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Meta-Analysis
. 2016 Jan;37(1):88-99.
doi: 10.1017/ice.2015.249. Epub 2015 Oct 27.

Diabetes and Risk of Surgical Site Infection: A Systematic Review and Meta-analysis

Emily T Martin  1 , Keith S Kaye  2 , Caitlin Knott  3 , Huong Nguyen  3 , Maressa Santarossa  3 , Richard Evans  1 , Elizabeth Bertran  3 , Linda Jaber  3
Affiliations
Meta-Analysis

Diabetes and Risk of Surgical Site Infection: A Systematic Review and Meta-analysis

Emily T Martin et al. Infect Control Hosp Epidemiol. 2016 Jan.

Abstract

OBJECTIVE To determine the independent association between diabetes and surgical site infection (SSI) across multiple surgical procedures. DESIGN Systematic review and meta-analysis. METHODS Studies indexed in PubMed published between December 1985 and through July 2015 were identified through the search terms "risk factors" or "glucose" and "surgical site infection." A total of 3,631 abstracts were identified through the initial search terms. Full texts were reviewed for 522 articles. Of these, 94 articles met the criteria for inclusion. Standardized data collection forms were used to extract study-specific estimates for diabetes, blood glucose levels, and body mass index (BMI). A random-effects meta-analysis was used to generate pooled estimates, and meta-regression was used to evaluate specific hypothesized sources of heterogeneity. RESULTS The primary outcome was SSI, as defined by the Centers for Disease Control and Prevention surveillance criteria. The overall effect size for the association between diabetes and SSI was odds ratio (OR)=1.53 (95% predictive interval [PI], 1.11-2.12; I2, 57.2%). SSI class, study design, or patient BMI did not significantly impact study results in a meta-regression model. The association was higher for cardiac surgery 2.03 (95% PI, 1.13-4.05) compared with surgeries of other types (P=.001). CONCLUSIONS These results support the consideration of diabetes as an independent risk factor for SSIs for multiple surgical procedure types. Continued efforts are needed to improve surgical outcomes for diabetic patients. Infect. Control Hosp. Epidemiol. 2015;37(1):88-99.

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Conflict of interest statement

Potential Conflicts of Interest. All authors report no conflicts of interest relevant to this article.

Figures

Figure 1
Figure 1
Flow diagram of search and selection processes
Figure 2
Figure 2
Meta-analysis of diabetes and surgical site infection, by surgery type
Figure 3
Figure 3
Meta-analysis of pre-operative hyperglycemia and surgical site infection
Figure 4
Figure 4
Meta-analysis of post-operative hyperglycemia and surgical site infection
See this image and copyright information in PMC

References

    1. Cheng YJ, Imperatore G, Geiss LS, Wang J, Saydah SH, Cowie CC, et al. Secular changes in the age-specific prevalence of diabetes among U.S. adults: 1988–2010. Diabetes Care. 2013;36:2690–6. - PMC - PubMed
    1. Zimlichman E, Henderson D, Tamir O, Franz C, Song P, Yamin CK, et al. Health care-associated infections: a meta-analysis of costs and financial impact on the US health care system. JAMA Intern Med. 2013;173:2039–46. - PubMed
    1. Joynt KE, Jha AK. Characteristics of hospitals receiving penalties under the Hospital Readmissions Reduction Program. JAMA. 2013;309:342–3. - PubMed
    1. Sievert DM, Ricks P, Edwards JR, Schneider A, Patel J, Srinivasan A, et al. Antimicrobial-resistant pathogens associated with healthcare-associated infections: summary of data reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2009–2010. Infect Control Hosp Epidemiol. 2013;34:1–14. - PubMed
    1. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000;283:2008–12. - PubMed

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