Literature DB >> 26316722

Risk factors for surgical site infection in a teaching hospital: a prospective study of 1,138 patients.

Keping Cheng1, Jiawei Li1, Qingfang Kong1, Changxian Wang1, Nanyuan Ye1, Guohua Xia1.   

Abstract

BACKGROUND: The purpose of this study was to identify risk factors for surgical site infection (SSI) in a teaching hospital.
METHODS: A prospective study was initiated to investigate risk factors for SSI at a university-affiliated tertiary care center from July 2013 to December 2014. The chi-square test for categorical variables was used to determine the significance of association, whereas the multivariate logistic regression model was used to examine independent risk factors for SSI.
RESULTS: A total of 1,138 patients met the inclusion criteria, in whom 36 cases of infection occurred during the hospitalization period and two cases occurred after discharge. Univariate analysis showed that SSI was associated with the type of operation, wound classification, volume of blood loss, blood transfusion, American Society of Anesthesiology score before surgery, risk index, duration of surgery, diabetes, cancer, gastrointestinal catheter, urinary catheter, postoperative drainage, and preprocedural white blood cell count. Multivariate analysis identified six independent parameters correlating with the occurrence of SSI: diabetes (odds ratio [OR] 6.400; 95% confidence interval [CI] 2.582-15.866; P=0.000); cancer (OR 2.427; 95% CI 1.028-5.732; P=0.043); preprocedural white blood cell count more than 10×10(9)/L (OR 6.988; CI 3.165-15.425; P=0.000); wound classification (clean contaminated [OR: 7.893; CI: 2.244-27.762; P=0.001]; contaminated [OR: 7.031; CI: 1.652-29.922; P=0.008]; dirty [OR: 48.778; CI: 5.418-439.164; P=0.001]); operative duration more than 120 minutes (OR 4.289; CI 1.773-10.378; P=0.001); and postoperative drainage (OR 3.957; CI 1.422-11.008; P=0.008).
CONCLUSION: Our data suggest that all these risk factors could be regarded as potential indicators of SSI and that relevant preventive measures should be taken to reduce SSI and improve patient outcomes.

Entities:  

Keywords:  nosocomial infection; risk factors; surgical site infection; wound classification

Year:  2015        PMID: 26316722      PMCID: PMC4542557          DOI: 10.2147/PPA.S86153

Source DB:  PubMed          Journal:  Patient Prefer Adherence        ISSN: 1177-889X            Impact factor:   2.711


Introduction

The surgery department is a place with a high incidence of nosocomial infection, and accumulating evidence suggests advances have been made in infection control practices,1,2 including improved operating room ventilation, sterilization methods, barriers, surgical techniques, and availability of antimicrobial prophylaxis. However, surgical site infection (SSI) remains a substantial cause of morbidity, prolongs hospitalization, and increases death. SSI rates have been reported to range from less than 1% to more than 10%, and 75% of SSI-associated deaths are directly attributable to SSI.3 The occurrence of SSI is not only a serious threat to the patient’s health and life, but also imposes a substantial economic burden on the patient’s family and society.4–6 Early diagnosis and treatment of infection is essential in the care of surgical patients. Thus, it is urgent that we identify the factors responsible for SSI and, if possible, corresponding measures should be taken to prevent the occurrence of nosocomial infection, alleviate patientspain, speed their recovery, and reduce their medical expenses.

Subjects and methods

This study was carried out prospectively at the Department of Infection Control, Zhongda Hospital, which has more than 2,600 beds and is affiliated to Southeast University. The study was approved by the ethics committee of Southeast University.

Study population

A total of 1,138 patients who had surgery at the teaching hospital affiliated to Southeast University from July 2013 to December 2014, were studied prospectively. Patients admitted to the hospital for more than 1 day were included, while outpatients and those who had surgery elsewhere before referral to our hospital were excluded.

Survey method

Based on patient information gathered from the computer network system and from ward rounds in the teaching hospital, system monitoring of SSI was filled in survey forms according to the software of Nosocomial Infection Monitoring Management System developed by Beijing Minke Medical Electronic Technology Research Institute. All patients were followed up from the time of admission until the time of discharge and 30 days postoperatively to inspect the incidence of SSI.7

Diagnostic criteria

Patients were evaluated for SSI according to the Nosocomial Infection Diagnostic Criteria published by China’s Ministry of Health in 2001.8

Risk index calculation

According to the Monitoring Standard of Nosocomial Infection requirements issued by the Ministry of Health, the risk index for each operation in this survey was calculated according to the accumulation points of three risk factors, ie, operative duration, surgical wound classification system, and American Society of Anesthesiology (ASA) score. In our daily work, the risk index for each operation was automatically generated by the Nosocomial Infection Monitoring Management System software using the aforementioned factors.

