ObjectiveTo study the effects of PDCA cycle in the control of surgical site infection (SSI). MethodsA total of 1 761 surgeries between January 2012 and December 2013 were chosen to be monitored. PDCA cycle was used as a tool of total quality management evaluation to enhance the control of SSI. ResultsAfter 2 to 4 cycles of PDCA, the preventive medication rate of ClassⅠ operation incision was decreased significantly (χ2=309.513，P<0.001) and the postoperative incision infection rate did not change significantly (χ2=1.474，P=0.669). ConclusionUsing PDCA cycle can increase SSI management level and quality significantly and total quality management can be operated effectively.
ObjectiveTo investigate the impact of comprehensive interventions on the prevention of the incidence of surgical site infection (SSI) after hip or knee arthroplasty.MethodsPatients who underwent total hip and knee arthroplasty for the first time in orthopedics department of Chengdu Fifth People’s Hospital from January 2016 to March 2018 were selected. The patients were observed after surgery for 1 year, and divided into the control group and the treatment group according to the odd or even hospitalization number. Basic precautions were taken in the control group, while further comprehensive preventive measures (preoperative chlorhexidine bath, intraoperative body temperature maintenance, using antibacterial film over surgery area without shearing, health and education after discharge from hospital) were taken in the treatment group. The incidence of SSI of the two groups was compared to evaluate the effects of comprehensive interventions.ResultsA total of 341 patients were included, including 174 in the control group and 167 in the treatment group. No one failed to be followed up. Among the 341 patients undergoing surgery, 13 had SSI, including 11 (6.3%) in the control group and 2 (1.2%) in the treatment group. The incidence of SSI in the treatment group was lower than that in the control group (χ2=6.102, P=0.014). Single factor analysis showed that sex (χ2=10.933, P=0.001), preoperative chlorhexidine sponge bath (χ2=8.837, P=0.003), intraoperative thermal insulation (χ2=13.917, P<0.001), health education (χ2=12.671, P<0.001), skin preparation methods (χ2=6.102, P=0.014), perioperative blood glucose control (χ2=17.512, P=0.003), and surgical type (χ2=8.360,factor P=0.004) were the effect factors of occurrence of SSI. Logistic regression analysis showed that surgical type [odds ratio (OR)=0.129, 95% confidence interval (CI)(0.026, 0.640), P=0.012] and strict blood glucose control [OR=9.868, 95%CI (2.158, 45.131), P=0.003] were the independent factors affecting the occurrence of SSI.ConclusionsComprehensive intervention measures can effectively reduce the occurrence of SSI after hip and knee arthroplasty. It is not confirmed that preoperative chlorhexidine bath can reduce the occurrence of SSI. But choosing selective operation and controlling the perioperative blood glucose below 200 mg/dL can reduce the risk of SSI.
Objective To probe the distribution and drug resistance of pathogens causing surgical site infection in patients after gynecologic operation, and provide reference for prevention and treatment. Methods Seventy patients with incision infection after gynecologic operation in West China Second University Hospital of Sichuan University from January 2010 to May 2015 were selected. Species of the pathogens from the submitted specimens and the results of the drug susceptibility testing were analyzed. Results Seventy-two strains of pathogens were isolated, including 36 strains (50.0%) of Gram-negative (G–) bacteria and 36 strains (50.0%) of Gram-positive (G+) bacteria. The main G– bacteria were Escherichia coli (36.1%) and Enterobacter cloacae (5.6%); the main G+ bacteria were Staphylococcus aureus (18.1%), Staphylococcus epidermidis (12.5%), and Enterococcus faecalis (8.3%). Escherichia coli showed low sensitivities to ampicillin, ceftriaxone, and gentamicin, with resistance rates of 76.9%, 61.5%, and 61.5%, respectively. Staphylococcus aureus showed low sensitivities to penicillin G, clindamycin, and erythromycin, with resistance rates of 92.3%, 69.2%, and 61.5%, respectively. Staphylococcus epidermidis showed low sensitivities to erythromycin, penicillin G, and ciprofloxacin, with resistance rates of 88.9%, 77.8%, and 77.8%, respectively. No carbapenem-resistant G– bacteria or vancomycin-resistant G+ bacteria were detected. Conclusion Postoperative surgical site infection is the most common nosocomial infection. The main bacteria related to postoperative incision infection in the gynecology department of the hospital are Escherichia coli, Staphylococcus aureus, Staphylococcus epidermidis, and Enterococcus faecalis, which become resistant to common antibiotics currently. Therefore more attention should be paid to bacterial isolation and drug susceptibility test results for rational use of antimicrobial drugs and effectiveness of the treatment to nosocomial infection.
