract

Introduction

When anterior cruciate ligament reconstruction (ACLR) is performed by high-volume surgeons, lower rates of reoperation, readmission, infection, and decreased cost have been reported. The effect of surgeon volume on revision ACLR practices has not been well studied; this knowledge may help deliver high-quality care. We aimed to determine the rate of revisions in the practices of high-, medium-, and low-volume surgeons, and assess referral patterns and demographic, injury, and surgical factors among each group. It was hypothesized that high-volume surgeons would perform more revision ACLRs; additionally, revision ACLRs for high-volume surgeons would be more complex referrals.

Methods

A retrospective database review of all ACLRs performed from 2015 to 2020 within our health system was conducted. Using the number of annual ACLR, surgeons were categorized by the number of annual ACLRs as low- (=17), medium- (18-34), or high-volume (=35) (1). The referral source for each revision ACLR and re-revisions were recorded. Activity level (competition level, Marx, and Tegner scores), time from graft failure or previous ACLR to revision, age, concomitant injuries, graft type, and return to sport data were collected. Comparison among surgeons with different volumes was performed by Chi-square, one-way ANOVA with post-hoc analysis, or a Kruskal-Wallis test, as appropriate, using SPSS statistics (IBM) with p<0.05.

Results

Of 4,555 ACLR, 171 were revisions (3.8%). The percentage of revision surgeries was significantly higher for high- (4.9%) and medium- (3.9%) compared to low-volume surgeons (1.6%, p<0.05). There was no statistically significant difference between the referral source or rate of re-revision between the three groups. Patients revised by a high-volume surgeon were more likely to have a higher activity level as assessed by competition level, Marx, and Tegner scores (p<0.05). Significant differences in graft choice for revision ACLR were seen, with hamstring autografts (HS) and allografts more frequently used by low- (5% and 70%) and medium-volume (14% and 35%) surgeons than high-volume surgeons (4% and 25%); bone-patellar tendon bone (BTB) and quadriceps tendon (QT) autografts were more likely to be used by high- (32% and 39%) and medium-volume (38% and 14%) surgeons compared to low-volume (15% and 10%) surgeons (p<0.05). High-volume surgeons were more likely to perform revisions on patients with cartilage injuries (p<0.05) and to perform staged revision ACLR (p<0.05). No additional significant differences were identified.

Discussion

This study’s main finding was that practice patterns for revision ACLR vary significantly among surgeons of various surgical volumes. Low-volume surgeons were found to perform fewer revision ACLRs, and significant variations in patient, injury, and treatment patterns were also observed. Low-volume surgeons use more HS and allograft while high-volume surgeons more commonly use BTB and QT. These findings are likely due to high-volume surgeons being fellowship-trained and more willing to perform revision ACLR and aggressively diagnose and treat chondral injuries. In conclusion, knowledge of differing practice patterns for revision ACLR among surgeons of various surgical volumes may allow targeted interventions to improve outcomes (clinical or graft failure, patient reported outcomes) that are affected by these variables to improve patient care.

References: 1)Schairer. OJSM. 2017.