OBJECTIVES: To assess the clinical effectiveness of central venous catheters (CVCs) treated with anti-infective agents (AI-CVCs) in preventing catheter-related bloodstream infections (CRBSI). DATA SOURCES: MEDLINE (OVID), EMBASE, SCI//Web of Science, SCI/ISI Proceedings, and the Cochrane Library. STUDY SELECTION: A systematic review of the literature was conducted using internationally recognized methodology. All included articles were reports of randomized controlled trials comparing the clinical effectiveness of CVCs treated with AI-CVCs with either standard CVCs or another anti-infective treated catheter. Articles requiring in-house preparation of catheters or that only reported interim data were excluded. DATA EXTRACTION: Data extraction was carried out independently and crosschecked by two reviewers using a pretested data extraction form. DATA SYNTHESIS: Meta-analyses were conducted to assess the effectiveness of AI-CVCs in preventing CRBSI, compared with standard CVCs. Results are presented in forest plots with 95% confidence intervals. RESULTS: Thirty-eight randomized controlled trials met the inclusion criteria. Methodologic quality was generally poor. Meta-analyses of data from 27 trials assessing CRBSI showed a strong treatment effect in favor of AI-CVCs (odds ratio 0.49 (95% confidence interval 0.37-0.64) fixed effects, test for heterogeneity, chi-square = 28.78, df = 26, p = 0.321, I = 9.7). Results subgrouped by the different types of anti-infective treatments generally demonstrated treatment effects favoring the treated catheters. Sensitivity analyses investigating the effects of methodologic differences showed no differences to the overall conclusions of the primary analysis. CONCLUSION: AI-CVCs appear to be effective in reducing CRBSI compared with standard CVCs. However, it is important to establish whether this effect remains in settings where infection-prevention bundles of care are established as routine practice. This review does not address this question and further research is required.
OBJECTIVES: To assess the clinical effectiveness of central venous catheters (CVCs) treated with anti-infective agents (AI-CVCs) in preventing catheter-related bloodstream infections (CRBSI). DATA SOURCES: MEDLINE (OVID), EMBASE, SCI//Web of Science, SCI/ISI Proceedings, and the Cochrane Library. STUDY SELECTION: A systematic review of the literature was conducted using internationally recognized methodology. All included articles were reports of randomized controlled trials comparing the clinical effectiveness of CVCs treated with AI-CVCs with either standard CVCs or another anti-infective treated catheter. Articles requiring in-house preparation of catheters or that only reported interim data were excluded. DATA EXTRACTION: Data extraction was carried out independently and crosschecked by two reviewers using a pretested data extraction form. DATA SYNTHESIS: Meta-analyses were conducted to assess the effectiveness of AI-CVCs in preventing CRBSI, compared with standard CVCs. Results are presented in forest plots with 95% confidence intervals. RESULTS: Thirty-eight randomized controlled trials met the inclusion criteria. Methodologic quality was generally poor. Meta-analyses of data from 27 trials assessing CRBSI showed a strong treatment effect in favor of AI-CVCs (odds ratio 0.49 (95% confidence interval 0.37-0.64) fixed effects, test for heterogeneity, chi-square = 28.78, df = 26, p = 0.321, I = 9.7). Results subgrouped by the different types of anti-infective treatments generally demonstrated treatment effects favoring the treated catheters. Sensitivity analyses investigating the effects of methodologic differences showed no differences to the overall conclusions of the primary analysis. CONCLUSION: AI-CVCs appear to be effective in reducing CRBSI compared with standard CVCs. However, it is important to establish whether this effect remains in settings where infection-prevention bundles of care are established as routine practice. This review does not address this question and further research is required.
Authors: Nabil M Abraham; Lei Liu; Brandon L Jutras; Kristen Murfin; Ali Acar; Timur O Yarovinsky; Erica Sutton; Martin Heisig; Christine Jacobs-Wagner; Erol Fikrig Journal: Antimicrob Agents Chemother Date: 2017-06-27 Impact factor: 5.191
Authors: Peter J Pronovost; Christine A Goeschel; Elizabeth Colantuoni; Sam Watson; Lisa H Lubomski; Sean M Berenholtz; David A Thompson; David J Sinopoli; Sara Cosgrove; J Bryan Sexton; Jill A Marsteller; Robert C Hyzy; Robert Welsh; Patricia Posa; Kathy Schumacher; Dale Needham Journal: BMJ Date: 2010-02-04
Authors: Mohamed A Jamal; Joel S Rosenblatt; Ray Y Hachem; Jiang Ying; Egbert Pravinkumar; Joseph L Nates; Anne-Marie P Chaftari; Issam I Raad Journal: Antimicrob Agents Chemother Date: 2013-10-28 Impact factor: 5.191