title: Prospective nationwide surveillance of surgical site infections after gastric surgery and risk factor analysis in the Korean Nosocomial Infections Surveillance System (KONIS).
abstract: OBJECTIVE
  To evaluate the risk factors for surgical site infection (SSI) after gastric surgery in patients in Korea.
  
  
  METHODS
  A nationwide prospective multicenter study.
  
  
  METHODS
  Twenty university-affiliated hospitals in Korea.
  
  
  METHODS
  The Korean Nosocomial Infections Surveillance System (KONIS), a Web-based system, was developed. Patients in 20 Korean hospitals from 2007 to 2009 were prospectively monitored for SSI for up to 30 days after gastric surgery. Demographic data, hospital characteristics, and potential perioperative risk factors were collected and analyzed, using multivariate logistic regression models.
  
  
  RESULTS
  Of the 4,238 case patients monitored, 64.9% (2,752) were male, and mean age (± SD) was 58.8 (± 12.3) years. The SSI rates were 2.92, 6.45, and 10.87 per 100 operations for the National Nosocomial Infections Surveillance system risk index categories of 0, 1, and 2 or 3, respectively. The majority (69.4%) of the SSIs observed were organ or space SSIs. The most frequently isolated microorganisms were Staphylococcus aureus and Klebsiella pneumoniae. Male sex (odds ratio [OR], 1.67 [95% confidence interval (CI), 1.09-2.58]), increased operation time (1.20 [1.07-1.34] per 1-hour increase), reoperation (7.27 [3.68-14.38]), combined multiple procedures (1.79 [1.13-2.83]), prophylactic administration of the first antibiotic dose after skin incision (3.00 [1.09-8.23]), and prolonged duration (≥7 days) of surgical antibiotic prophylaxis (SAP; 2.70 [1.26-5.64]) were independently associated with increased risk of SSI.
  
  
  CONCLUSIONS
  Male sex, inappropriate SAP, and operation-related variables are independent risk factors for SSI after gastric surgery.
authors.affiliation: Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
authors.forename: Eu Suk
authors.initials: ES
authors.lastname: Kim
authors.forename: Hong Bin
authors.initials: HB
authors.lastname: Kim
authors.forename: Kyoung-Ho
authors.initials: KH
authors.lastname: Song
authors.forename: Young Keun
authors.initials: YK
authors.lastname: Kim
authors.forename: Hyung-Ho
authors.initials: HH
authors.lastname: Kim
authors.forename: Hye Young
authors.initials: HY
authors.lastname: Jin
authors.forename: Sun Young
authors.initials: SY
authors.lastname: Jeong
authors.forename: Joohon
authors.initials: J
authors.lastname: Sung
authors.forename: Yong Kyun
authors.initials: YK
authors.lastname: Cho
authors.forename: Yeong-Seon
authors.initials: YS
authors.lastname: Lee
authors.forename: Hee-Bok
authors.initials: HB
authors.lastname: Oh
authors.forename: Eui-Chong
authors.initials: EC
authors.lastname: Kim
authors.forename: June Myung
authors.initials: JM
authors.lastname: Kim
authors.forename: Tae Yeol
authors.initials: TY
authors.lastname: Choi
authors.forename: Hee Jung
authors.initials: HJ
authors.lastname: Choi
authors.forename: Hyo Youl
authors.initials: HY
authors.lastname: Kim
mesh_terms: D000328:Adult; D000368:Aged; D019072:Antibiotic Prophylaxis / Q000009:adverse effects; D003428:Cross Infection / Q000453:epidemiology / Q000209:etiology* / Q000517:prevention & control; D005260:Female; D006801:Humans; D017053:Infection Control; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011159:Population Surveillance; D011446:Prospective Studies; D056910:Republic of Korea / Q000453:epidemiology; D012307:Risk Factors; D012737:Sex Factors; D013270:Stomach / Q000601:surgery*; D013530:Surgical Wound Infection / Q000453:epidemiology / Q000209:etiology* / Q000517:prevention & control