Home⇛Health Sciences Journal⇛vol. 15 no. 1 (2026)

Accuracy of Selective Postoperative Surgical Site Infection Surveillance Among High-Risk Patients Compared With Traditional Surveillance in a Tertiary University Hospital

Domingo Bongala

Discipline: medicine by specialism

 

Abstract:

Introduction Surgical site infection (SSI) surveillance is resource-intensive, particularly in low-resource settings. This study evaluated whether selective surveillance of high-risk patients can accurately identify postoperative SSI compared with traditional surveillance of all surgical patients. Methods A cross-sectional study was conducted among 587 patients who underwent selected general surgical procedures from January 2022 to June 2023 in a tertiary university hospital. Patients were classified as high-risk or low-risk for SSI using eight perioperative variables. Logistic regression analysis identified factors independently associated with SSI. The accuracy and agreement of selective surveillance versus traditional surveillance were assessed using sensitivity, specificity, predictive values, and Cohen’s kappa. Results The overall SSI rate was 12% (71/587). Independent predictors of SSI included resident service cases (OR 2.57, 95% CI 1.37–4.83), ASA score 3–5 (OR 6.28, 95% CI 3.30–11.93), clean-contaminated to dirty wounds (OR 21.73, 95% CI 6.26–75.48), operative duration beyond the 75th percentile (OR 2.33, 95% CI 1.24–4.38), and failure to maintain perioperative normothermia (OR 39.49, 95% CI 3.35–465.06). Selective surveillance demonstrated 100% sensitivity, specificity, positive predictive value, and negative predictive value, with perfect agreement with traditional surveillance (Cohen’s kappa = 1.00). Conclusion Selective surveillance focused on high-risk patients demonstrated excellent agreement with traditional surveillance and may serve as a cost-effective alternative for SSI monitoring in resource-limited settings.



References:

