Predictors for blood loss and transfusion frequency to guide blood saving programs in primary knee- and hip-arthroplasty

Suction drain usage has no benefit following revision total hip and knee arthroplasty

INTRODUCTION

The use of drains after primary total joint arthroplasty (TJA) has shown little benefit. Few studies have investigated drain usage after revision TJA. The purpose of this study was to determine whether utilizing suction drains is beneficial for patients undergoing revision arthroplasty.

MATERIALS AND METHODS

We performed a comprehensive literature review utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines from the PubMed, Embase, Web of Science, and Cochrane Library. Inclusion criteria of this review were all original articles written in English investigating the efficacy and safety of closed suction drainage in revision TKA or THA, reporting at least one of the following outcome measures: (1) estimated blood loss (EBL), (2) perioperative hemoglobin change, (3) needs for transfusion, (4) postoperative infection, and (5) wound complications. Articles were excluded if they are not available in English or they included case reports, systematic reviews, comments, editorials, surveys, or animal studies prior to July 22, 2023. A total of six studies met inclusion criteria. In total, 655 patients had a drain while 1765 patients did not have a drain after revision total hip or knee arthroplasty. Primary outcomes included for meta-analysis included estimated blood loss (EBL), postoperative hemoglobin, need for transfusion. Other data extracted includes postoperative infections, and wound complications.

RESULTS

Six studies met the inclusion criteria. In total, 655 patients had drains, while 1765 patients did not after revision total hip or knee arthroplasty. The average age of the patients was 66.1+/- 3.4 years, and the average BMI was 30.3 +/-0.8. There was no difference in postoperative infections (p = 0.14), wound complications (p = 0.621) or need for transfusion (p = 0.521) between the two groups. There was also no difference in EBL (Hedges' g CI[-3.52, 2.77]) or postoperative Hb (Hedges' g CI[-1.65, 2.41]) between patients with and without drains.

CONCLUSIONS

Our results do not show any benefit from drain placement after revision total hip or knee arthroplasty. With the increased cost, time and need for drain removal, this is likely an unnecessary intervention.

LEVEL OF EVIDENCE

Level III, systematic review and meta-analysis.

Development and Validation of a Machine Learning Algorithm to Predict the Risk of Blood Transfusion after Total Hip Replacement in Patients with Femoral Neck Fractures: A Multicenter Retrospective Cohort Study

OBJECTIVE

Total hip arthroplasty (THA) remains the primary treatment option for femoral neck fractures in elderly patients. This study aims to explore the risk factors associated with allogeneic blood transfusion after surgery and to develop a dynamic prediction model to predict post-operative blood transfusion requirements. This will provide more accurate guidance for perioperative humoral management and rational allocation of medical resources.

METHODS

We retrospectively analyzed data from 829 patients who underwent total hip arthroplasty for femoral neck fractures at three third-class hospitals between January 2017 and August 2023. Patient data from one hospital were used for model development, whereas data from the other two hospitals were used for external validation. Logistic regression analysis was used to screen the characteristic subsets related to blood transfusion. Various machine learning algorithms, including logistic regression, SVA (support vector machine), K-NN (k-nearest neighbors), MLP (multilayer perceptron), naive Bayes, decision tree, random forest, and gradient boosting, were used to process the data and construct prediction models. A 10-fold cross-validation algorithm facilitated the comparison of the predictive performance of the models, resulting in the selection of the best-performing model for the development of an open-source computing program.

RESULTS

BMI (body mass index), surgical duration, IBL (intraoperative blood loss), anticoagulant history, utilization rate of tranexamic acid, Pre-Hb, and Pre-ALB were included in the model as well as independent risk factors. The average area under curve (AUC) values for each model were as follows: logistic regression (0.98); SVA (0.91); k-NN (0.87) MLP, (0.96); naive Bayes (0.97); decision tree (0.87); random forest (0.96); and gradient boosting (0.97). A web calculator based on the best model is available at: (https://nomo99.shinyapps.io/dynnomapp/).