Statistical analysis

All of the data were checked and analyzed with Statistical Package for the Social Sciences version 19.0 software (SPSS Inc., Chicago, IL, USA). First, descriptive statistics, including count and percentage, were used to describe the demographic characteristics of the subjects. Univariate analysis for association between identified risk factors and SSI was performed using chi-square tests for discrete variables, and P<0.05 was accepted as statistically significant. When the P-value was less than 0.05, multivariate logistic regression was performed using the stepwise forward method to identify those factors most significantly associated with risk of infection; the P-value for significance was set at 0.01 and the results are presented with an odds ratio (OR) and a 95% confidence interval (CI).

Study limitation

Either chlorhexidine bathing or normothermia could have contributed to the low prevalence of SSI.

Results

Patient information

Details on 1,138 patients who underwent breast, hernia, esophagus, stomach, appendix, colon, or rectal surgery at a university-affiliated tertiary care center were retrieved from an SSI database. The mean patient age was 54.62 (range 2–92) years; 542 were male and 596 were female.

Incidence and cause of SSI

Our analysis showed that 38 of the 1,138 patients suffered from SSI, giving an incidence of 3.34%. Thirty-six of the SSI cases occurred during hospitalization and two occurred after discharge. The 38 cases comprised 30 superficial incisional infections, six deep incisional infections, and six, two organ/space infections. Twenty bacterial strains were isolated from the infected surgical incision sites, including Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa.

Univariate analysis

The association between potential risk factors and SSI was performed using the chi-square test for discrete variables. Risk factors significantly associated with SSI were diabetes, cancer, wound classification, ASA scores before surgery, pre-procedural white blood cell count (WBC), type of surgery, volume of blood loss, blood transfusion, operative duration, risk index, use of a gastrointestinal or urinary catheter, and postoperative drainage. In contrast, risk factors determined not to be significantly associated with SSI were sex, age, skin preparation, use of a trachea cannula, antibiotic prophylaxis, and type of anesthesia (P>0.05; Table 1).
Table 1

Analysis of patient factors related to surgical site infections using the chi-square test

Risk factor (n)Infection cases (incidence, %)χ2 (P-value)
Sex
 Male (542)19 (3.5)0.089
 Female (596)19 (3.2)(0.776)
Age (years)
 <75 (977)29 (3.0)2.944
 ≥75 (161)9 (5.6)(0.086)
Pre-morbidity
Diabetes
 Yes (77)11 (14.3)30.660
 No (1,061)27 (2.5)(0.000)
Cancer
 Yes (119)10 (8.4)10.559
 No (1,019)28 (2.7)(0.001)
Wound classification
 Clean (639)3 (0.5)
 Clean contaminated (379)24 (6.3)60.768
 Contaminated (112)8 (7.1)(0.000)
 Dirty (8)3 (37.5)
ASA score before operation
 Level I (387)3 (0.8)
 Level II (576)19 (3.3)33.411
 Level III (139)13 (9.4)(0.000)
 Level IV (9)2 (22.2)
 Level V (27)1 (3.7)
Skin preparation
 Yes (423)13 (3.1)0.147
 No (715)25 (3.5)(0.701)
Preprocedural WBC (×109/L)
 ≤10 (988)20 (2.0)40.151
 >10 (150)18 (12.0)(0.000)
Type of surgery
 Selective (972)24 (2.5)15.628
 Emergency (166)14 (8.4)(0.000)
Type of anesthesia
 General anesthesia (812)32 (3.9)4.225
 Balanced anesthesia (48)2 (4.2)(0.376)
 Epidural anesthesia (13)0 (0.0)
 Local anesthesia (263)4 (1.5)
 Other (2)0 (0.00)
Volume of blood loss (mL)
 <200 (869)19 (2.2)18.057
 200–400 (213)13 (6.1)(0.000)
 ≥400 (56)6 (10.7)
Blood transfusion
 Yes (56)6 (10.7)9.925
 No (1,082)32 (3.0)(0.002)
Risk index
 0 (673)9 (1.3)
 1 (377)22 (5.8)22.001
 2 (78)4 (5.1)(<0.000)
 3 (10)3 (30.0)
Operative duration (minutes)
 <120 (553)8 (1.4)11.937
 ≥120 (585)30 (5.1)(0.001)
Catheter
Gastrointestinal catheter
 Yes (353)25 (7.1)22.212
 No (785)13 (1.7)(0.000)
Urinary catheters
 Yes (421)23 (2.1)9.339
 No (717)15 (5.5)(0.002)
Trachea cannula
 Yes (402)13 (3.2)0.021
 No (736)25 (3.4)(0.884)
Postoperative drainage
 Yes (539)33 (6.1)24.576
 No (599)5 (0.8)(0.000)
Antibiotic prophylaxis
 Yes (944)28 (3.0)2.388
 No (194)10 (5.2)(0.122)

