Analysis Of Risk Factors For Postoperative Infections After Open Biliary Surgery And Its Preventive Strategies

Background&Aims:Biliary surgery is one of the most important surgeries. Due to its sophisticated anatomy, operations for this kind of disease are rather difficult. With the rise and development of laproscopic technology, many surgeries including laproscopic cholecystectomy can be performed via MIS (minimally invasive surgery) thus decreasing postoperative complications, most biliary operations are sill being performed by conventional "open" method. Post-operative infection after laparotomy is the most frequent complication with high incidence even in current surgical units which increases not only length of hospital stay but aloso medical cost, greatly influencing patients’prognosis. Thus, reducing the incidence of post-operative infection after open biliary surgery is of great clinical significance. No efficient strategy so far has been shown effective in reducing postoperative infection incidence following biliary tract surgery. One possible solution might be ascertaining risk factors for postoperative infections by analyzing possible underlying influential factors. Contrary to foreign counterparts, studies on risk factors for post-operative infection following open biliary surgery in domestic academic circles are rare and even there have, mainly with univariate analysis. Compared with univariate analysis, multiple variable analysis ensures a more reliable conclusion taking into account interaction and interconnections between individual factors. Based on what we call the clinical "Big Data", we aim to apply data mining methods to analyze factors associated with postoperative infections after open biliary surgery and to establish risk prediction models for early discovery of patients with high risks for developing postoperative infections, thus minimizing post operative infection.Methods:Patients who underwent open biliary surgeries at the Department of Hepato-biliary-pancreatic Surgery (Surgery V), the Second Affiliated Hospital, Zhejiang University School of Medicine between January2012and October2014were identified. Data on general characteristics, past history, perioperative details, as well as postoperative complications were collected and analyzed. Reviewing Sabiston Textbook of Surgery and other literatures, thirty-one factors possibly leading to post-operative infection were included. Univariate analysis for these factors using SPSS13.0were performed at the test level0.05. Stepwise logistic regression were performed for factors with significance (p<0.05) to obtain independent risk factors. Thereafter we calculate the odds ratio for each influencing factors. Eventually regression models are constructed which is later to be tested its accuracy, sensitivity and specificity using samples from subsequent newly admitted patients. Diagnosis of postoperative infections were independently made by two physicians, based on the Criteria of Hospital Infection published by Ministry of Health of the People’s Republic of China in2001, Monitoring Norm for Nosocomial Infection published by the affliated Xiangya hospital of Zhongnan University and occupational standard for biliary infection with reference to actual clinical manifestation, and were then confirmed by the attending physicians.Results:A total of576cases were included in the analysis. The incidence rate of the overall postoperative complications was28.12%(162cases). The incidence for the abdominal and biliary infection are11.50%and10.80%respectively. Univariate logistic regression analysis revealed the factors associated with postoperative infections are as follows:namely gender, obesity, past abdominal surgery times, pre-operative albumin, PT, pre-operative fever, white blood counts, CRP, preoperative infections, pre-operative administration of antibiotics, ASA class, operation time, estimated blood loss, blood transfusion, ICU stay, post-operative fever and delayed extubation.Further multivariate logistic regression for the above17parameters with p<0.05in Univariate logistic regression suggest that blood transfusion, obesity and ASA class are included in the regression prediction model. Power according to the order for these three factors in regression are blood transfusion (OR=5.342, P=0.000), obesity (OR=3.291, P=0.000) and ASA grading (OR=1.508, P=0.013)respectively. Data for newly admitted patients were generated into the equation for comparison between the prediction value and the actual value at the cutoff point0.5. Validation shows the accuracy, sensitivity, specificity, and AUC of logistic regression model were80%,65.63%,85.23%and0.837respectively.Conclusions:Postoperative infection rates after open biliary surgery remained considerable. Several factors were significantly associated with this. Our study shows that blood transfusion, obesity, and ASA class are independent risk factors for post-operative infection after open biliary surgery which should be paid special attention to.