DOI QR코드

DOI QR Code

The Relationship between Preoperative Wound Classification and Postoperative Infection: A Multi-Institutional Analysis of 15,289 Patients

  • Mioton, Lauren M. (Department of Plastic Surgery, Vanderbilt School of Medicine) ;
  • Jordan, Sumanas W. (Division of Plastic and Reconstructive Surgery, Northwestern University, Feinberg School of Medicine) ;
  • Hanwright, Philip J. (Division of Plastic and Reconstructive Surgery, Northwestern University, Feinberg School of Medicine) ;
  • Bilimoria, Karl Y. (Department of Surgery, Northwestern University, Feinberg School of Medicine) ;
  • Kim, John Y.S. (Division of Plastic and Reconstructive Surgery, Northwestern University, Feinberg School of Medicine)
  • 투고 : 2013.01.08
  • 심사 : 2013.05.07
  • 발행 : 2013.09.15

초록

Background Despite advances in surgical techniques, sterile protocols, and perioperative antibiotic regimens, surgical site infections (SSIs) remain a significant problem. We investigated the relationship between wound classification (i.e., clean, clean/contaminated, contaminated, dirty) and SSI rates in plastic surgery. Methods We performed a retrospective review of a multi-institutional, surgical outcomes database for all patients undergoing plastic surgery procedures from 2006-2010. Patient demographics, wound classification, and 30-day outcomes were recorded and analyzed by multivariate logistic regression. Results A total of 15,289 plastic surgery cases were analyzed. The overall SSI rate was 3.00%, with superficial SSIs occurring at comparable rates across wound classes. There were similar rates of deep SSIs in the clean and clean/contaminated groups (0.64%), while rates reached over 2% in contaminated and dirty cases. Organ/space SSIs occurred in less than 1% of each wound classification. Contaminated and dirty cases were at an increased risk for deep SSIs (odds ratios, 2.81 and 2.74, respectively); however, wound classification did not appear to be a significant predictor of superficial or organ/space SSIs. Clean/contaminated, contaminated, and dirty cases were at increased risk for a postoperative complication, and contaminated and dirty cases also had higher odds of reoperation and 30-day mortality. Conclusions Analyzing a multi-center database, we found that wound classification was a significant predictor of overall complications, reoperation, and mortality, but not an adequate predictor of surgical site infections. When comparing infections for a given wound classification, plastic surgery had lower overall rates than the surgical population at large.

키워드

참고문헌

  1. Klevens RM, Edwards JR, Richards CL Jr, et al. Estimating health care-associated infections and deaths in U.S. hospitals, 2002. Public Health Rep 2007;122:160-6. https://doi.org/10.1177/003335490712200205
  2. Thompson KM, Oldenburg WA, Deschamps C, et al. Chasing zero: the drive to eliminate surgical site infections. Ann Surg 2011;254:430-6. https://doi.org/10.1097/SLA.0b013e31822cc0ad
  3. Boyce JM, Potter-Bynoe G, Dziobek L. Hospital reimbursement patterns among patients with surgical wound infections following open heart surgery. Infect Control Hosp Epidemiol 1990;11:89-93. https://doi.org/10.2307/30144267
  4. Olsen MA, Chu-Ongsakul S, Brandt KE, et al. Hospital-associated costs due to surgical site infection after breast surgery. Arch Surg 2008;143:53-60. https://doi.org/10.1001/archsurg.2007.11
  5. Poulsen KB, Bremmelgaard A, Sorensen AI, et al. Estimated costs of postoperative wound infections. A case-control study of marginal hospital and social security costs. Epidemiol Infect 1994;113:283-95. https://doi.org/10.1017/S0950268800051712
  6. Kirkland KB, Briggs JP, Trivette SL, et al. The impact of surgical-site infections in the 1990s: attributable mortality, excess length of hospitalization, and extra costs. Infect Control Hosp Epidemiol 1999;20:725-30. https://doi.org/10.1086/501572
  7. Hart D, Postlethwait RW, Brown IW Jr, et al. Postoperative wound infections: a further report on ultraviolet irradiation with comments on the recent (1964) national research council cooperative study report. Ann Surg 1968;167:728-43. https://doi.org/10.1097/00000658-196805000-00011
  8. Garner JS. CDC guideline for prevention of surgical wound infections, 1985. Supersedes guideline for prevention of surgical wound infections published in 1982. (Originally published in November 1985). Revised. Infect Control 1986;7:193-200. https://doi.org/10.1017/S0195941700064080
  9. Culver DH, Horan TC, Gaynes RP, et al. Surgical wound infection rates by wound class, operative procedure, and patient risk index. National Nosocomial Infections Surveillance System. Am J Med 1991;91:152S-7S. https://doi.org/10.1016/0002-9343(91)90361-Z
  10. Olson MM, Lee JT Jr. Continuous, 10-year wound infection surveillance. Results, advantages, and unanswered questions. Arch Surg 1990;125:794-803. https://doi.org/10.1001/archsurg.1990.01410180120020
  11. American College of Surgeons. ACS data collection, analysis, and reporting [Internet]. Chicago, IL: American College of Surgeons; c2013 [cited 2012 Aug 31]. Available from: http://site.acsnsqip.org/programspecifics/data-collectionanalysis- and-reporting/.
  12. Horan TC, Gaynes RP, Martone WJ, et al. CDC definitions of nosocomial surgical site infections, 1992: a modification of CDC definitions of surgical wound infections. Infect Control Hosp Epidemiol 1992;13:606-8. https://doi.org/10.2307/30148464
  13. American College of Surgeons. ACS NSQIP: user guide for the 2009 participant use data file [Internet]. Chicago, IL: American College of Surgeons; c2010 [cited 2012 Oct 31]. Available from: http://site.acsnsqip.org/wp-content/uploads/2012/03/ACS_NSQIP_Participant_User_Data_File_User_Guide.pdf.
  14. Ortega G, Rhee DS, Papandria DJ, et al. An evaluation of surgical site infections by wound classification system using the ACS-NSQIP. J Surg Res 2012;174:33-8. https://doi.org/10.1016/j.jss.2011.05.056
  15. Andenaes K, Amland PF, Lingaas E, et al. A prospective, randomized surveillance study of postoperative wound infections after plastic surgery: a study of incidence and surveillance methods. Plast Reconstr Surg 1995;96:948-56. https://doi.org/10.1097/00006534-199509001-00028
  16. Gravante G, Caruso R, Araco A, et al. Infections after plastic procedures: incidences, etiologies, risk factors, and antibiotic prophylaxis. Aesthetic Plast Surg 2008;32:243-51. https://doi.org/10.1007/s00266-007-9068-8
  17. Drapeau CM, D'Aniello C, Brafa A, et al. Surgical site infections in plastic surgery: an Italian multicenter study. J Surg Res 2007;143:393-7. https://doi.org/10.1016/j.jss.2007.01.040
  18. Sylaidis P, Wood S, Murray DS. Postoperative infection following clean facial surgery. Ann Plast Surg 1997;39:342-6. https://doi.org/10.1097/00000637-199710000-00003
  19. Murphy RC, Robson MC, Heggers JP, et al. The effect of microbial contamination on musculocutaneous and random flaps. J Surg Res 1986;41:75-80. https://doi.org/10.1016/0022-4804(86)90011-9
  20. Devaney L, Rowell KS. Improving surgical wound classification: why it matters. AORN J 2004;80:208-9. https://doi.org/10.1016/S0001-2092(06)60559-0
  21. Eisenberg D. Surgical site infections: time to modify the wound classification system? J Surg Res 2012;175:54-5. https://doi.org/10.1016/j.jss.2011.07.025
  22. Nichols RL. Classification of the surgical wound: a time for reassessment and simplification. Infect Control Hosp Epidemiol 1993;14:253-4. https://doi.org/10.2307/30148361

