Melbourne Medical School, University of Melbourne, Melbourne, Australia.
Division of Internal Medicine, Grampians Health Ballarat, PO Box 577, Ballarat, VIC, 3353, Australia.
Eur J Clin Microbiol Infect Dis. 2023 May;42(5):543-554. doi: 10.1007/s10096-023-04573-1. Epub 2023 Mar 6.
Whether Candida within the patient microbiome drives the pathogenesis of Staphylococcus aureus bacteremia, described as microbial hitchhiking, cannot be directly studied. Group-level observations from studies of various decontamination and non-decontamination-based ICU infection prevention interventions and studies without study interventions (observational groups) collectively enable tests of this interaction within causal models. Candidate models of the propensity for Staphylococcus aureus bacteremia to arise with versus without various antibiotic, anti-septic, and antifungal exposures, each identified as singleton exposures, were tested using generalized structural equation modelling (GSEM) techniques with Candida and Staphylococcus aureus colonization appearing as latent variables within the models. Each model was tested by confrontation against blood and respiratory isolate data, obtained from 467 groups within 284 infection prevention studies. Introducing an interaction term between Candida colonization and Staphylococcus aureus colonization substantially improved GSEM model fit. Model-derived coefficients for singular exposure to anti-septic agents (- 1.28; 95% confidence interval; - 2.05 to - 0.5), amphotericin (- 1.49; - 2.3 to - 0.67), and topical antibiotic prophylaxis (TAP; + 0.93; + 0.15 to + 1.71) as direct effects versus Candida colonization were similar in magnitude but contrary in direction. By contrast, the coefficients for singleton exposure to TAP, as with anti-septic agents, versus Staphylococcus colonization were weaker or non-significant. Topical amphotericin would be predicted to halve both candidemia and Staphylococcus aureus bacteremia incidences versus literature derived benchmarks for absolute differences of < 1 percentage point. Using ICU infection prevention data, GSEM modelling validates the postulated interaction between Candida and Staphylococcus colonization facilitating bacteremia.
在患者微生物组中是否有念珠菌驱动金黄色葡萄球菌菌血症的发病机制,被描述为微生物搭便车,这不能直接研究。来自各种去污和非去污 ICU 感染预防干预研究以及没有研究干预(观察组)的研究的群组级观察结果,共同使该相互作用能够在因果模型中得到测试。使用广义结构方程模型(GSEM)技术测试了在有无各种抗生素、防腐剂和抗真菌剂暴露的情况下金黄色葡萄球菌菌血症发生的倾向的候选模型,每个模型都被确定为单暴露,在模型中,念珠菌和金黄色葡萄球菌定植作为潜在变量出现。每个模型都通过与来自 284 项感染预防研究的 467 组的血液和呼吸道分离物数据进行对抗来进行测试。在念珠菌定植和金黄色葡萄球菌定植之间引入交互项,极大地改善了 GSEM 模型拟合度。通过 GSEM 模型得出的对防腐剂(-1.28;95%置信区间;-2.05 至-0.5)、两性霉素(-1.49;-2.3 至-0.67)和局部抗生素预防(TAP;+0.93;+0.15 至+1.71)的单一暴露的系数与念珠菌定植的直接效应相似,但方向相反。相比之下,TAP 与防腐剂一样,对金黄色葡萄球菌定植的单一暴露的系数较弱或无统计学意义。与文献中获得的绝对差异基准相比,局部两性霉素的使用预计将使念珠菌血症和金黄色葡萄球菌菌血症的发生率减半,差异<1 个百分点。使用 ICU 感染预防数据,GSEM 模型验证了假设的念珠菌和金黄色葡萄球菌定植之间的相互作用,从而促进了菌血症的发生。