Blood Loss and Transfusion Risk in Robotic‐Assisted Knee Arthroplasty: A Retrospective Analysis

Author(s):  
Hasaan Khan ◽  
Kieran Dhillon ◽  
Piyush Mahapatra ◽  
Ravi Popat ◽  
Omar Zakieh ◽  
...  
2021 ◽  
Vol 108 (Supplement_2) ◽  
Author(s):  
H Khan ◽  
K Dhillon ◽  
P Mahapatra ◽  
R Popat ◽  
D Nathwani

Abstract Introduction Significant blood loss is associated with a delayed postoperative recovery in joint arthroplasty. Emerging evidence suggests robotic-assisted knee arthroplasty reduces soft-tissue trauma, length of stay, and can facilitate a faster recovery. This study compares the total blood loss in patients undergoing robotic-assisted knee arthroplasty compared to conventional methods. Method Patients undergoing robotic-assisted total knee arthroplasty (TKA) or unicomparmental knee arthroplasty (UKA) were identified using patient records. Robotic-assisted groups were compared against contemporary sex-matched controls undergoing jig-based arthroplasty. The mean total blood loss was estimated using the Gross equation. Statistical significance was identified using the Student's t-test and Mann-Whitney U test for parametric and non-parametric data, respectively. Results Robotic TKA and UKA groups were successfully matched to contemporary controls (n = 50 in all groups). No differences in preoperative haematological parameters or blood volume were found between the robotic-assisted and control groups. Robotic TKA experienced 23.7% less blood loss compared to control TKA (911.0ml vs 1193.7ml, p < 0.01) which was found to be statistically significant. There was a non-significant difference in mean total blood loss in robotic UKA compared to control UKA (821.7ml vs 854.7ml, p = 0.69). Conclusions The use of a robotic surgical system reduces blood loss in TKA but not UKA in knee arthroplasty.


Author(s):  
H. E. Skibicki ◽  
D. Y. Ponzio ◽  
J. A. Brustein ◽  
Z. D. Post ◽  
A. C. Ong ◽  
...  

Author(s):  
Matthias Meyer ◽  
Tobias Renkawitz ◽  
Florian Völlner ◽  
Achim Benditz ◽  
Joachim Grifka ◽  
...  

Abstract Introduction Because of the ongoing discussion of imageless navigation in total knee arthroplasty (TKA), its advantages and disadvantages were evaluated in a large patient cohort. Methods This retrospective analysis included 2464 patients who had undergone TKA at a high-volume university arthroplasty center between 2012 and 2017. Navigated and conventional TKA were compared regarding postoperative mechanical axis, surgery duration, complication rates, one-year postoperative patient-reported outcome measures (PROMs) (WOMAC and EQ-5D indices), and responder rates as defined by the criteria of the Outcome Measures in Rheumatology and Osteoarthritis Research Society International consensus (OMERACT-OARSI). Results Both navigated (1.8 ± 1.6°) and conventional TKA (2.1 ± 1.6°, p = 0.002) enabled the exact reconstruction of mechanical axis. Surgery duration was six minutes longer for navigated TKA than for conventional TKA (p < 0.001). Complication rates were low in both groups with comparable frequencies: neurological deficits (p = 0.39), joint infection (p = 0.42 and thromboembolic events (p = 0.03). Periprosthetic fractures occurred more frequently during conventional TKA (p = 0.001). One-year PROMs showed excellent improvement in both groups. The WOMAC index was statistically higher for navigated TKA than for conventional TKA (74.7 ± 19.0 vs. 71.7 ± 20.7, p = 0.014), but the increase was not clinically relevant. Both groups had a similarly high EQ-5D index (0.23 ± 0.24 vs. 0.26 ± 0.25, p = 0.11) and responder rate (86.5% [256/296] vs. 85.9% [981/1142], p = 0.92). Conclusion Both methods enable accurate postoperative leg alignment with low complication rates and equally successful PROMs and responder rates one year postoperatively. Level of evidence III. Retrospective cohort study.


2021 ◽  
Vol 11 (7) ◽  
pp. 662
Author(s):  
Kim Huber ◽  
Bernhard Christen ◽  
Sarah Calliess ◽  
Tilman Calliess

Introduction: Image-based robotic assistance appears to be a promising tool for individualizing alignment in total knee arthroplasty (TKA). The patient-specific model of the knee enables a preoperative 3D planning of component position. Adjustments to the individual soft-tissue situation can be done intraoperatively. Based on this, we have established a standardized workflow to implement the idea of kinematic alignment (KA) for robotic-assisted TKA. In addition, we have defined limits for its use. If these limits are reached, we switch to a restricted KA (rKA). The aim of the study was to evaluate (1) in what percentage of patients a true KA or an rKA is applicable, (2) whether there were differences regarding knee phenotypes, and (3) what the differences of philosophies in terms of component position, joint stability, and early patient outcome were. Methods: The study included a retrospective analysis of 111 robotic-assisted primary TKAs. Based on preoperative long leg standing radiographs, the patients were categorized into a varus, valgus, or neutral subgroup. Initially, all patients were planned for KA TKA. When the defined safe zone had been exceeded, adjustments to an rKA were made. Intraoperatively, the alignment of the components and joint gaps were recorded by robotic software. Results and conclusion: With our indication for TKA and the defined boundaries, “only” 44% of the patients were suitable for a true KA with no adjustments or soft tissue releases. In the varus group, it was about 70%, whereas it was 0% in the valgus group and 25% in the neutral alignment group. Thus, significant differences with regard to knee morphotypes were evident. In the KA group, a more physiological knee balance reconstructing the trapezoidal flexion gap (+2 mm on average laterally) was seen as well as a closer reconstruction of the surface anatomy and joint line in all dimensions compared to rKA. This resulted in a higher improvement in the collected outcome scores in favor of KA in the very early postoperative phase.


2014 ◽  
Vol 22 (2) ◽  
pp. 146-149 ◽  
Author(s):  
Bob Jang ◽  
Mark Kao ◽  
Martin T Bohm ◽  
Ian A Harris ◽  
Darren B Chen ◽  
...  

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