Revisiting the effectiveness of interventions to decrease surgical site infections in colorectal surgery: A Bayesian perspective

Objective To evaluate the evidence for interventions to decrease surgical site infections (SSIs) in colorectal operations using Bayesian meta-analysis. Background Interventions other than appropriate administration of prophylactic antibiotics to prevent SSIs have not been adopted widely, in part bec...

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Veröffentlicht in:Surgery 2012-08, Vol.152 (2), p.202-211
Hauptverfasser: Phatak, Uma R., MD, Pedroza, Claudia, PhD, Millas, Stefanos G., MD, Chang, George J., MD, MS, Lally, Kevin P., MD, MS, Kao, Lillian S., MD, MS
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Sprache:eng
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Zusammenfassung:Objective To evaluate the evidence for interventions to decrease surgical site infections (SSIs) in colorectal operations using Bayesian meta-analysis. Background Interventions other than appropriate administration of prophylactic antibiotics to prevent SSIs have not been adopted widely, in part because of lack of recommendations for these interventions based on traditional meta-analyses. Bayesian methods can provide probabilities of specific thresholds of benefit, which may be more useful in guiding clinical decision making. We hypothesized that Bayesian meta-analytic methods would complement the interpretation of traditional analyses regarding the effectiveness of interventions to decrease SSIs. Methods We conducted a systematic search of the Cochrane database for reviews of interventions to decrease SSIs after colorectal surgery other than prophylactic antibiotics. Traditional and Bayesian meta-analyses were performed using RevMan (Nordic Cochrane Center, Copenhagen, Denmark) and WinBUGS (MRC Biostatistics Unit, Cambridge, UK). Bayesian posterior probabilities of any benefit, defined as a relative risk of 85% probability of benefit. Also, nonuse of 2 interventions (mechanical bowel preparation and adhesive drapes) had a high probability of decreasing SSIs compared with their use. Conclusion Bayesian probabilities and traditional point estimates of treatment effect yield similar information in terms of potential effectiveness. Bayesian meta-analysis, however, provides complementary information on the probability of a large magnitude of effect. The clinical impact of using Bayesian methods to inform decisions about which interventions to institute first or which interventions to combine requires further study.
ISSN:0039-6060
1532-7361
DOI:10.1016/j.surg.2012.05.005