Antimicrobial surfaces to prevent healthcare-associated infections: a systematic review. Issue 1 (January 2016) - Muller, M.P.; MacDougall, C.; Lim, M.; ,; ,
Summary: Contamination of the healthcare environment with pathogenic organisms contributes to the burden of healthcare-associated infection (HCAI). Antimicrobial surfaces are designed to reduce microbial contamination of healthcare surfaces. We aimed to determine whether antimicrobial surfaces prevent HCAI, transmission of antibiotic-resistant organisms (AROs), or microbial contamination, we conducted a systematic review of the use of antimicrobial surfaces in patient rooms. Outcomes included HCAI, ARO, and quantitative microbial contamination. Relevant databases were searched. Abstract review, full text review, and data abstraction were performed in duplicate. Risk of bias was assessed using the Cochrane Effective Practice and Organization Care (EPOC) Group risk of bias assessment tool and the strength of evidence determined using Grading of Recommendations Assessment, Development and Evaluation (GRADE). Eleven studies assessed the effect of copper ( N = 7), silver ( N = 1), metal-alloy ( N = 1), or organosilane-treated surfaces ( N = 2) on microbial contamination. Copper surfaces demonstrated a median (range) reduction of microbial contamination of <1 log10 (<1 to 2 log10 ). Two studies addressed HCAI/ARO incidence. An RCT of copper surfaces in an ICU demonstrated 58% reduction in HCAI ( P = 0.013) and 64% reduction in ARO transmission ( P = 0.063) but was considered low-quality evidence due to improper randomization and incomplete blinding. An uncontrolled before–after study evaluating copper-impregnated textiles in a long-term care ward demonstrated 24% reduction in HCAI but was considered very-low-quality evidence based on the study design. Copper surfaces used in clinical settings result in modest reductions in microbial contamination. One study of copper surfaces and one of copper textiles demonstrated reduction in HCAI, but both were at high risk of bias.