CONCLUSION

Utilizing a computer algorithm, a prediction model with a high discrimination accuracy (AUC > 0.5) was developed. The logistic regression model demonstrated superior differentiation and reliability, thereby successfully passing external validation. The model's strong generalizability and applicability have significant implications for clinicians, aiding in the identification of patients at high risk for postoperative blood transfusion.

Outcomes of Unicompartmental Knee Arthroplasty in Patients Receiving Long-Term Anticoagulation Therapy: A Propensity-Matched Cohort Study

BACKGROUND

Although total knee arthroplasty has been considered the gold-standard treatment for severe osteoarthritis of the knee, unicompartmental knee arthroplasty (UKA) has become an increasingly favorable alternative for single-compartment osteoarthritis of the knee. Few studies have examined potential high-risk populations undergoing this procedure. The purpose of this study was to investigate the outcomes of UKA in patients receiving long-term anticoagulation therapy.

METHODS

In this study, a large administrative database was queried to identify patients undergoing UKA between 2009 and 2019, who were then divided into a cohort receiving long-term anticoagulation and a control cohort. Propensity scores were utilized to match these patients. Multivariable logistic regression was utilized to compare 90-day and 2-year complication rates between cohorts.

RESULTS

Patients who were on long-term anticoagulation had significantly increased odds of extended length of stay, surgical site infection, wound complication, transfusion, deep vein thrombosis, pulmonary embolism, and readmission at 90-day follow-up. The long-term anticoagulation cohort also experienced significantly higher odds of periprosthetic joint infection and mechanical complications at 2-year follow-up; however, odds of conversion to total knee arthroplasty were not increased.

CONCLUSIONS

This study demonstrated that long-term anticoagulation use was associated with poorer medical and surgical outcomes at both 90 days and 2 years postoperatively in patients undergoing UKA, even after rigorous adjustment for confounders.

Risk Factors for Anemia Exacerbation Requiring Red Blood Cell Transfusion During Edoxaban Thromboprophylaxis After Orthopedic Surgery

Background An increased risk of anemia during edoxaban thromboprophylaxis in orthopedic surgery has been reported. However, the risk factors for the exacerbation of anemia requiring transfusion with irradiated red blood cell concentrates during postoperative edoxaban thromboprophylaxis remain unknown. Therefore, this study investigated the factors that increase the possibility of transfusion during edoxaban thromboprophylaxis after orthopedic surgery by reanalyzing clinical data from a previous collection. Methods A total of 221 patients who underwent total hip or knee arthroplasty at a single center between July 2011 and June 2012 were included in this study. Among these, 167 patients who received 30 mg of postoperative edoxaban thromboprophylaxis were retrospectively analyzed to identify critical factors for transfusion during edoxaban thromboprophylaxis after orthopedic surgery. Results Lower preoperative hemoglobin levels and higher intraoperative blood loss per body weight were significantly associated with an increase in the frequency of transfusion during postoperative edoxaban thromboprophylaxis. These factors were also potentially related to increased coagulation parameters during edoxaban thromboprophylaxis. Conclusion Our study shows that lower preoperative hemoglobin levels and higher intraoperative blood loss are associated with increased coagulation parameters with edoxaban thromboprophylaxis after orthopedic surgery and may lead to worsening of anemia, thereby requiring blood transfusion.

