Prediction of surgical site infection and other adverse postoperative outcomes

Authors

  • B.R. Luitel Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal Author
  • S.P Kandel Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal Author
  • B. Shrestha Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal Author
  • R. Sapkota Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal Author
  • R.S Bhandari Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal Author

DOI:

https://doi.org/10.59779/jiomnepal.382

Keywords:

Prediction, SENIC Index, surgical site infection

Abstract

Background: To predict surgical site infection, hospital acquired pneumonia, wound dehiscence, and mortality based on SENIC index in Nepalese perspective in surgical patients. Methods: A Retrospective study was conducted at Department of Surgery, Tribhuvan University Teaching Hospital (TUTH), Kathmandu, Nepal from October 2007 to September 2008. Surgicalinfection risk factors assessed by the traditional wound-classification system (clean, cleancontaminated, contaminated, and dirty-infected wound) and by the SENIC risk index (length of intervention more than 2 hours, more than three discharge diagnoses, abdominal surgery, and contaminated or dirty infected wound) were compared by Receiver Operating Characteristic (ROC) curve. Results: The SENIC index showed a good ability to predict SSI, Hospital Acquired pneumonia, wound dehiscence and in hospital mortality. If the index score is higher, the outcome is poorer. By using SENIC index score the area under ROC curve for SSI, pneumonia, wound dehiscence and in hospital mortality was 82.2±4.8, 90.5±2.4, 85.1 ±4.7 and 96.9±1.2 % respectively with sensitivity above 95% for all the parameters. Conclusion: This study shows that the SENIC risk index results are reproducible, and the index can be used to predict rates of SSI and other adverse postoperative complications in developing countries as well.

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Published

2009-08-31

How to Cite

Luitel, B., Kandel, S., Shrestha, B., Sapkota, R., & Bhandari, R. (2009). Prediction of surgical site infection and other adverse postoperative outcomes. Journal of Institute of Medicine Nepal, 31(2), 3-6. https://doi.org/10.59779/jiomnepal.382

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