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Forecasting carbapenem resistance from antimicrobial consumption surveillance: Lessons learnt from an OXA-48-producing Klebsiella pneumoniae outbreak in a West London renal unit

机译:通过抗菌药物消费监测预测碳青霉烯抗药性:从伦敦西部肾脏单位发生的产生OXA-48的肺炎克雷伯菌肺炎暴发中吸取的经验教训

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This study aimed to forecast the incidence rate of carbapenem resistance and to assess the impact of an antimicrobial stewardship intervention using routine antimicrobial consumption surveillance data. Following an outbreak of OXA-48-producing Klebsiella pneumoniae (January 2008-April 2010) in a renal cohort in London, a forecasting ARIMA model was derived using meropenem consumption data [defined daily dose per 100 occupied bed-days (DDD/100 OBD)] from 2005-2014 as a predictor of the incidence rate of OXA-48-producing organisms (number of new cases/year/100,000 OBD). Interrupted times series assessed the impact of meropenem consumption restriction as part of the outbreak control. Meropenem consumption at lag -1 year (the preceding year), highly correlated with the incidence of OXA-48-producing organisms (r = 0.71; P = 0.005), was included as a predictor within the forecasting model. The number of cases/100,000 OBD for 2014-2015 was estimated to be 4.96 (95% CI 2.53-7.39). Analysis of meropenem consumption pre- and post-intervention demonstrated an increase of 7.12 DDD/100 OBD/year (95% CI 2.97-11.27; P < 0.001) in the 4 years preceding the intervention, but a decrease thereafter. The change in slope was -9.11 DDD/100 OBD/year (95% CI -13.82 to -4.39). Analysis of alternative antimicrobials showed a significant increase in amikacin consumption post-intervention from 0.54 to 3.41 DDD/100 OBD/year (slope +0.72, 95% CI 0.29-1.15; P = 0.01). Total antimicrobials significantly decreased from 176.21 to 126.24 DDD/100 OBD/year (P = 0.05). Surveillance of routinely collected antimicrobial consumption data may provide a key warning indicator to anticipate increased incidence of carbapenem-resistant organisms. Further validation using real-time data is needed. (C) 2015 The Authors. Published by Elsevier B.V.
机译:这项研究旨在预测碳青霉烯耐药性的发生率,并使用常规的抗菌药物消费监测数据评估抗菌药物管理干预的影响。在伦敦的一个肾脏队列中爆发了产生OXA-48的肺炎克雷伯菌(2008年1月至2010年4月),使用美罗培南的消费数据[定义了每100个就诊日的日剂量(DDD / 100 OBD,每天定义的剂量),得出了预测的ARIMA模型)]作为2005年至2014年间可预测产生OXA-48的生物体发生率的指标(新病例数/年/ 100,000 OBD)。中断时间序列评估了美罗培南消费限制的影响,作为爆发控制的一部分。滞后-1年(前一年)的美洛培南的消费与产生OXA-48的生物的发生率高度相关(r = 0.71; P = 0.005),被作为预测模型包括在内。 2014-2015年的100,000 OBD案例数估计为4.96(95%CI 2.53-7.39)。干预前后美罗培南消费量的分析表明,干预前4年,美罗培南的消费量增加了7.12 DDD / 100 OBD /年(95%CI 2.97-11.27; P <0.001),但此后有所下降。斜率变化为-9.11 DDD / 100 OBD /年(95%CI -13.82至-4.39)。替代抗微生物药物的分析显示,干预后丁胺卡那霉素的消费量从0.54到3.41 DDD / 100 OBD /年显着增加(斜率+ 0.72,95%CI 0.29-1.15; P = 0.01)。总抗菌药物从176.21 DDD / 100 OBD /年显着降低(P = 0.05)。常规收集的抗菌药物消费数据的监测可能会提供一个重要的预警指标,以预测耐碳青霉烯生物的发生率增加。需要使用实时数据进行进一步验证。 (C)2015作者。由Elsevier B.V.发布

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