A neck-sparing short stem shows significantly lower blood loss in total hip arthroplasty compared to a neck-resecting short stem

Short stems are associated with a significantly lower blood loss (BL) compared to straight stems in total hip arthroplasty (THA). Different types of stems differ in design, fixation and level of femoral neck osteotomy. Therefore, we sought to evaluate the difference regarding the perioperative BL between two short stems with different designs in direct anterior approach (DAA). A total of 187 THA performed by a single surgeon were analysed. 107 patients received a neck-resecting (Group A) and 80 patients a neck-sparing short stem (Group B). Blood counts of the day before surgery and of two days after surgery were evaluated. Total blood volume and BL were calculated. Additionally, duration of surgery was analysed. The perioperative BL was significantly lower in Group B (451.4 ± 188.4 ml) compared to Group A (546.6 ± 232.7 ml; p = 0.002). The postoperative haematocrit (31.6 ± 3.7% vs. 30.4 ± 4.4%; p = 0.049) and haemoglobin-level (11.0 ± 1.3 g/dL vs. 10.4 ± 1.5 g/dL; p = 0.002) were significantly higher in Group B. Duration of surgery was significantly shorter in Group B (62.0 ± 11.4 min vs. 72.6 ± 21.8 min; p < 0.001). The use of a neck-sparing short stem leads to a significantly decreased BL compared to a neck-resecting short stem in DAA THA. A less extensively conducted capsular release necessary for optimal femoral exposition might lead to a lower perioperative BL and shorter durations of surgery.

Effect of Perioperative Antithrombotics on Postoperative Transfusion and Hematoma in Head and Neck Free Flaps

Objective

To explore if antiplatelet or anticoagulant therapy increases the risk of transfusion requirement or postoperative hematoma formation in patients undergoing microvascular reconstruction for head and neck defects.

Study Design

Retrospective cohort study.

Setting

Departments of Otolaryngology-Head and Neck Surgery at the University of Alabama at Birmingham, the University of Colorado, and the University of California Irvine.

Methods

A multi-institutional, retrospective review on microvascular reconstruction of the head and neck between August 2013 to July 2021. Perioperative antithrombotic data were collected to examine predictors of postoperative transfusion and hematoma.

Results

A total of 843 free flaps were performed. Preoperative hemoglobin, hematocrit, operative time, and flap type were positive predictors of postoperative transfusion in both bivariate (P < .0001) and multivariate analyses (P < .0001). However, neither anticoagulation nor antiplatelet therapy were predictive of postoperative transfusion rates and hematoma formation.

Conclusion

Antithrombotic regimens do not increase the risk of postoperative transfusion or hematoma in head and neck microvascular reconstruction. Based on this limited data, perioperative antithrombotic regimens can be considered in patients who may otherwise be at risk for these postoperative complications.

Validation of Machine Learning Model Performance in Predicting Blood Transfusion After Primary and Revision Total Hip Arthroplasty

BACKGROUND

The rates of blood transfusion following primary and revision total hip arthroplasty (THA) remain as high as 9% and 18%, respectively, contributing to patient morbidity and healthcare costs. Existing predictive tools are limited to specific populations, thereby diminishing their clinical applicability. This study aimed to externally validate our previous institutionally developed machine learning (ML) algorithms to predict the risk of postoperative blood transfusion following primary and revision THA using national inpatient data.

METHODS

Five ML algorithms were trained and validated using data from 101,266 primary THA and 8,594 revision THA patients from a large national database to predict postoperative transfusion risk after primary and revision THA. Models were assessed and compared based on discrimination, calibration, and decision curve analysis.

RESULTS

The most important predictors of transfusion following primary and revision THA were preoperative hematocrit (<39.4%) and operation time (>157 minutes), respectively. All ML models demonstrated excellent discrimination (area under the curve (AUC) >0.8) in primary and revision THA patients, with artificial neural network (AUC = 0.84, slope = 1.11, intercept = -0.04, Brier score = 0.04), and elastic-net-penalized logistic regression (AUC = 0.85, slope = 1.08, intercept = -0.01, and Brier score = 0.12) performing best, respectively. On decision curve analysis, all 5 models demonstrated a higher net benefit than the conventional strategy of intervening for all or no patients in both patient cohorts.

CONCLUSIONS

This study successfully validated our previous institutionally developed ML algorithms for the prediction of blood transfusion following primary and revision THA. Our findings highlight the potential generalizability of predictive ML tools developed using nationally representative data in THA patients.

