2019 年 24 巻 1 号 p. 39-48
The resistance rate (RR) to antimicrobials is useful laboratory evidence for clinicians, especially for guiding empirical therapy. Similarly, cross-resistance rate (CRR) is important when alternative antimicrobials are needed, or when several antimicrobials need to be simultaneously administered. However, CRR information is currently organized in a complicated matrix that does not facilitate quick comprehension of the trends. Therefore, we have developed a new “CRR diagram” to better visualize and comprehend the CRR matrix and explain how to understand cross- resistance using a CRR diagram. Next, to verify the usefulness of this diagram, we evaluated its function using real-world clinical data. In the CRR diagram, the horizontal axis represents the CRR of the object antimicrobials (OAM) with respect to the base-antimicrobial (BAM), while the vertical axis represents the CRR of BAM to OAM. The CRR diagram was derived using antimicrobial susceptibility test data of Pseudomonas aeruginosa isolated at the Takanohara Central Hospital. All analyses were carried out using the software “Chans”, which was originally developed by Hatsuda, the lead author of this paper. Using the CRR diagram, we could discern the magnitude of RR from the gradient of the line passing through the origin and each data point. By comparing data positions, we could easily identify similarities and differences in antibacterial effect and the sensitivity spectrum. Consequently, trends in cross-resistance between antimicrobials could be recognized more easily and comprehensively compared to conventional methods. The CRR diagram is a useful method for determining the optimal antimicrobial.
