Blood loss and transfusion risk in robotic-assisted knee arthroplasty: A retrospective analysis

Robotics in total knee replacement: Current use and future implications

Robotic total knee replacement (TKR) surgery has evolved over the years with the aim of improving the overall 80% satisfaction rate associated with TKR surgery. Proponents claim higher precision in executing the pre-operative plan which results in improved alignment and possibly better clinical outcomes. Opponents suggest longer operative times with potentially higher complications and no superiority in clinical outcomes alongside increased costs. This editorial will summarize where we currently stand and the future implications of using robotics in knee replacement surgery.

Over the Past Decade, Preoperative Anemia Has Become a Greater Predictor of Transfusions After Total Knee Arthroplasty

BACKGROUND

With advancements in perioperative blood management and the use of tranexamic acid, the rate of transfusions after total knee arthroplasty (TKA) has substantially decreased. As these principles are refined, other modifiable risk factors, such as preoperative anemia, may play an increasingly important role in transfusion risk for patients undergoing TKA.

METHODS

A multicenter, national database was utilized to identify patients undergoing TKA from 2010 to 2021. Anemia was defined by World Health Organization definitions as < 12 g/dL for women and < 13 g/dL for men. A predictive model was created using backwards elimination logistic regression to predict transfusion risk, controlling for demographic and medical covariates. The coefficient of anemia was then analyzed for each year. The trend over time was fitted with a best-fit linear regression equation.

RESULTS

There were 509,117 patients who underwent TKA, and had a mean age of 67 years (range, 18 to 89). There were 57,716 (11%) patients who were anemic preoperatively, and 15,426 (3%) of patients required a transfusion. Rate of transfusion decreased from 10.6% in 2010 to 0.6% in 2021. The odds ratio associated with anemia as a predictor of transfusion increased from 3.1 (95% confidence interval: 2.1 to 4.6) in 2010 to 14.0 (95% confidence interval: 8.9 to 24) in 2021.

CONCLUSIONS

The results of this study demonstrate that the importance of preoperative anemia as a predictor of transfusion has increased over the past decade as rates of transfusion have decreased. As perioperative blood management protocols improve, preoperative anemia should be considered an important focus of intervention to reduce the risk of transfusion prior to TKA.

LEVEL OF EVIDENCE

III.

Analysis of the incidence and risk factors of blood transfusion in total knee revision: a retrospective nationwide inpatient sample database study

OBJECTIVE

This study sought to determine the incidence and risk factors of blood transfusion among patients undergoing total knee revision (TKR) using a nationwide database.

METHODS

A retrospective data analysis was conducted based on the Nationwide Inpatient Sample (NIS), enrolling patients who underwent TKR from 2010 to 2019 with complete information. The patients were divided into two groups based on whether they received blood transfusion or not. The demographic characteristics (race, sex, and age), length of stay (LOS), total charge of hospitalization, hospital characteristics (admission type, insurance type, bed size, teaching status, location, and region of hospital), hospital mortality, comorbidities, and perioperative complications were analyzed. Finally, we conducted univariate and multivariate logistic regression to identify factors that were associated with TKR patients to require blood transfusion.

RESULTS

The NIS database included 115,072 patients who underwent TKR. Among them, 14,899 patients received blood transfusion, and the incidence of blood transfusion was 13.0%. There was a dramatic decrease in the incidence over the years from 2010 to 2019, dropping from 20.4 to 6.5%. TKR patients requiring transfusions had experienced longer LOS, incurred higher total medical expenses, utilized Medicare more frequently, and had increased in-hospital mortality rates (all P < 0.001). Independent predictors for blood transfusion included advanced age, female gender, iron-deficiency anemia, rheumatoid disease, chronic blood loss anemia, congestive heart failure, coagulopathy, uncomplicated diabetes, lymphoma, fluid and electrolyte disorders, metastatic carcinoma, other neurological diseases, paralysis, peripheral vascular disorders, pulmonary circulation disorders, renal failure, valvular disease, and weight loss. In addition, risk factors for transfusion in TKR surgery included sepsis, acute myocardial infarction, deep vein thrombosis, pulmonary embolism, gastrointestinal bleeding, heart failure, renal insufficiency, pneumonia, wound infection, lower limb nerve injury, hemorrhage/seroma/hematoma, wound rupture/non healing, urinary tract infection, acute renal failure, and postoperative delirium.

CONCLUSIONS

Our findings highlight the importance of recognizing the risk factors of blood transfusion in TKR to reduce the occurrence of adverse events.