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.

Predictive and protective factors for allogenic blood transfusion in total knee arthroplasty. A retrospective cohort study

Background

This study aimed to identify the predictive and protective factors of blood transfusion in patients undergoing total knee arthroplasty (TKA) and therefore determine the profile of patients with low and high risk of blood transfusion after arthroplasty.

Methods

We conducted a retrospective study with all patients who underwent primary TKA between January 2017 and December 2019 (n = 1.028 patients) in our institution. Information about allogenic transfusion was collected from medical records to determine the incidence, the predictive and protective factors of blood transfusion. All cases of blood transfusions were documented as well the number of units and the moment of each transfusion. We performed univariate and multivariate logistic regression analyses to identify the independent risk and protective factors.

Results

The total transfusion rate was 11%, 1.1% at intraoperative and 9,9% at postoperative period. The independent risk factors for transfusion were female gender (OR 1.64), older age (>55yo, OR > 2) higher surgical risk (ASA III, OR 3.07), lower preoperative hemoglobin levels (p = 0.024), post-traumatic arthritis (OR 4.11) and use of postoperative drains (OR 1.81) The protective factors for transfusion were male gender (OR 0.60), obesity (IMC >30, OR 0.60) and use of intravenous tranexamic acid intraoperatively (OR 0.40).

Conclusions

We conclude that in addition to the well-established risk factors for blood transfusion such as advanced age, low hemoglobin levels and high surgical risk, we can add post-fracture arthroplasty, non-use of tranexamic acid and the use of postoperative joint drain.

Artificial neural networks for the prediction of transfusion rates in primary total hip arthroplasty

BACKGROUND

Despite advancements in total hip arthroplasty (THA) and the increased utilization of tranexamic acid, acute blood loss anemia necessitating allogeneic blood transfusion persists as a post-operative complication. The prevalence of allogeneic blood transfusion in primary THA has been reported to be as high as 9%. Therefore, this study aimed to develop and validate novel machine learning models for the prediction of transfusion rates following primary total hip arthroplasty.

METHODS

A total of 7265 consecutive patients who underwent primary total hip arthroplasty were evaluated using a single tertiary referral institution database. Patient charts were manually reviewed to identify patient demographics and surgical variables that may be associated with transfusion rates. Four state-of-the-art machine learning algorithms were developed to predict transfusion rates following primary THA, and these models were assessed by discrimination, calibration, and decision curve analysis.

RESULTS

The factors most significantly associated with transfusion rates include tranexamic acid usage, bleeding disorders, and pre-operative hematocrit (< 33%). The four machine learning models all achieved excellent performance across discrimination (AUC > 0.78), calibration, and decision curve analysis.

CONCLUSION

This study developed machine learning models for the prediction of patient-specific transfusion rates following primary total hip arthroplasty. The results represent a novel application of machine learning, and has the potential to improve outcomes and pre-operative planning.

LEVEL OF EVIDENCE

III, case-control retrospective analysis.

Rotational Thromboelastometry Predicts Transfusion Requirements in Total Joint Arthroplasties

