Objective To analyze the trend of standardized infection ratio (SIR) of surgical site infection (SSI) in small bowel surgery, objectively evaluate the effect of infection control, and provide evidence-based strategies for SSI prevention. Methods According to Centers for Disease Control and Prevention (CDC) / National Healthcare Safety Network (NHSN) surveillance definitions for specific types of infections and the monitoring methods of SSI events published by NHSN, the SSI and related risk factors of adult inpatients undergoing small bowel surgery in Yichang Central People’s Hospital between January 1, 2016 and December 31, 2022 were prospectively monitored. The inpatients undergoing small bowel surgery that meets the definition of International Classification of Diseases, 10th Revision Clinical Modifications/Procedure Coding System (ICD-10-CM/PCS), a multivariate binary logistic regression model was used to calculate the predicted infections in each year, the model included the risk factors for small bowel surgery in NHSN Complex Admission/Readmission (A/R) SSI Model with 7 years of surveillance data as the baseline. The SIR was calculated by dividing the number of observed SSI by the number of predicted SSI in each year. The Mid-P method was used to test the difference of SIR compared to the previous year, and the linear regression model was used to analyze the trend of SIR. Results A total of 2 436 patients were included, with 48 cases of deep incision infection and 49 cases of organ/cavity infection, and the overall incidence rate of infection was 4.0%. From 2016 to 2022, there were 151, 244, 222, 260, 320, 408, and 831 patients who underwent small bowel surgery, respectively. The Mid-P test showed that there was a significant difference in SIR from 2016 to 2019 (P<0.05), and there was an increase in 2018 compared with 2017. There was no significant difference in SIR compared to the previous year from 2019 to 2022 (P>0.05), and there was no significant difference in the trend of SIR of SSI (P=0.065). Conclusions From January 1, 2017, to December 31, 2022, advances have been made in SSI control practices of small bowel surgery in six consecutive years, except for 2018, but there was no annual downward trend from 2020 to 2022. The use of SIR provides a new approach for evaluating the quality of infection control.
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.
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.
ObjectiveTo systematically review the effect of perioperative supplemental oxygen administration on surgical site infection (SSI) in patients underwent abdominal surgery with general anesthesia. MethodsDatabases including PubMed, EMbase, The Cochrane Library (Issue 2,2015), CBM, VIP, WanFang Data and CNKI were searched to collect randomized controlled trials (RCTs) about perioperative supplemental oxygen administration versus normal FiO2 in patients underwent abdominal surgery with general anesthesia from inception to March, 2015. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Then, meta-analysis was conducted using RevMan 5.3 software. ResultsA total of 13 RCTs involving 3 532 patients were included. The results of meta-analysis indicated that: the incidence of SSI in the perioperative supplemental oxygen administration group was lower than that in the control group (OR=0.68, 95%CI 0.47 to 0.99, P=0.04). There were no significiant differences between both groups in incidence of atelectasis, incidence of infection requiring reoperation and 30-day mortality after surgery (all P values >0.05). ConclusionPerioperative supplemental oxygen administration could further decrease the risk of SSI in patients underwent abdominal surgery with general anesthesia, and does not increase the risk of other adverse events. Due to the limitations of quality of included studies, more high quality studies are needed to verify the above conclusions.
ObjectiveTo analyze the relevant factors for surgical site infection. MethodsA total of 677 cases of surgery in one hospital from July 1 to December 31 in 2012 were surveyed (not including implant and cardiac intervention surgeries), which were divided into different groups according to the preoperative incision contamination level, and the postoperative healing of incisions were observed closely. After the patients were discharged, we investigated the situation of incisions by phone or periodic review, and forms were filled in on schedule. ResultsBy follow-up evaluation of the 677 cases, the incisions in 12 cases were infected and the infection rate was 1.77%. Polluted and infected (14.28%, 30.76%) incisions caused more infection than the clean and clean-polluted incisions (0.00%, 0.59%). The patients who stayed in hospital for 4 or more than 4 days before surgeries (infection rate was 4.55%) took more risk of infection than the patients whose preoperative time in hospital were 2-3 days (infection rate was 0.60%) and 1 or shorter than 1 day (0.68%). Perioperative use of antibiotics for longer than 72 hours will increase the risk of incision infection than those within 48 hours (7.69%, 0.00%; P=0.002). ConclusionSurgical site infection is related to the incision type. Shortening the preoperative in-hospital time will reduce the risk of infection. Long time use of antibiotics in perioperative period cannot prevent the postoperative infection effectively, but may increase the risk of 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.
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.