Publication: Prediction of surgical site infection and other adverse postoperative outcomes
Files
Date
2009
Article Type
Original Article
Journal Title
Journal ISSN
ISSN (Print) : 1993-2979 | ISSN (Online) : 1993-2987
Volume Title
Pages
Pages: 3 - 6
Publisher
Institute of Medicine
Abstract
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.
Keywords: Prediction, SENIC Index, surgical site infection
Description
B.R. Luitel
Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal
S.P Kandel
Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal
B. Shrestha
Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal
R. Sapkota
Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal
R.S Bhandari
Department of surgery, Tribhuvan University Teaching Hospital, Kathmandu, Nepal
Keywords
Prediction, SENIC Index, surgical site infection
Identifier
https://doi.org/10.59779/jiomnepal.382