The frequency of red blood cell (RBC) transfusions is high in total joint arthroplasties, and the hemorrhagic risk is associated with both surgery- and patient-related factors. This study aims to assess the ability of rotational thromboelastometry (ROTEM) to identify patients at high risk for transfusion and excessive bleeding. A prospective observational study was conducted including 206 patients who underwent total knee or hip arthroplasties. Assessment of the coagulation status was performed preoperatively and immediately postoperatively using ROTEM analysis and conventional coagulation tests. The number of RBC transfusions and the postoperative hemoglobin drop were recorded. ROTEM findings were compared between transfused and nontransfused patients, and also between patients with and without excessive bleeding. Higher values of postoperative FIBTEM maximum clot firmness (MCF) were associated with lower risks of transfusion (odds ration [OR]: 0.66, 95% confidence interval [CI]: 0.57-0.78, p<0.001) and excessive bleeding (OR: 0.58, 95% CI: 0.36-0.94, p=0.028). A postoperative FIBTEM MCF value ≤10mm had 80.1% (95% CI: 73.1-85.9%) sensitivity with 75.5% (95% CI: 60.4-87.1%) specificity to predict transfusion requirements, and 70.5% (95% CI: 63.6-76.8%) sensitivity with 88.8% (95% CI: 51.7-99.7%) specificity to predict excessive bleeding. The estimated average probability of transfusion in patients with FIBTEM MCF values of 0 to 4mm is 86.3%. ROTEM assay demonstrated high predictive ability for transfusion and excessive bleeding. Identification of patients at risk for transfusion could allow blood banks to ensure adequate blood supply, while also more intense blood-salvaging strategies could be implemented in these patients.

Prevalence of modifiable risk factors in primary elective arthroplasty and their association with infections

BACKGROUND AND PURPOSE

The aim of this study was to identify the prevalence of modifiable risk factors of surgical site infections (SSI) in patients undergoing primary elective total joint arthroplasty (TJA) receiving conventional preoperative preparation, and to explore their association with infectious outcomes.

PATIENTS AND METHODS

Information regarding modifiable risk factors (anemia, diabetes, obesity, nutritional status, smoking, physical activity) was prospectively gathered in patients undergoing primary TJA of hip or knee in 2018-2020 at a single institution with 6 weeks' follow-up time.

RESULTS

738 patients (median age 68 years [IQR 61-73], women 57%) underwent TJA (knee 64%, hip 36%). Anemia was detected in 8%, diabetes was present in 9%, an additional 2% had undiagnosed diabetes (HbA1c > 47 mmol/mol), and 8% dysglycemia (HbA1c 42-47 mmol/mol). Obesity (BMI ≥ 30) was observed in 52%. Serum albumin, total lymphocyte count, and vitamin D below normal limits was identified in 0.1%, 18%, and 16%, respectively. Current smokers were 7%. Surgical site complications occurred in 116 (16%), superficial SSI in 57 (8%), progressing to periprosthetic joint infection in 7 cases. Univariate analysis identified higher odds of superficial SSI for BMI ≥ 30 (OR 2.1, 95%CI 1.2-3.8) and HbA1c ≥ 42 mmol/mol (OR 2.2, CI 1.1-4.2), but no association was found with other factors.

CONCLUSION

In a general population undergoing primary TJA an association was found between obesity (52%) and dysglycemia/diabetes (19%) and superficial SSI (8%), which progressed to PJI in 12% of cases, generating a 1% total rate of PJI. Modification of these risk factors might mitigate infectious adverse outcomes.

The association between perioperative blood transfusions and venous thromboembolism risk following surgical management of hip fractures

Introduction

Despite high rates of transfusion reported among hip fracture patients in the perioperative period, the relationship between perioperative transfusions and VTE has not been thoroughly explored. Therefore, we used a national database to evaluate how perioperative transfusions among patients undergoing surgical management of hip fractures impacted 1) deep vein thrombosis (DVT) and 2) pulmonary embolism (PE) risk.

Methods

The Targeted Hip Fracture Database of the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) was queried for patients undergoing surgical management of hip fractures from 2016 to 2019. A multivariate logistic regression was conducted using various patient-specific variables to identify risk factors for DVT and PE. A nearest-neighbor propensity score matched (PSM) comparison between patients receiving and not receiving perioperative blood transfusions (1:1) was additionally conducted.

Results

Prior to our PSM, preoperative transfusions were not associated with DVT incidence (OR: 1.48, 95% CI: 0.80-2.50; p = 0.2). However, intra-operative/post-operative transfusions (OR: 1.26, 95% CI: 1.02-1.56; p = 0.00.30) as well as the receipt of both transfusion types (OR: 1.81, 95% CI: 1.10-2.81; p = 0.012) were associated with an increased risk of DVT. The latter of these findings remained significant following PSM (OR: 1.73, 95% CI: 1.04-2.73; p = 0.025). No relationship was demonstrated between PE risk and perioperative transfusion receipt.