Biochemical implications of robotic surgery: a new frontier in the operating room

Robotic surgery represents a milestone in surgical procedures, offering advantages such as less invasive methods, elimination of tremors, scaled motion, and 3D visualization. This in-depth analysis explores the complex biochemical effects of robotic methods. The use of pneumoperitoneum and steep Trendelenburg positioning can decrease pulmonary compliance and splanchnic perfusion while increasing hypercarbia. However, robotic surgery reduces surgical stress and inflammation by minimizing tissue trauma. This contributes to faster recovery but may limit immune function. Robotic procedures also limit ischemia-reperfusion injury and oxidative damage compared to open surgery. They also help preserve native antioxidant defenses and coagulation. In a clinical setting, robotic procedures reduce blood loss, pain, complications, and length of stay compared to traditional procedures. However, risks remain, including device failure, the need for conversion to open surgery and increased costs. On the oncology side, there is still debate about margins, recurrence, and long-term survival. The advent of advanced technologies, such as intraoperative biosensors, localized drug delivery systems, and the incorporation of artificial intelligence, may further improve the efficiency of robotic surgery. However, ethical dilemmas regarding patient consent, privacy, access, and regulation of this disruptive innovation need to be addressed. Overall, this review sheds light on the complex biochemical implications of robotic surgery and highlights areas that require additional mechanistic investigation. It presents a comprehensive approach to responsibly maximize the potential of robotic surgery to improve patient outcomes, integrating technical skill with careful consideration of physiological and ethical issues.

The Effect of Tranexamic Acid With or Without Tourniquet on Blood Loss in Total Knee Arthroplasty at a Community Hospital

Tourniquets have long been used in total knee arthroplasty due to the theoretical improvement of bleeding control, integration of cement-bone interface, visibility, and efficiency of the overall surgery. However, this has become increasingly disputed. Comparative studies in total knee arthroplasty employing chemical prophylaxis, i.e., tranexamic acid, have been conducted. This retrospective cohort study evaluated the effect of tranexamic with or without a tourniquet on mean blood loss, hemoglobin, and length of stay in total knee arthroplasty patients. A total of 153 patients' records met the inclusion criteria, 95 patients (62%) were in the tranexamic acid-only group while 58 patients (38%) were in the tranexamic acid plus tourniquet group. Based on mean blood loss in mL (827.5 without vs. 810.1 with the tourniquet, p=0.805), hemoglobin counts in g/dL (12.6 without vs. 12.5 with the tourniquet, p=0.598), and length of stay in days (1.0 days without vs. 1.1 with the tourniquet, p=0.204), there was no statistical difference between the tranexamic alone vs. tranexamic plus tourniquet groups. There were no statistical differences in the mean BMI between groups (32.3 without vs. 32.4 with tourniquets, p=0.901). The patient population had more women (64.1%) than men (35.9%) (p=0.001), but no significant difference in gender based on tourniquet use (p=0.521). The tourniquet group averaged three years younger than the tranexamic alone group (age mean 68.2 without vs 65.3 with tranexamic, p=0.029). This study found no identifiable difference in the three observed variables, indicating that tourniquet provides limited to no additional benefit in reducing blood loss over tranexamic alone in total knee arthroplasty, while tranexamic alone has no deleterious decrease in mean hemoglobin or increase in length of stay.

Advancements in Robotic Surgery: A Comprehensive Overview of Current Utilizations and Upcoming Frontiers

Robotic surgery, a groundbreaking advancement in medical technology, has redefined the landscape of surgical procedures. This comprehensive overview explores the multifaceted world of robotic surgery, encompassing its definition, historical development, current applications, clinical outcomes, benefits, emerging frontiers, challenges, and future implications. We delve into the fundamentals of robotic surgical systems, examining their components and advantages. From general and gynecological surgery to urology, cardiac surgery, orthopedics, and beyond, we highlight the diverse specialties where robotic surgery is making a significant impact. The many benefits discussed include improved patient outcomes, reduced complications, faster recovery times, cost-effectiveness, and enhanced surgeon experiences. The outlook reveals a healthcare landscape where robotic surgery is increasingly vital, enabling personalized medicine, bridging healthcare disparities, and advancing surgical precision. However, challenges such as cost, surgeon training, technical issues, ethical considerations, and patient acceptance remain relevant. In conclusion, robotic surgery is poised to continue shaping the future of health care, offering transformative possibilities while emphasizing the importance of collaboration, innovation, and ethical governance.

Predicting Factors for Blood Transfusion in Primary Total Knee Arthroplasty Using a Machine Learning Method

INTRODUCTION

Acute blood loss anemia requiring allogeneic blood transfusion is still a postoperative complication of total knee arthroplasty (TKA). This study aimed to use machine learning models for the prediction of blood transfusion after primary TKA and to identify contributing factors.

