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Cycling Empirical Antibiotic Therapy in Hospitals: Meta-Analysis and Models

机译:医院循环经验性抗生素治疗的荟萃分析和模型

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摘要

The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling). Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43–0.48] and resistant infections by 7.2 [14.00–0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing). We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call “adjustable cycling/mixing”. In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that “adjustable cycling” is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that “adjustable cycling” suppresses multiple resistance and warrants further investigations that allow comparing various diseases and hospital settings.
机译:耐药性的上升以及新广谱抗生素的短缺,凸显了优化利用现有药物以最大程度降低疾病负担的紧迫性。理论研究表明,在医院病房中协调经验性使用抗生素可以遏制耐药性的扩散。但是,关于旋转一线治疗(循环)的有效性,理论和临床研究得出了不同的结论。在这里,我们进行了定量的病原体特异性荟萃分析,比较了自行车运动与标准操作。我们搜索了PubMed和Google Scholar,并确定了46项临床研究,研究了骑自行车对医院感染的影响,其中11项符合我们的选择标准。我们采用了一种以发生率作为终点的多元荟萃分析方法,发现骑自行车减少了每千名患者每天的总感染率4.95 [9.43-0.48]和耐药性感染率7.2 [14.00-0.44]。尽管各个物种之间差异很大,但在大多数病原体中都观察到了这种积极作用。我们的发现在单变量和多元元回归中仍然很可靠。我们使用反映各种感染和医院环境的理论模型来比较骑自行车和随机分配给不同药物(混合)的情况。我们做出现实的假设,即在一线治疗无效时会改变治疗方法,我们称之为“可调循环/混合”。与早期的理论研究一致,我们发现在严格的治疗方案中,骑车有害。但是,在可调方案中,单阻力被抑制,并且在大多数情况下循环都是成功的。元回归和我们的理论模型均表明,“可调循环”对于抑制多重阻力的出现特别有用。虽然我们的模型预测一个月的骑车周期表现良好,但我们认为太长的骑车周期是有害的。我们的结果表明,“可调节的循环”可抑制多重耐药性,因此有必要进行进一步的研究,以比较各种疾病和医院环境。

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