A systematic review of surgical site infections following day surgery: a frequentist and a Bayesian meta-analysis of prevalence

J Hosp Infect. 2019 Feb;101(2):196-209. doi: 10.1016/j.jhin.2018.07.035. Epub 2018 Jul 30.

Abstract

Background: Since 1990, several studies have focused on safety and patient satisfaction in connection with day surgery. However, to date, no meta-analysis has investigated the overall prevalence of surgical site infections (SSI).

Aim: To estimate the overall prevalence of SSI following day surgery, regardless of the type of surgery.

Method: A systematic review and a meta-analysis of the prevalence of SSI following day surgery, regardless of the type of surgery, was conducted, seeking all studies before June 2016. A pooled random effects model using the DerSimonian and Laird approach was used to estimate overall prevalence. A double arcsine transformation was used to stabilize the variance of proportions. After performing a sensitivity analysis to validate the robustness of the method, univariate and multi-variate meta-regressions were used to test the effect of date of publication, country of study, study population, type of specialty, contamination class, time of postoperative patient visit after day surgery, and duration of hospital care.

Findings: Ninety articles, both observational and randomized, were analysed. The estimated overall prevalence of SSI among patients who underwent day surgery was 1.36% (95% confidence interval 1.1-1.6), with a Bayesian probability between 1 and 2% of 96.5%. The date of publication was associated with the prevalence of SSI (coefficient -0.001, P = 0.04), and the specialty (digestive vs non-digestive surgery) tended to be associated with the prevalence of SSI (coefficient 0.03, P = 0.064).

Conclusion: The meta-analysis showed a low prevalence of SSI following day surgery, regardless of the surgical procedure.

Keywords: Bayesian; Day surgery; Meta-analysis; Prevalence; Surgical site infections.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Ambulatory Surgical Procedures / adverse effects*
  • Bayes Theorem
  • Humans
  • Prevalence
  • Surgical Wound Infection / epidemiology*