피인용 문헌

  1. Treatment Algorithm of Complications after Filler Injection: Based on Wound Healing Process vol.29, pp.suppl3, 2014, https://doi.org/10.3346/jkms.2014.29.s3.s176
  2. Use of low-power laser to assist the healing of traumatic wounds in rats vol.30, pp.3, 2013, https://doi.org/10.1590/s0102-865020150030000007
  3. Analysis of Malpractice Claims Associated with Surgical Site Infection in the Field of Plastic Surgery vol.31, pp.12, 2013, https://doi.org/10.3346/jkms.2016.31.12.1963
  4. Patients at High-Risk for Surgical Site Infection vol.18, pp.4, 2013, https://doi.org/10.1089/sur.2017.058
  5. Risk factors for surgical site infection following nonshunt pediatric neurosurgery: a review of 9296 procedures from a national database and comparison with a single-center experience vol.19, pp.4, 2017, https://doi.org/10.3171/2016.11.peds16454
  6. Association of Postoperative Readmissions With Surgical Quality Using a Delphi Consensus Process to Identify Relevant Diagnosis Codes vol.153, pp.8, 2018, https://doi.org/10.1001/jamasurg.2018.0592
  7. Operating room staff and surgeon documentation curriculum improves wound classification accuracy vol.4, pp.8, 2013, https://doi.org/10.1016/j.heliyon.2018.e00728
  8. Determinants of superficial surgical site infections in abdominal surgeries at a Rural Teaching Hospital in Central India: A prospective study vol.8, pp.7, 2019, https://doi.org/10.4103/jfmpc.jfmpc_419_19
  9. Variations in Perioperative Antibiotic Prescriptions Among Academic Urologists After Ambulatory Endoscopic Urologic Surgery: Impact on Infection Rates and Validation of 2019 Best Practice Statement vol.146, pp.None, 2013, https://doi.org/10.1016/j.urology.2020.07.049
  10. A Comparison of Interobserver Reliability Between Orthopedic Surgeons Using the Centers for Disease Control Surgical Wound Class Definitions vol.29, pp.24, 2013, https://doi.org/10.5435/jaaos-d-20-01128
  11. Wound healing applications of creams and “smart” hydrogels vol.30, pp.9, 2013, https://doi.org/10.1111/exd.14396
  12. Predictors of Postoperative Complications After Paramedian Forehead Flaps vol.23, pp.6, 2013, https://doi.org/10.1089/fpsam.2020.0570
  13. Preoperative contaminated wound management using short-term negative pressure wound therapy with instillation vol.30, pp.12, 2013, https://doi.org/10.12968/jowc.2021.30.12.994