  1. American Society of Anesthesiologists. (2020, December 13). Statement on ASA physical status classification system. https://www.asahq.org/standards-and-practice-parameters/statement-on-asa-physical-status-classification-system
  2. Anderson DJ, Podgorny K, Berríos-Torres SI, Bratzler DW, Dellinger EP, Greene L, Nyquist AC, Saiman L, Yokoe DS, Maragakis LL & Kaye KS. (2014). Strategies to prevent surgical site infections in acute care hospitals: 2014 update. Infect Contr Hosp Epidemiol 35(Suppl. 2), S66–S88. https://doi.org/10.1017/S0899823X00193869
  3. Ban KA, Minei JP, Laronga C, Harbrecht BG, Jensen EH, Fry DE, Itani KMF, Dellinger EP, Ko CY & Duane TM. (2017). American College of Surgeons and Surgical Infection Society: Surgical site infection guidelines, 2016 update. J Am Coll Surg 224(1): 59–74. https://doi.org/10.1016/j.jamcollsurg.2016.10.029
  4. Branch-Elliman W, Strymish J, Itani KM & Gupta K. (2014). Using clinical variables to guide surgical site infection detection: A novel surveillance strategy. Am J Infect Control 42(12): 1291–5.
  5. Centers for Disease Control and Prevention. (2015). 2015 national and state healthcare-associated infections progress report. https://www.cdc.gov/hai/data/portal/progress-report.html
  6. Cheng H, Chen BPH, Soleas IM, Ferko NC, Cameron CG & Hinoul P. (2017). Prolonged operative duration increases risk of surgical site infections: A systematic review. Surg Infect 18(6): 722–35.
  7. Curcio D, Cane A, Fernández F & Correa J. (2019). Surgical site infection in elective clean and clean- contaminated surgeries in developing countries. Int J Infect Dis 80: 34–45.
  8. De Brito Poveda V, Oliveira RA & Galvão CM. (2020). Perioperative body temperature maintenance and occurrence of surgical site infection: A systematic review with meta-analysis. Am J Infect Control 48(10): 1248–54.
  9. Fukuda H. (2016). Patient-related risk factors for surgical site infection following eight types of gastrointestinal surgery. J Hosp Infect 93(4): 347–54.
  10. Gillespie BM, Harbeck E, Rattray M, Liang R, Walker R, Latimer S, Thalib L, Andersson AE, Griffin B, Ware R & Chaboyer W. (2021). Worldwide incidence of surgical site infections in general surgical patients: A systematic review and meta-analysis of 488,594 patients. Int J Surg 95: 106136. https://doi.org/10.1016/j.ijsu.2021.106136
  11. Hackett NJ, De Oliveira GS, Jain UK & Kim JY. (2015). ASA class is a reliable independent predictor of medical complications and mortality following surgery. Int J Surg 18: 184–90.
  12. Horgan S, Hegarty J, Drennan J, Keane D & Saab MM. (2023). The effect of interventions on the incidence of surgical site infections in acute care settings: A systematic review. J Tissue Viability 32(4): 655–67. https://doi.org/10.1016/j.jtv.2023.08.004
  13. Kasatpibal N, Nørgaard M & Jamulitrat S. (2009). Improving surveillance system and surgical site infection rates through a network: A pilot study from Thailand. Clin Epidemiol 1: 67–74. https://doi.org/10.2147/CLEP.S4890
  14. Kaye KS, Schmit K, Pieper C, Sloane R, Caughlan KF, Sexton DJ & Schmader KE. (2005). The effect of increasing age on the risk of surgical site infection. J Infect Dis 191(7): 1056–62.
  15. Kurz A, Sessler DI & Lenhardt R. (1996). Perioperative normothermia to reduce the incidence of surgical-wound infection and shorten hospitalization. New Engl J Med 334(19): 1209–15.
  16. Latham R, Lancaster AD, Covington JF, Pirolo JS & Thomas CS. (2001). The association of diabetes and glucose control with surgical-site infections among cardiothoracic surgery patients. Infect Control Hosp Epidemiol 22(10): 607–12.
  17. Melling AC, Ali B, Scott EM & Leaper DJ. (2001). Effects of preoperative warming on the incidence of wound infection after clean surgery: A randomised controlled trial. The Lancet 358(9285): 876–80. https://doi.org/10.1016/S0140-6736(01)06071-8
  18. Mujagic E, Hoffmann H, Soysal SD, Delko T, Mechera R, Coslovsky M, Grass F, Hubner M & Weber WP. (2020). Teaching in the operating room: A risk for surgical site infections? Am J Surg 220(2): 322–7. https://doi.org/10.1016/j.amjsurg.2019.12.034
  19. National Nosocomial Infections Surveillance System. (2003). National Nosocomial Infections Surveillance (NNIS) system report, data summary from January 1992 through June 2003. Am J Infect Contr 31(8): 481–98.
  20. Pedroso-Fernandez Y, Aguirre-Jaime A, Ramos MJ, Hernández M, Cuervo M, Bravo A & Carrillo A. (2016). Prediction of surgical site infection after colorectal surgery. Am J Infect Control 44(4): 450–4.
  21. Rosenthal VD, Yin R, Nercelles P, Rivera-Molina SE, Jyoti S, Dongol R, Al-Abdely HM, AlKhawaja SAA, Al-Mousa HH, Al-Ruzzieh MA, Ben-Jaballah N, Belskiy V, Bukhari SZ, Chandy SJ, Chhabra S, Chittora M, Das A, Dendane T, El-Kholy A, Jin Z. (2024). International Nosocomial Infection Control Consortium (INICC) report of healthcare-associated infections, data summary of 2020–2023, compared with 2013–2019. Am J Infect Control 52(9): 1002–11.
  22. Russo PL, Saguil E, Chakravarthy M, Lee KY, Ling ML, Morikane K, Spencer M, Danker W, Yu NYC & Edmiston CE Jr. (2021). Improving surgical site infection prevention in Asia-Pacific through appropriate surveillance programs: Challenges and recommendation. Infect Dis Health 26(3): 198–207.
  23. Saunders L, Perennec-Olivier M, Jarno PL’Hériteau F, Venier AG, Simon L, Giard M, Thiolet JM, Viel JF, & RAISIN Group. (2014). Improving prediction of surgical site infection risk with multilevel modeling. PLoS One 9(5): e95295. https://doi.org/10.1371/journal.pone.0095295.
  24. Tomsic I, Heinze NR, Chaberny IF, Krauth C, Schock B, & von Lengerke T. (2020). Implementation interventions in preventing surgical site infections in abdominal surgery: A systematic review. BMC Health Serv Res 20, Article 236. https://doi.org/10.1186/s12913-020-05081-y

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