ObjectiveTo study the present situation of hospital orthopedic surgery incision infection, in order to provide the basis for further intervention. MethodsProspective investigation combined with retrospective investigation method was adopted in our study to perform a statistical analysis on orthopedic surgery incision infections among 545 patients in our hospital between January and December 2012. ResultsDuring the one year of follow-up, there were 10 cases of surgical incision infection among all the 545 patients, with an infection rate of 1.83%. The infection rate of class-Ⅰ incision was 0.46%, of class-Ⅱ was 5.13%, and of class-Ⅲ/Ⅳ was 12.12%, and the Cochrane-Armitage trend chi-square test showed significant trend among them (χ2=28.273, P<0.001). Based on different operation risk index, patients with index 1, 2, 3 had a surgical site infection rate of 0.82%, 2.60%, and 18.75%, respectively. The higher the index, the higher the surgery incision infection rate, and the trend was statistically significant (χ2=12.916, P<0.001). The infection rate was 1.43% for elective surgical procedures, and was 3.15% for emergency surgery, but there was no significant difference (P>0.05). ConclusionOrthopedic surgery has a high-risk surgical site infection rate, and incision classification and surgical risk index have statistical correlation with the incidence of hospital infection. In order to ensure the security of patients and reduce medical disputes, we should pay close attention to orthopedic surgery infection.
ObjectiveTo establish a predictive model of surgical site infection (SSI) following colorectal surgery using machine learning.MethodsMachine learning algorithm was used to analyze and model with the colorectal data set from Duke Infection Control Outreach Network Surveillance Network. The whole data set was divided into two parts, with 80% as the training data set and 20% as the testing data set. In order to improve the training effect, the whole data set was divided into two parts again, with 90% as the training data set and 10% as the testing data set. The predictive result of the model was compared with the actual infected cases, and the sensitivity, specificity, positive predictive value, and negative predictive value of the model were calculated, the area under receiver operating characteristic (ROC) curve was used to evaluate the predictive capacity of the model, odds ratio (OR) was calculated to tested the validity of evaluation with a significance level of 0.05.ResultsThere were 7 285 patients in the whole data set registered from January 15th, 2015 to June 16th, 2016, among whom 234 were SSI cases, with an incidence of SSI of 3.21%. The predictive model was established by random forest algorithm, which was trained by 90% of the whole data set and tested by 10% of that. The sensitivity, specificity, positive predictive value, and negative predictive value of the model were 76.9%, 59.2%, 3.3%, and 99.3%, respectively, and the area under ROC curve was 0.767 [OR=4.84, 95% confidence interval (1.32, 17.74), P=0.02].ConclusionThe predictive model of SSI following colorectal surgery established by random forest algorithm has the potential to realize semi-automatic monitoring of SSIs, but more data training should be needed to improve the predictive capacity of the model before clinical application.
Surgical site infection (SSI) is a common hospital acquired infection that can increase medical burden and affect patient prognosis. Its occurrence involves multiple factors such as the patient’s basic condition and perioperative management quality. Although there is a basic consensus on SSI prevention in domestic and foreign guidelines, there are still differences between the recommendations in the guidelines and infection prevention and control management. To further promote the implementation of the guidelines, this article reviews the key preventive measures for SSI in domestic and foreign guidelines from preoperative skin preparation, intraoperative standardized operation, and postoperative incision management, and explores in depth the management strategies of SSI, in order to provide a reference for building a full process infection prevention and control system for SSI.
Objective To study the influence factors of surgical site infection (SSI) after hepatobiliary and pancreatic surgery. Methods Fifty patients suffered from SSI after hepatobiliary and pancreatic surgery who treated in Feng,nan District Hospital of Tangshan City from April 2010 and April 2015 were retrospectively collected as observation group, and 102 patients who didn’t suffered from SSI after hepatobiliary and pancreatic surgery at the same time period were retrospectively collected as control group. Then logistic regression was performed to explore the influence factors of SSI. Results Results of univariate analysis showed that, the ratios of patients older than 60 years, combined with cardiovascular and cerebrovascular diseases, had abdominal surgery history, had smoking history, suffered from the increased level of preoperative blood glucose , suffered from preoperative infection, operative time was longer than 180 minutes, American Societyof Anesthesiologists (ASA) score were 3-5, indwelled drainage tube, without dressing changes within 48 hours after surgery, and new injury severity score (NISS) were 2-3 were higher in observation group (P＜0.05). Results of logistic regression analysis showed that, patients had history of abdominal surgery (OR=1.92), without dressing changes within 48 hours after surgery (OR=2.07), and NISS were 2-3 (OR=2.27) had higher incidence of SSI (P＜0.05). Conclusion We should pay more attention on the patient with abdominal surgery history and with NISS of 2-3, and give dressing changes within 48 hours after surgery, to reduce the incidence of SSI.
It has been certificated that hip and knee arthroplasty can improve quality of life and relieving pain and discomfort for ageing population and patients with muscloskeletal disorders. However, the outcomes of prosthetic joint infections (PJI) after arthroplasty usually are disastrous. The incidence of PJI is lower, but the number of this population is huge, which makes the strong impacts on quality of life for patients and healthcare economics. This review discusses the prevention strategies of PJI based on clinical epidemiology, diagnostic definition, pathogenesis, microbiology and risk factors, combined with some guidelines for prevention surgical site infections published recently.
Surgical site infections are the common healthcare-associated infections. This article introduced the guidelines on the prevention and control of surgical site infection in using from background, making progress, and recommendations, to give directions for clinicians and infection prevention and control professionals choosing appropriately for decreasing surgical site infection risks.