Incidence of surgical site infections and prediction of risk factors in a hospital center in Morocco

  • Rachid Flouchi Laboratory of Microbial Biotechnology and Bioactive Molecules, Science and Technologies Faculty, Sidi Mohamed Ben Abdellah University, Fez, Morocco https://orcid.org/0000-0003-0762-5305
  • Mohamed El Far Laboratory of Applied Physics, Computer Science and Statistics Sciences Faculty Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco https://orcid.org/0000-0002-7539-6332
  • Abdelaziz Hibatallah Surgical Department, Provincial Hospital Center Ibn Baja Taza, Morocco
  • Abderrahim Elmniai Human Pathology, Biomedicine and Environment Laboratory, Faculty of Medicine and Pharmacy, Sidi Mohamed Ben Abdellah University, Fez, Morocco
  • Ibtissam Rhbibou High Institute of Nursing Professions and Health Techniques annex Taza, Fez, Morocco
  • Ibrahim Touzani Laboratory of Microbial Biotechnology and Bioactive Molecules, Science and Technologies Faculty, Sidi Mohamed Ben Abdellah University, Fez, Morocco https://orcid.org/0000-0003-4202-2681
  • Naoufal El Hachlafi Laboratory of Microbial Biotechnology and Bioactive Molecules, Science and Technologies Faculty, Sidi Mohamed Ben Abdellah University, Fez, Morocco https://orcid.org/0000-0003-0768-5914
  • Kawtar Fikri-Benbrahim Laboratory of Microbial Biotechnology and Bioactive Molecules, Science and Technologies Faculty, Sidi Mohamed Ben Abdellah University, Fez, Morocco https://orcid.org/0000-0002-2923-9299
Keywords: incidence, surgery, surgical site infection, hospital, prediction

Abstract

Introduction: Surgical site infections (SSIs) remain the major cause of morbidity and mortality in the postoperative period and are important surgical and hospital quality indicators. In this context, our study aims to identify SSIs associated risk factors and to develop a predictive model.

Methodology: 2521 patients who underwent surgery, between June 2018 and May 2019, in four surgery departments, at the Taza Provincial Hospital (Morocco) were diagnosed for SSI according to the standards of the Center for Disease Control and Prevention. The SSIs’ risk factors were assessed by univariate statistical analysis and logistic regression using the Scikit Learn function of Python.

Results: The average age of the studied population was 35 ± 1 years. The overall SSI incidence was 6.3% (17.95%, 6.86%, 6.67% and 3.16% respectively in child, female, male and gynaecological-obstetrical surgeries. The univariate statistical analysis has shown a highly significant (p < 0.001) and a very significant (p < 0.01) relationship between SSIs and almost all risk factors; and the logistic regression model has revealed a strong association between SSI and people who have had previous surgery, urinary catheter, antibiotic use duration, co-morbidity, American Society of Anesthesiologists (ASA) score, duration of intervention, emergency preoperative and postoperative durations, service, specialty and age range. The prediction score exceeds 96% which justifies our model’s quality.

Conclusions: SSIs are generally frequent among postoperative patients. Therefore, pre-operative preparation, post-operative surveillance and the environment quality of the wards are necessary to reduce SSI rates in the hospital.

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Published
2022-07-28
How to Cite
1.
Flouchi R, El FarM, Hibatallah A, Elmniai A, Rhbibou I, Touzani I, El HachlafiN, Fikri-BenbrahimK (2022) Incidence of surgical site infections and prediction of risk factors in a hospital center in Morocco. J Infect Dev Ctries 16:1191-1198. doi: 10.3855/jidc.15289
Section
Original Articles