Hurley James C
Rural Health Academic Center, Melbourne Medical School, University of Melbourne, Ballarat 3350, Australia.
J Fungi (Basel). 2020 Oct 27;6(4):252. doi: 10.3390/jof6040252.
Whether interacts to enhance the invasive potential of and bacteria cannot be resolved within individual studies. There are several anti-septic, antibiotic, anti-fungal, and non-decontamination-based interventions to prevent ICU acquired infection. These effective prevention interventions would be expected to variably impact colonization. The collective observations within control and intervention groups from numerous ICU infection prevention studies simulates a multi-centre natural experiment with which to evaluate , and interaction (CAPI).
Eight Candidate-generalized structural equation models (GSEM), with , and colonization as latent variables, were confronted with blood culture and respiratory tract isolate data derived from >400 groups derived from 286 infection prevention studies.
Introducing an interaction term between colonization and each of and colonization improved model fit in each case. The size of the coefficients (and 95% confidence intervals) for these interaction terms in the optimal (+0.33; 0.22 to 0.45) and models (+0.32; 0.01 to 0.5) were similar to each other and similar in magnitude, but contrary in direction, to the coefficient for exposure to topical antibiotic prophylaxis (TAP) on colonization (-0.45; -0.71 to -0.2). The coefficient for exposure to topical antibiotic prophylaxis on colonization was not significant.
GSEM modelling of published ICU infection prevention data supports the CAPI concept. The CAPI model could account for some paradoxically high and infection incidences, most apparent among the concurrent control groups of TAP studies.
[具体细菌名称]之间是否相互作用以增强[具体细菌名称]和[具体细菌名称]的侵袭潜力，无法在单个研究中得到解决。有几种基于防腐剂、抗生素、抗真菌和非去污的干预措施来预防重症监护病房（ICU）获得性感染。这些有效的预防干预措施预计会对[具体细菌名称]的定植产生不同程度的影响。来自众多ICU感染预防研究的对照组和干预组的综合观察结果模拟了一项多中心自然实验，可用于评估[具体细菌名称]、[具体细菌名称]和[具体细菌名称]之间的相互作用（CAPI）。
八个候选广义结构方程模型（GSEM），以[具体细菌名称]、[具体细菌名称]和[具体细菌名称]的定植作为潜在变量，与来自286项感染预防研究的400多个组的血培养和呼吸道分离数据进行对比。
在[具体细菌名称]定植与[具体细菌名称]和[具体细菌名称]定植之间引入相互作用项，在每种情况下都改善了模型拟合。在最优的[具体模型名称]（+0.33；0.22至0.45）和[具体模型名称]模型（+0.32；0.01至0.5）中，这些相互作用项的系数大小（以及95%置信区间）彼此相似，且在大小上与局部抗生素预防（TAP）暴露对[具体细菌名称]定植的系数相似，但方向相反（-0.45；-0.71至-0.2）。局部抗生素预防暴露对[具体细菌名称]定植的系数不显著。
对已发表的ICU感染预防数据进行GSEM建模支持CAPI概念。CAPI模型可以解释一些矛盾的高[具体细菌名称]和[具体细菌名称]感染发生率，这在TAP研究的同期对照组中最为明显。
