Systemic analysis of the AST results in medical organizations of the Russian Federation

Q4 Medicine
Alina G. Vinogradova, Alexey Yu. Kuzmenkov, Ivan V. Trushin, Marina V. Sukhorukova, Roman S. Kozlov
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Abstract

Objective. To analyse aggregated AST results for key microorganisms collected through the 2022 reports of chief specialists in clinical microbiology and antimicrobial resistance. Materials and Methods. The study included an analysis of the interpretation criteria used in the laboratories and an evaluation of the AST reports. Data were obtained from the clinical microbiology and antimicrobial resistance annual reporting system. Reports were analyzed using EUCAST guidelines for expected resistance phenotypes and expected susceptible phenotypes. Data processing and analysis were realized using the «R» programming language. The 95% CI for the percentages of inaccuracies/errors distributed by federal districts was calculated using the Wilson method. Results. A combination of several interpretation standards was used in 27.78% of laboratories, MUK 4.2.1890-04 was noted as one of the options in 57.6% of laboratories. Irrelevant standards of interpretation with a lag of 1 year or more were used in a significant number of cases. The highest percentage of errors/ inaccuracies by the type «expected resistance» was observed for A. baumannii – 14,06% (N = 9163), E. faecium – 8,05% (N = 3451) and S. pneumoniae – 6,18% (N = 2779). «Susceptibility categorization in the absence of interpretive breakpoints» was highest for S. aureus – 13.24% (N = 19784) and S. pneumoniae – 8.76% (N = 3942). Rare phenotype was determined in the highest percentage in relation to S. pneumoniae and antimicrobials: vancomycin – 54.04% and linezolid – 64.6%. Conclusions. The study revealed a significant number of errors/inaccuracies in the data reported. The use of irrelevant interpretation criteria, the exclusion of situations with rare phenotypes and expected resistance, may contribute to a significant increase in the likelihood of inappropriate antibacterial prescribing.
对俄罗斯联邦医疗机构的AST结果进行系统分析
目标。分析通过临床微生物学和抗菌素耐药性首席专家的2022份报告收集的关键微生物的AST汇总结果。材料与方法。该研究包括对实验室使用的解释标准的分析和对AST报告的评价。数据来源于临床微生物学和抗菌药物耐药性年度报告系统。报告使用EUCAST指南对预期耐药表型和预期易感表型进行分析。数据处理和分析使用«R»编程语言实现。联邦区分布的不准确/误差百分比的95% CI使用Wilson方法计算。结果。27.78%的实验室采用多种解释标准的组合,57.6%的实验室选择MUK 4.2.1890-04。在相当数量的病例中,使用了滞后1年或更长时间的不相关的解释标准。按“预期耐药”类型划分的错误/不准确百分比最高的是鲍曼芽胞杆菌14.06% (N = 9163)、屎肠杆菌8.05% (N = 3451)和肺炎链球菌6.18% (N = 2779)。“没有解释断点的敏感性分类”在金黄色葡萄球菌和肺炎葡萄球菌中最高,分别为13.24% (N = 19784)和8.76% (N = 3942)。罕见表型与肺炎链球菌和抗菌剂相关的比例最高:万古霉素为54.04%,利奈唑胺为64.6%。结论。这项研究揭示了所报告的数据中大量的错误/不准确之处。使用不相关的解释标准,排除具有罕见表型和预期耐药性的情况,可能会导致不适当的抗菌药物处方的可能性显著增加。
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CiteScore
0.90
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