PDF(Pubmed)
Abstract：
Antimicrobial de-escalation refers to reducing the spectrum of antibiotics used in treating bacterial infections. This strategy is widely recommended in many antimicrobial stewardship programs and is believed to reduce patients\' exposure to broad-spectrum antibiotics and prevent resistance. However, the ecological benefits of de-escalation have not been universally observed in clinical studies. This paper conducts computer simulations to assess the ecological effects of de-escalation on the resistance prevalence of Pseudomonas aeruginosa-a frequent pathogen causing nosocomial infections. Synthetic data produced by the models are then used to estimate the sample size and study period needed to observe the predicted effects in clinical trials. Our results show that de-escalation can reduce colonization and infections caused by bacterial strains resistant to the empiric antibiotic, limit the use of broad-spectrum antibiotics, and avoid inappropriate empiric therapies. Further, we show that de-escalation could reduce the overall super-infection incidence, and this benefit becomes more evident under good compliance with hand hygiene protocols among health care workers. Finally, we find that any clinical study aiming to observe the essential effects of de-escalation should involve at least ten arms and last for four years-a size never attained in prior studies. This study explains the controversial findings of de-escalation in previous clinical studies and illustrates how mathematical models can inform outcome expectations and guide the design of clinical studies.
摘要：
抗微生物剂降级是指减少用于治疗细菌感染的抗生素谱。该策略在许多抗菌药物管理计划中被广泛推荐，并被认为可以减少患者对广谱抗生素的暴露并防止耐药性。然而,在临床研究中尚未普遍观察到降级的生态效益.本文进行了计算机模拟，以评估降级对铜绿假单胞菌耐药性流行的生态影响。铜绿假单胞菌是引起医院感染的常见病原体。然后使用模型产生的合成数据来估计在临床试验中观察预测效果所需的样本量和研究时间。我们的结果表明，降级可以减少由对经验性抗生素具有抗性的细菌菌株引起的定植和感染，限制广谱抗生素的使用，避免不适当的经验性治疗。Further,我们表明降级可以降低整体的超级感染发生率，在医护人员良好遵守手部卫生协议的情况下，这种益处变得更加明显。最后,我们发现,任何旨在观察降级的基本影响的临床研究应至少涉及十只手臂,并持续4年,这一规模在以前的研究中从未达到.本研究解释了先前临床研究中关于降级的有争议的发现，并说明了数学模型如何为结果预期提供信息并指导临床研究的设计。