Abbreviations: ASA, American Society of Anesthesiologists; WBC, white blood cell count.

Multivariate logistic regression analysis

Based on the results of the chi-square test, six risk factors identified in univariate analysis were analyzed further by multivariate logistic regression analysis using a forward conditional model (Table 2). This analysis identified six parameters as independent markers for occurrence of SSI: diabetes (OR 6.400; 95% CI 2.582–15.866; P=0.000); cancer (OR 2.427; CI 1.028–5.732; P=0.043); preprocedural WBC more than 10×109/L (OR 6.988; CI 3.165–15.425; P=0.000); wound classification (clean contaminated [OR: 7.893; CI: 2.244–27.762; P=0.001]; contaminated [OR: 7.031; CI: 1.652–29.922; P=0.008]; dirty [OR: 48.778; CI: 5.418–439.164; P=0.001]); operative duration more than 120 minutes (OR 4.289; CI 1.773–10.378; P=0.001); and postoperative drainage (OR 3.957; CI 1.422–11.008; P=0.008).
Table 2

Analysis of risk factors for surgical site infection using a multivariate logistic regression model

Risk factorVariables in the equation
Reference
βSEWaldP-valueOR95% CI
Diabetes1.8560.46316.0590.0006.4002.582–15.866No
Cancer0.8870.4384.0930.0432.4271.028–5.732No
Preprocedural WBC (×109/L)
 >101.9440.40423.1570.0006.9883.165–15.425≤10
Wound classification
 Clean contaminated2.0660.64210.3640.0017.8932.244–27.762Clean
 Contaminated1.9500.7396.9660.0087.0311.652–29.922
 Dirty3.8871.12112.0200.00148.7785.418–439.164
Operative duration (minutes)
 ≥1201.4560.45110.4330.0014.2891.773–10.378<120
 Postoperative drainage1.3750.5226.9420.0083.9571.422–11.008No

Notes: β indicates the partial regression coefficient, and 95% CI is credibility interval of 95% standard partial regression coefficient.

Abbreviations: CI, confidence interval; OR, odds ratio; SE, standard error; WBC, white blood cell count.

