Soft tissue balancing in total knee arthroplasty using sensor‐guided assessment: is there a learning curve?

Gharaibeh, Monther; Chen, Darren B.; MacDessi, Samuel J.

doi:10.1111/ans.14437

Cited by 20 publications

(15 citation statements)

References 19 publications

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“…For both TKA and UKA, RAS has shown no learning curve with the implant positioning but a significant learning curve with the workflow and instrumentation [3,4,12]. Surgical time flattens out effect after 5-10 cases and, in most studies, reaches a steady value after 8 cases in image-based RAS for UKA and TKA [4,6,11,17,18,20,22]. RAS offers a good opportunity for low-volume arthroplasty surgeons to achieve high levels of implant position accuracy in TKA and UKA [10].…”

Section: Introductionmentioning

confidence: 99%

The learning curve in robotic assisted knee arthroplasty is flattened by the presence of a surgeon experienced with robotic assisted surgery

Schopper

Proier

Luger

et al. 2022

Knee Surg Sports Traumatol Arthrosc

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Purpose The purpose of this study was to investigate the learning curve associated with robotic assisted knee arthroplasty (RAS KA). Therefore, the evaluation of the influence of an experienced surgeon on the overall team performance of three surgeons regarding the learning curve in RAS KA was investigated. It was hypothesized that the presence of an experienced surgeon flattens the learning curve and that there was no inflection point for the learning curve of the surgical team. Methods Fifty-five cases consisting of 31 total knee arthroplasties (TKA) and 24 unicompartmental arthroplasties (UKA) performed by three surgeons during 2021 were prospectively investigated. Single surgeon and team performance for operation time learning curve and inflection points were investigated using cumulative sum analysis (CUSUM). Results A downward trend line for individual surgeons and the team performance regarding the operation time learning curve was observed. No inflexion point was observed for the overall team performance regarding TKA and UKA. The surgeon that performed all cases with the assistance of the experienced surgeon had significantly shorter surgical times than the surgeon that only occasionally received assistance from the experienced surgeon (p = 0.004 TKA; p = 0.002 UKA). Conclusion The presence of an experienced surgeon in robotically assisted knee arthroplasty can flatten the learning curve of the surgical team formerly unexperienced in robotic assisted systems. Manufacturers should provide expanded support during initial cases in centres without previous experience to robotic assisted knee arthroplasty. Level of evidence III.

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Section: Introductionmentioning

confidence: 99%

The learning curve in robotic assisted knee arthroplasty is flattened by the presence of a surgeon experienced with robotic assisted surgery

Schopper

Proier

Luger

et al. 2022

Knee Surg Sports Traumatol Arthrosc

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“…The remaining three had used them intermittently in previous TKAs, but then intensively for 15 to 30 cases prior to the start of the study, experience which has been shown to mitigate any learning curve. 21 A pragmatic approach was used for the inclusion of patients: all those aged between 20 and 85 years who were scheduled for primary TKA to treat primary osteoarthritis, inflammatory arthritis, or post-traumatic arthritis were eligible. Those undergoing unilateral or bilateral procedures, those with extraarticular deformity from previous fracture or osteotomy, and those with severe stiffness were also included, but those who required constrained prostheses due to significant ligament deficiencies, and those undergoing TKA for acute fracture or tumour, were excluded.…”

Section: Methodsmentioning

confidence: 99%

Intraoperative pressure sensors improve soft-tissue balance but not clinical outcomes in total knee arthroplasty: a multicentre randomized controlled trial

MacDessi

Diwan

Harris

2022

The Bone & Joint Journal

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Aims Intraoperative pressure sensors allow surgeons to quantify soft-tissue balance during total knee arthroplasty (TKA). The aim of this study was to determine whether using sensors to achieve soft-tissue balance was more effective than manual balancing in improving outcomes in TKA. Methods A multicentre randomized trial compared the outcomes of sensor balancing (SB) with manual balancing (MB) in 250 patients (285 TKAs). The primary outcome measure was the mean difference in the four Knee injury and Osteoarthritis Outcome Score subscales (ΔKOOS4) in the two groups, comparing the preoperative and two-year scores. Secondary outcomes included intraoperative balance data, additional patient-reported outcome measures (PROMs), and functional measures. Results There was no significant difference in ΔKOOS4 between the two groups at two years (mean difference 0.4 points (95% confidence interval (CI) -4.6 to 5.4); p = 0.869), and multiple regression found that SB was not associated with a significant ΔKOOS4 (0.2-point increase (95% CI -5.1 to 4.6); p = 0.924). There were no significant differences between groups in other PROMs. Six-minute walking distance was significantly increased in the SB group (mean difference 29 metres; p = 0.015). Four-times as many TKAs were unbalanced in the MB group (36.8% MB vs 9.4% SB; p < 0.001). Irrespective of group assignment, no differences were found in any PROM when increasing ICPD thresholds defined balance. Conclusion Despite improved quantitative soft-tissue balance, the use of sensors intraoperatively did not differentially improve the clinical or functional outcomes two years after TKA. These results question whether a more precisely balanced TKA that is guided by sensor data, and often achieved by more balancing interventions, will ultimately have a significant effect on clinical outcomes. Cite this article: Bone Joint J 2022;104-B(5):604–612.

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“…In a single-surgeon experience, Lakra et al retrospectively quantified, using a CUSUM (cumulative sum control chart) analysis, their learning curve after performing 41 sensing technology-augmented total knee arthroplasties, showing an increase in the mean operative time of 11 minutes 41 . In a consecutive series of 90 total knee arthroplasties, Gharaibeh et al hypothesized that a surgeon's development of fine-tuning skills to obtain a well-balanced knee could be quantitatively demonstrated to occur within the first 30 cases 42 .…”

Section: Limitationsmentioning

confidence: 99%

Intraoperative Sensing Technology to Achieve Balance in Primary Total Knee Arthroplasty

et al. 2019

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Instability following total knee arthroplasty has been reported as a major cause for early or delayed total knee arthroplasty revision. » Balancing the knee remains an inexact art with no standardized protocol to optimize soft-tissue tension. » The sensing technology reviewed in this article allows surgeons to intraoperatively analyze several parameters, including tibiofemoral rotational alignment, quantitative pressure at peak contact points in the medial and lateral compartments during both total knee arthroplasty trialing and final implant positioning, evaluation of the kinematics of the prosthetic knee, and, finally, correcting soft-tissue imbalance in real time.» This technology has the potential for improved outcomes, reduction in constrained implant utilization, increased patient satisfaction, and lower revision rates.

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Soft tissue balancing in total knee arthroplasty using sensor‐guided assessment: is there a learning curve?

Abstract: This study suggests that there is a learning curve with the use of sensor-guided assessment in TKA in achieving knee balance; however, the differences noted between initial and final groups were small and may not be of clinical significance.

Cited by 20 publications

References 19 publications

The learning curve in robotic assisted knee arthroplasty is flattened by the presence of a surgeon experienced with robotic assisted surgery

The learning curve in robotic assisted knee arthroplasty is flattened by the presence of a surgeon experienced with robotic assisted surgery

Intraoperative pressure sensors improve soft-tissue balance but not clinical outcomes in total knee arthroplasty: a multicentre randomized controlled trial

Intraoperative Sensing Technology to Achieve Balance in Primary Total Knee Arthroplasty

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