Next-generation microbiological testing in intraabdominal infections with PCR technology

LANGENBECKS ARCHIVES OF SURGERY(2024)

引用 0|浏览0
暂无评分
摘要
Purpose Intraabdominal infections (IAI) are increasing worldwide and are a major contributor to morbidity and mortality. Among IAI, the number of multi-drug resistant organisms (MDRO) is increasing globally. We tested the Unyvero A50 (R) for intraabdominal infections, compared the detected microorganisms and antibiotic resistance, and compared the results with those of routine microbiology.Methods We prospectively compared samples obtained from surgical patients using PCR-based Unyvero IAI cartridges against routine microbiology for the detection of microorganisms. Additionally, we identified clinical parameters that correlated with the microbiological findings. Data were analyzed using the t-test and Mann-Whitney U test.Results Sixty-two samples were analyzed. The PCR system identified more microorganisms, mostly Bacteroides species, Escherichia coli, and Enterococcus spp. For bacterial resistance, the PCR system results were fully concordant with those of routine microbiology, resulting in a sensitivity, specificity, and positive and negative predictive value (PPV, NPV) of 100%. The sensitivity, specificity, PPV, and NPV for the detection of microorganisms were 74%, 58%, 60%, and 72%, respectively. CRP levels were significantly higher in patients with detectable microorganisms. We identified more microorganisms and bacterial resistance in hospital-acquired intra-abdominal infections by using the PCR system.Discussion IAI warrants early identification of the microorganisms involved and their resistance to allow for adequate antibiotic therapy. PCR systems enable physicians to rapidly adjust their antibiotic treatment. Conventional microbiological culture and testing remain essential for determining the minimal growth inhibition concentrations for antibiotic therapy.
更多
查看译文
关键词
Intraabdominal infection,Resistant microorganisms,PCR testing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要