Conclusion

Our findings emphasize the importance of perioperative blood management strategies among patients undergoing surgical repair of hip fracture. Specifically, orthopaedic surgeons should aim to optimize hip fracture patients prior to surgical intervention as well as intra-operatively to reduce transfusion incidence.

Personalized Surgical Transfusion Risk Prediction Using Machine Learning to Guide Preoperative Type and Screen Orders

BACKGROUND

Accurate estimation of surgical transfusion risk is essential for efficient allocation of blood bank resources and for other aspects of anesthetic planning. This study hypothesized that a machine learning model incorporating both surgery- and patient-specific variables would outperform the traditional approach that uses only procedure-specific information, allowing for more efficient allocation of preoperative type and screen orders.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program Participant Use File was used to train four machine learning models to predict the likelihood of red cell transfusion using surgery-specific and patient-specific variables. A baseline model using only procedure-specific information was created for comparison. The models were trained on surgical encounters that occurred at 722 hospitals in 2016 through 2018. The models were internally validated on surgical cases that occurred at 719 hospitals in 2019. Generalizability of the best-performing model was assessed by external validation on surgical cases occurring at a single institution in 2020.

RESULTS

Transfusion prevalence was 2.4% (73,313 of 3,049,617), 2.2% (23,205 of 1,076,441), and 6.7% (1,104 of 16,053) across the training, internal validation, and external validation cohorts, respectively. The gradient boosting machine outperformed the baseline model and was the best- performing model. At a fixed 96% sensitivity, this model had a positive predictive value of 0.06 and 0.21 and recommended type and screens for 36% and 30% of the patients in internal and external validation, respectively. By comparison, the baseline model at the same sensitivity had a positive predictive value of 0.04 and 0.144 and recommended type and screens for 57% and 45% of the patients in internal and external validation, respectively. The most important predictor variables were overall procedure-specific transfusion rate and preoperative hematocrit.

CONCLUSIONS

A personalized transfusion risk prediction model was created using both surgery- and patient-specific variables to guide preoperative type and screen orders and showed better performance compared to the traditional procedure-centric approach.

EDITOR’S PERSPECTIVE

Blood loss and transfusion rates following total hip arthroplasty: a multivariate analysis

This study aimed to identify factors that inde- pendently predict increased rates of transfusion following total hip arthroplasty (THA) surgery. A retrospective analysis of all patients undergoing THA surgery over 12 months was performed. Electronic operative records were analysed to determine the following patient factors: American Society of Anesthesiologists (ASA) grade, body mass index (BMI), co-morbidities, indication for surgery, surgical technique, type of implant used, haematological markers, hospital length of stay (LOS) and complications. A total of 244 patients were included. There were 141 females (58%) and 103 males (42%). The median age was 65±12. The median pre-operative blood volume was 4500mls (IQR; 4000-5200). The median blood loss was 1069mls (IQR; 775-1390). The total number of patients requiring transfusion was 28 (11%), with a median of two units being transfused. Pre-operative haemoglobin (p<0.001) level, haematocrit (p<0.001) level and weight (p=0.016) were found to be predictive of transfusion requirement as well as ASA grade (p=0.005). Application of an intra-operative surgical drain was associated with higher rates of transfusion (p<0.001). Our study strengthens the evidence that pre-operative haemoglobin and haematocrit levels are valuable predictors of patients requiring transfusion. Additionally, ASA grade may be viewed as a helpful factor in predicting risk of transfusion. A strategy incorporating pre-operative optimisation of modifiable factors may reduce rates of transfusion requirement.

