Risk Factors for Surgical-Site Infection Following Primary Total Knee Arthroplasty

2004 ◽  
Vol 25 (6) ◽  
pp. 477-480 ◽  
Author(s):  
Brian Minnema ◽  
Mary Vearncombe ◽  
Anne Augustin ◽  
Jeffrey Gollish ◽  
Andrew E. Simor
Keyword(s):  
Risk Factors ◽  
Total Knee Arthroplasty ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Knee Arthroplasty ◽  
Site Infection ◽  
Suction Drainage ◽  
Closed Suction ◽  
Closed Suction Drainage ◽  
Total Knee

AbstractObjective:To identify risk factors associated with the development of surgical-site infection (SSI) following total knee arthroplasty (TKA).Design:A case-control study.Setting:A 1,100-bed, university-affiliated, tertiary-care teaching hospital.Methods:Case-patients with SSI occurring up to 1 year following primary TKA performed between January 1999 and December 2001 were identified prospectively by infection control practitioners using National Nosocomial Infections Surveillance (NNIS) System methods. Three control-patients were selected for each case-patient, matched by date of surgery. Stepwise logistic regression analysis was used to determine the relation of potential risk factors to the development of infection.Results:Twenty-two patients with infections (6 superficial and 16 deep) were identified. Infection rates per year were 0.95%, 1.07%, and 1.19% in 1999, 2000, and 2001, respectively. Logistic regression analysis identified two variables independently associated with the development of infection: the use of closed suction drainage (odds ratio [OR], 7.0; 95% confidence interval [CI95], 2.1-25.0; P = .0015) and increased international normalized ratio (INR) (OR, 2.4; CI95, 1.1-5.7; P = .035). Factors not statistically associated with the development of infection included age, NNIS System risk index score, presence of various comorbidities, surgeon, duration of procedure or tourniquet time, type of bone cement or prosthesis used, or receipt of blood product transfusions.Conclusions:The use of closed suction drainage and a high postoperative INR were associated with the development of SSI following TKA. Avoiding the use of surgical drains and careful monitoring of anticoagulant prophylaxis in patients undergoing TKA should reduce the risk of infection.

Closed Suction Drainage after Primary Total Knee Arthroplasty: A Prospective Randomized Trial

2018 ◽  
Vol 31 (08) ◽  
pp. 804-810 ◽  
Author(s):  
Felix Erne ◽  
Stefanie Wetzel ◽  
Nikolaus Wülker ◽  
Marco Gesicki ◽  
Ulf Hofmann
Keyword(s):  
Total Knee Arthroplasty ◽  
Randomized Trial ◽  
Knee Arthroplasty ◽  
Prospective Randomized Trial ◽  
Postoperative Blood Loss ◽  
Suction Drainage ◽  
Closed Suction ◽  
Closed Suction Drainage ◽  
Total Knee

AbstractThe discussion as to whether or not to use closed suction drainage (CSD) after total knee arthroplasty (TKA) is still ongoing. A multitude of surgical techniques makes comparison between studies difficult. The aim of the present study was to investigate the benefit of CSD versus nondrainage following primary TKA when operating after exsanguination (by means of a rubber Esmarch bandage) with a tourniquet and without any form of hemostasis. A prospective randomized trial was performed with a homogeneous sample of 36 patients with strict inclusion and exclusion criteria. Patients were evaluated preoperatively, on a daily basis during their hospital stay, and at 6 weeks, 3 months, 6 months, and 1 year postoperatively. The use of CSD led to a significantly stronger drop in hemoglobin levels by approximately 1 g/dL (p = 0.012). Knee circumference, wound secretion, wound healing, and postoperative range of motion did not show significant differences. All discharge criteria were met in both groups by day 9. Interestingly, patients without CSD reported higher pain levels during the entire postoperative inpatient stay and also at the 6-week follow-up (p = 0.012). These differences could not be observed in longer follow-up. The use of CSD after primary TKA in this study did not lead to indispensable advantages but did lead to increased postoperative blood loss. When evaluating the advantages and disadvantages of the use of CSD after TKA from the data in the literature, special attention must be paid to the operating technique, as it has a strong impact on the results obtained.

Comparison Between Closed Suction Drainage and Nondrainage in Total Knee Arthroplasty

2011 ◽  
Vol 26 (8) ◽  
pp. 1265-1272 ◽  
Author(s):  
Qi-dong Zhang ◽  
Wan-shou Guo ◽  
Qian Zhang ◽  
Zhao-hui Liu ◽  
Li-ming Cheng ◽  
...  
Keyword(s):  
Total Knee Arthroplasty ◽  
Knee Arthroplasty ◽  
Suction Drainage ◽  
Closed Suction ◽  
Closed Suction Drainage ◽  
Total Knee

scholarly journals Closed Suction Drainage Is Not Associated with Faster Recovery after Total Knee Arthroplasty

2016 ◽  
Vol 8 (2) ◽  
pp. 226-233 ◽  
Author(s):  
Duan Wang ◽  
Jin Xu ◽  
Wei-nan Zeng ◽  
Kai Zhou ◽  
Tian-hang Xie ◽  
...  
Keyword(s):  
Total Knee Arthroplasty ◽  
Knee Arthroplasty ◽  
Suction Drainage ◽  
Closed Suction ◽  
Closed Suction Drainage ◽  
Total Knee

Artificial neural network prediction of same-day discharge following primary total knee arthroplasty based on preoperative and intraoperative variables

2021 ◽  
Vol 103-B (8) ◽  
pp. 1358-1366
Author(s):  
Chapman Wei ◽  
Theodore Quan ◽  
Kevin Y. Wang ◽  
Alex Gu ◽  
Safa C. Fassihi ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Total Knee Arthroplasty ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Knee Arthroplasty ◽  
Logistic Regression Model ◽  
Ann Model ◽  
Same Day Discharge ◽  
Total Knee

Aims This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA). Methods Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay. Results The predictability of the ANN model, area under the curve (AUC) = 0.801, was similar to the logistic regression model (AUC = 0.796) and identified certain variables as important factors to predict same-day discharge. The ten most important factors favouring same-day discharge in the ANN model include preoperative sodium, preoperative international normalized ratio, BMI, age, anaesthesia type, operating time, dyspnoea status, functional status, race, anaemia status, and chronic obstructive pulmonary disease (COPD). Six of these variables were also found to be significant on logistic regression analysis. Conclusion Both ANN modelling and logistic regression analysis revealed clinically important factors in predicting patients who can undergo safely undergo same-day discharge from an outpatient TKA. The ANN model provides a beneficial approach to help determine which perioperative factors can predict same-day discharge as of 2018 perioperative recovery protocols. Cite this article: Bone Joint J 2021;103-B(8):1358–1366.

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