Discussion

SSIs are the second most common type of adverse events occurring in hospitalized patients following surgery and are one of the most common surgical complications.9–12 SSI surveillance is integral to hospital infection control and quality improvement programs, with feedback of SSI rates being an important component of SSI reduction strategies.13 The incidence of SSI differs widely from hospital to hospital and from one geographic location to another.14 In the People’s Republic of China, surgical site infections are still one of the leading causes of morbidity and mortality among patients undergoing major surgery. The incidence of SSI in various hospitals varies from 13.0% to 18.0%, and accounts for 25.0% of all nosocomial infection,1 which is higher than in other countries.3 The incidence of SSI in our survey was 3.34%, which is far lower than that of the national average.15 This finding is likely to be the result of a multifactorial approach to improving patient safety and outcomes, especially the clinical real-time network monitoring performed since 2011. Moreover, the results of logistic regression analysis showed that SSI was related to type of operation, wound classification, volume of blood loss, blood transfusion, ASA score before operation, risk index, operative duration, diabetes, cancer, use of a gastrointestinal or urinary catheter, postoperative drainage, preprocedural WBC, suggesting that all patients having any type of operative procedure should be monitored for potential triggers of SSI in routine clinical practice. The potential risk factors for SSI in surgical patients in our present study were assessed, and details were recorded preoperatively, intraoperatively, and postoperatively. Various patient risk factors were found to predict the incidence of SSI, in agreement with previously reported findings.16 In our present study, an association was found between the age of surgical patients and SSI, suggesting that patients aged over 75 years (5.6%) were more likely to develop SSI than those under the age of 75 years (3.0%). However, this association failed to reach statistical significance (P>0.05). The lack of a significant association in this study may be due to the fact that elderly patients with chronic underlying disease often have decreased physiological defense mechanisms and poorer immune function. Therefore, elderly patients should undergo elective surgery when their bodies are in good condition. The clinical relevance of these findings is that patients suffering from serious pre-existing disease, such as diabetes or cancer, are at high risk of developing SSI. In this study, there was a significant correlation between existing cancer and the likelihood of SSI. This is similar to the findings of other study of SSI.7 Further, published reports have demonstrated that patients with diabetes are more susceptible to wound infection because of impaired neutrophil chemotaxis and phagocytosis.17,18 The incidence of SSI in diabetic patients was higher, and there was a significant difference between the diabetic and non-diabetic groups in our survey. This is in accordance with the literature, which shows that patients suffering from pre-morbid diseases are at high risk of SSI.19 Moreover, the results of our multivariate logistic regression analysis showed that diabetes was an independent risk factor for SSI (OR 6.400; 95% CI 2.582–15.866). As we know, the risk of SSI is very different for a patient who is having surgery to remove cancer when compared with a patient who is healthy and having knee replacement surgery. Thus, preexisting disease may be one of the possible risk factors of SSI, but it is important to consider the type of disease presented. Despite improvements in operating room practices, instrument sterilization methods, surgical technique, and the best efforts of infection prevention strategies, SSI remains a major cause of hospital-acquired infections and rates are increasing globally even in hospitals with the most modern facilities and standard protocols for preoperative preparation.7 Thus, SSI is considered to be one of the most common and serious anesthetic and surgical complications.20 It is well known that intraoperative or postoperative variable factors for SSI may reflect surgical technique more than patient case-mix. Emergency operative procedures do not allow for the standard preoperative preparation normally done within a facility for a scheduled operation (eg, confirmation of stable vital signs, adequate antiseptic skin preparation, and decontamination of the colon in advance of colon surgery). As shown in Table 1, the incidence of SSI in emergency surgery cases was higher than in elective surgery cases (8.4% versus 2.5%, respectively), which is in accordance with other studies.21,22 Patients with acute abdominal pain account for the majority of emergency surgeries, and are at high perioperative risk for SSI because of the infected operation, especially at the preoperative infection lesions. On the other hand, most of the emergency surgeries were carried out beyond normal duty working hours and inadequate preoperative preparation might be a possible explanation for the higher incidence of SSI. Therefore, it is of high importance to strengthen the management of emergency surgery. The type of anesthesia used depends on the procedure being performed and the patient’s health, age, and preferences. Several studies have reported an increased SSI rate in patients undergoing general anesthesia when compared with those undergoing regional anesthesia.23,24 However, there was no significant difference between them in our study. This finding has been proved by another study.15 Before each operative procedure, at least one incision (including for the laparoscopic approach) is made through the skin or mucous membrane, or reoperation via an incision that was left open.25 Surgical wound classification has long been established as an important predictor of postoperative SSI.26 The present survey showed that the incidence of SSI was higher in patients with a contaminated incision than in those with a clean or clean contaminated incision. The results of our multivariate logistic regression analysis further showed that wound classification was an independent risk factor for SSI, and the 95% CI for a dirty wound was much wider than the other ones of wound classification, but this may reflect the relatively small number of patients. We isolated 20 strains of bacteria, including E. coli, S. aureus, and P. aeruginosa, from infected surgical incision sites. Therefore, preventive measures should be strengthened for operations involving a contaminated incision, such as skin incision protection, minimizing contamination in the surgical field, and use of antibiotics. Reducing SSI while minimizing antibiotic resistance remains a challenge for many health care institutions. Use of perioperative antibiotics for incisions susceptible to infection did not seem to reduce the risk of SSI in our setting, as in other reports.27,28 The lack of statistical significance could be explained in part by the lack of a perioperative antibiotic policy regarding different procedures for those patients in our study. Further, use of surgical drains as well as arteriovenous catheters and tracheal cannulae has been reported to be associated with an increased risk of SSI,29,30 and multivariate analysis identified use of an arteriovenous catheter as a risk factor for SSI in our study. In contrast, tracheal cannulation was not associated with SSI. Thus, arteriovenous catheterization can alert surgeons to the increased risk of SSI, and nurses should be familiar with the monitoring and management of surgical drains to reduce this risk.31 An operative duration of longer than 2 hours has previously been reported to be associated with SSI due to the increased duration of exposure to microorganisms in the operating theater,32,33 and appeared to be a risk factor for SSI in our univariate analysis. It has also been demonstrated elsewhere by multivariate regression that increasing operative duration is associated with a stepwise increase in SSI.1 Our multivariate logistic regression results further showed that operative duration was an independent risk factor for SSI, with an OR of 4.289 and a 95% CI of 1.773–10.378. Therefore, SSI prevention strategies focusing on longer surgical duration are needed to improve the outcomes for patients. The relationship between blood products and SSI has been a matter of debate for more than 2 decades. It has been established that the incidence of SSI increases with increasing volume of blood transfusion.34 In our study, the incidence of SSI in patients who received transfusions (10.7%) was higher than in those who did not (3.0%), suggesting that surgical patients who receive blood transfusion are more prone to SSI. Therefore, clinicians should not use blood transfusions unless absolutely necessary. The ASA score evaluates the basal status of individuals including their comorbidities, so is also a good predictor of SSI.2 SSI rates were significantly higher in patients with ASA II–V than in those with ASA I, which is in agreement with previous reports,35,36 suggesting that the ASA score before surgery has a strong influence on SSI rates in clean and clean contaminated cases. According to the National Nosocomial Infection Surveillance SSI index (comprising ASA, potential for surgical wound contamination, and duration of surgery),37 the incidence of SSI was increased for scores 0, 1, 2, and 3 (corresponding to 1.3%, 5.8%, 5.1%, and 30.0%, respectively); although the rate in patients with a score of 1 was higher than in those with a score of 2, this difference was not statistically significant, which is most likely due to the small size of the sample available for subanalysis. Based on our study and those reported by others,38,39 the incidence of SSI can be expected in those patients with high-risk factors. Like other major inflammatory markers, the WBC is a stable, well standardized, widely available, and inexpensive biomarker of systemic inflammation.40 Using multiple logistic regression, we found that an elevated procedural WBC level was an independent risk factor for development of SSI in patients undergoing a surgical procedure, which is in contrast with the findings of a previous study.41 These different results between hospitals may be related to different reference values being used in the laboratory and the number of patients involved. The main limitations of our study are related to our data set, lack of analysis of chlorhexidine bathing, normothermia, and other possible risk factors that may contribute to the low prevalence of SSI. In addition, less than 2 years of data (from July 2013 to December 2014) was considered in the analysis, and our results are not necessarily representative of other years. However, despite these limitations, our data suggest that six independent parameters are correlated with the risk of SSI and that relevant preventive measures should be implemented to reduce the incidence of SSI.
  38 in total