METHODS

A total of 2,093 patients who underwent primary TKA at our institution were evaluated using data extracted from the hospital quality improvement database to identify patient demographics and surgical variables that may be associated with blood transfusion. A multilayer perceptron neural network (MPNN) machine learning algorithm was used to predict risk factors for blood transfusion and factors associated with increased length of stay. Statistical analyses including bivariate correlate analysis, Chi-Square test, and Student t-test were performed for demographic analysis and to determine the correlation between blood transfusion and other variables.

RESULTS

The results demonstrated important factors associated with transfusion rates, including preoperative hemoglobin level, preoperative creatinine level, length of surgery, simultaneous bilateral surgeries, tranexamic acid usage, American Society of Anesthesiologists Physical Status score, preoperative albumin level, ethanol usage, preoperative anticoagulation medications, age, and TKA type (conventional versus robotic-assisted). Patients who underwent a blood transfusion had a markedly greater length of stay than those who did not. The MPNN machine learning model achieved excellent performance across discrimination (AUC = 0.894).

DISCUSSION

The MPNN machine learning model showed its power as a statistical analysis tool to predict the ranking of factors for blood transfusion. Traditional statistics are unable to differentiate importance or predict in the same manner as a machine learning model.

CONCLUSION

This study demonstrated that MPNN for the prediction of patient-specific blood transfusion rates after TKA represented a novel application of machine learning with the potential to improve preoperative planning for treatment outcomes.

Effectiveness of Robotic Arm-Assisted Total Knee Arthroplasty on Transfusion Rate in Staged Bilateral Surgery

The transfusion rate in staged bilateral total knee arthroplasty (TKA) remains high despite the application of blood management techniques. The potential of robotic arm-assisted TKA (R-TKA) in reducing the transfusion rate in staged bilateral surgery has not yet been investigated. Therefore, we aimed to evaluate the effectiveness of R-TKA on transfusion reduction compared with conventional TKA (C-TKA) in staged bilateral surgery. This retrospective study involved two groups of patients who underwent 1-week interval staged bilateral TKA-the C-TKA group and the R-TKA group-using MAKO SmartRobotics (Stryker, Kalamazoo, MI, USA). Each group comprised 53 patients after propensity score matching and was compared in terms of nadir hemoglobin (Hb) level and transfusion rate after each stage of surgery. Both groups showed no significant differences in the propensity-matched variables of age, sex, body mass index, American Society of Anesthesiologists physical status score, and preoperative Hb level. The R-TKA group showed a significantly higher nadir Hb level than the C-TKA group after the second TKA (p = 0.002). The transfusion rate was not significantly different between the two groups after the first TKA (p = 0.558). However, the R-TKA group showed a significantly lower transfusion rate in the TKA (p = 0.030) and overall period (p = 0.023) than the C-TKA group. Patients who undergo staged bilateral R-TKA have lower transfusion rate than those who undergo C-TKA. R-TKA may be effective in minimizing unnecessary allogeneic transfusions in staged bilateral surgery.

Evaluation of Blood Loss in Conventional vs MAKOplasty Total Knee Arthroplasty

Background

Methods

Results

Conclusions

Comparison of Robotic and Conventional Unicompartmental Knee Arthroplasty Outcomes in Patients with Osteoarthritis: A Retrospective Cohort Study

Robotic-arm-assisted unicompartmental knee arthroplasty (RUKA) was developed to increase the accuracy of bone alignment and implant positioning. This retrospective study explored whether RUKA has more favorable overall outcomes than conventional unicompartmental knee arthroplasty (CUKA). A total of 158 patients with medial compartment osteoarthritis were recruited, of which 85 had undergone RUKA with the Mako system and 73 had undergone CUKA. The accuracy of component positioning and bone anatomical alignment was compared using preoperative and postoperative radiograph. Clinical outcomes were evaluated using questionnaires, which the patients completed preoperatively and then postoperatively at six months, one year, and two years. In total, 52 patients from the RUKA group and 61 from the CUKA group were eligible for analysis. The preoperative health scores and Kellgren-Lawrence scores were higher in the RUKA group. RUKA exhibited higher implant positioning accuracy, thus providing a superior femoral implant angle, properly aligned implant placement, and a low rate of overhang. RUKA also achieved higher accuracy in bone anatomical alignment (tibial axis angle and anatomical axis angle) than CUKA, but surgical time was longer, and blood loss was greater. No significant differences were observed in the clinical outcomes of the two procedures.