Simultaneous Bilateral Total Hip Arthroplasty With Contemporary Blood Management is Associated With a Low Risk of Allogeneic Blood Transfusion

BACKGROUND

There is a paucity of data on blood loss and the risk of allogeneic blood transfusion after simultaneous bilateral total hip arthroplasty (SBTHA) with contemporary blood management including neuraxial anesthesia, routine tranexamic acid use, and a restrictive transfusion protocol. As such, we sought to determine the in-hospital outcomes of SBTHA, specifically analyzing blood loss and the rate and risk factors for transfusion.

METHODS

We identified 191 patients who underwent SBTHA at a single institution from 2016 to 2019. No drains were utilized and no patients donated blood preoperatively. Mean age was 59 years with 96 females (50.3%). The surgical approach was posterior in 138 (72.3%) and direct anterior in 53 (27.7%) patients. We analyzed blood loss, the rate of allogeneic blood transfusions, and in-hospital thromboembolic complications. We analyzed risk factors for transfusion with a logistic regression analysis.

RESULTS

Twenty-two patients (11.5%) underwent allogeneic blood transfusion. All transfused patients were female. Univariate analysis revealed female gender as a transfusion risk factor since it had statistically significant higher proportion in the transfusion group than the nontransfusion group (100% vs 43.5%, respectively, P < .001). We did not identify any other singular significant risk factors for transfusion in a multivariable regression analysis. However, females with a preoperative Hb <12 had an elevated risk of transfusion at 37.5% (15/40 patients).

CONCLUSION

With contemporary perioperative blood management protocols, there is a relatively low (11.5%) risk of a blood transfusion after SBTHA. Females with a lower preoperative Hb (<12 g/dL) had the highest risk of transfusion at 37.5%.

Perioperative Blood Loss Can Be Reduced If Total Knee Arthroplasty Was Performed in the Si Hour-Period, Compared with the Wei Hour-Period: A Retrospective Cohort Study

OBJECTIVE

To investigate the efficacy and safety of performing primary unilateral total knee arthroplasty (TKA) in the "Si hour-period" meaning 09:00 a.m. to 11:00 a.m. (one of the 12 two-hour periods into which the day was traditionally divided, each being given the name of one of the 12 earthly branches), compared with the "Wei hour-period" (13:00-15:00).

METHODS

Patient documentations were studied for those who underwent a primary unilateral TKA performed by the same surgical team with a tourniquet between January 2018 and January 2021 at our medical center. Eighty-four patients were enrolled and assigned into group A (in Si hour-period) and group B (in Wei hour-period). The main outcomes were total blood cell loss (TBL), hidden blood loss (HBL), visible blood loss (VBL), maximum hemoglobin (Hb) drop, and transfusion rate. Secondary outcomes were length of hospital stay (LOS), postoperative femorotibial mechanical axis (FTMA), FTMA correction, platelet count, plasma D-dimer (D-D), prothrombin time (PT), international normalized ratio (INR), and the incidence of postoperative complications.

RESULTS

Group A showed statistical significance lower at the mean TBL, the mean HBL, and the maximum Hb drop (95% CI: -352.8 to -46.1,P=0.011, 95% CI: -348.0 to -40.1,P=0.014, and 95% CI: -9.5 to -0.7,P=0.023, respectively) after TKA than group B. The postoperative platelet count of group A was more significant than that of group B (95% CI:3.1 to 52.9, P=0.028). The VBL, transfusion rate, the LOS, postoperative FTMA, FTMA correction, plasma D-D, PT, INR, and the incidence of postoperative complications (wound complications, calf muscular vein thrombosis, infection, pulmonary embolism, and deep vein thrombosis) were similar between the two groups (P > 0.05, respectively).

CONCLUSION

Our study shows that blood loss can be reduced when TKA is performed in the "Si hour-period," which may be due to increasing platelet count, and postoperative complications did not increase, compared with the Wei hour-period. We recommend that the selective operation, such as TKA, should be performed in the "Si hour-period" in clinical practice between the two hour-period.