1.  Duration of operation as a risk factor for surgical site infection: comparison of English and US data.

Authors:  G Leong; J Wilson; A Charlett
Journal:  J Hosp Infect       Date:  2006-05-15       Impact factor: 3.926

2.  Caesarean section surgical site infection surveillance.

Authors:  A Johnson; D Young; J Reilly
Journal:  J Hosp Infect       Date:  2006-07-05       Impact factor: 3.926

3.  Leukocyte count as a predictor of cardiovascular events and mortality in postmenopausal women: the Women's Health Initiative Observational Study.

Authors:  Karen L Margolis; JoAnn E Manson; Philip Greenland; Rebecca J Rodabough; Paul F Bray; Monika Safford; Richard H Grimm; Barbara V Howard; Annlouise R Assaf; Ross Prentice
Journal:  Arch Intern Med       Date:  2005-03-14

4.  Anesthetic management and surgical site infections in total hip or knee replacement: a population-based study.

Authors:  Chuen-Chau Chang; Hsiu-Chen Lin; Hui-Wen Lin; Herng-Ching Lin
Journal:  Anesthesiology       Date:  2010-08       Impact factor: 7.892

5.  Predictors of surgical site infection after open lower extremity revascularization.

Authors:  David Yu Greenblatt; Victoria Rajamanickam; Matthew W Mell
Journal:  J Vasc Surg       Date:  2011-03-31       Impact factor: 4.268

6.  Surgical-site infection risk in oncologic digestive surgery.

Authors:  Paulo de Tarso Oliveira e Castro; André Lopes Carvalho; Stela Verzinhasse Peres; Milene Mitsuyuki Foschini; Afonso Dinis Costa Passos
Journal:  Braz J Infect Dis       Date:  2011 Mar-Apr       Impact factor: 1.949

7.  Risk factors and outcomes of surgical site infection in children.

Authors:  Brian T Bucher; Rebecca M Guth; Alexis M Elward; Nicholas A Hamilton; Patrick A Dillon; Brad W Warner; Martin S Keller
Journal:  J Am Coll Surg       Date:  2011-03-12       Impact factor: 6.113

8.  Operative duration as an independent risk factor for postoperative complications in single-level lumbar fusion: an analysis of 4588 surgical cases.

Authors:  Bobby D Kim; Wellington K Hsu; Gildasio S De Oliveira; Sujata Saha; John Y S Kim
Journal:  Spine (Phila Pa 1976)       Date:  2014-03-15       Impact factor: 3.468

9.  Surgical site infection in children: prospective analysis of the burden and risk factors in a sub-Saharan African setting.

Authors:  Emmanuel A Ameh; Philip M Mshelbwala; Abdulrasheed A Nasir; Christopher S Lukong; Basheer A Jabo; Mark A Anumah; Paul T Nmadu
Journal:  Surg Infect (Larchmt)       Date:  2009-04       Impact factor: 2.150

Review 10.  Surgical site infections: epidemiology, microbiology and prevention.

Authors:  C D Owens; K Stoessel
Journal:  J Hosp Infect       Date:  2008-11       Impact factor: 3.926

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Journal:  Eur Spine J       Date:  2019-05-13       Impact factor: 3.134

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Authors:  Stephen Tabiri; Edwin Yenli; Martin Kyere; Theophilus T K Anyomih
Journal:  World J Surg       Date:  2018-04       Impact factor: 3.352

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Journal:  Langenbecks Arch Surg       Date:  2022-10-10       Impact factor: 2.895

4.  Benchmarking for surgical site infections among gastrointestinal surgeries and related risk factors: multicenter study in Kuwait.

Authors:  Wafaa S Hamza; Mona F Salama; Samar S Morsi; Naglaa M Abdo; Mariam A Al-Fadhli
Journal:  Infect Drug Resist       Date:  2018-09-03       Impact factor: 4.003

5.  Pattern of antibiotics use, incidence and predictors of surgical site infections in a Tertiary Care Teaching Hospital.

Authors:  Ezaedin Halawi; Tamrat Assefa; Sadikalmahdi Hussen
Journal:  BMC Res Notes       Date:  2018-07-31

6.  Risk factors for surgical site infection after craniotomy: a prospective cohort study.

Authors:  Emilio Jiménez-Martínez; Guillermo Cuervo; Ana Hornero; Pilar Ciercoles; Andres Gabarrós; Carmen Cabellos; Ivan Pelegrin; Dolores García-Somoza; Jordi Adamuz; Jordi Carratalà; Miquel Pujol
Journal:  Antimicrob Resist Infect Control       Date:  2019-05-02       Impact factor: 4.887

7.  Interleukin-6 from Adipose-Derived Stem Cells Promotes Tissue Repair by the Increase of Cell Proliferation and Hair Follicles in Ischemia/Reperfusion-Treated Skin Flaps.

Authors:  Chi-Ming Pu; Ya-Chun Chen; Yu-Chen Chen; Tzu-Lin Lee; Yu-Sen Peng; Shun-Hua Chen; Yu-Hsiu Yen; Chung-Liang Chien; Jung-Hsien Hsieh; Yuh-Lien Chen
Journal:  Mediators Inflamm       Date:  2019-11-13       Impact factor: 4.711

8.  Methicillin-resistant Staphylococcus aureus screening is important for surgeons.

Authors:  Il-Kwang Hyun; Pyoung Jae Park; Dawon Park; Sae Byeol Choi; Hyung Joon Han; Tae-Jin Song; Cheol-Woong Jung; Wan-Bae Kim
Journal:  Ann Hepatobiliary Pancreat Surg       Date:  2019-08-30

9.  An audit of surgical site infection following open prostatectomy in a Nigerian Teaching Hospital.

Authors:  Abdulkadir A Salako; Tajudeen A Badmus; Chiazor U Onyia; Rotimi A David; Ifedayo E Adejare; Adekunle O Lawal; Chigozie I Onyeze; Chinedu U Ndegbu
Journal:  Afr Health Sci       Date:  2019-06       Impact factor: 0.927

10.  Risk factors for surgical site infections using a data-driven approach.

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Journal:  PLoS One       Date:  2020-10-28       Impact factor: 3.240

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