Ángel Rodríguez-Villodres, María Valentina Hoffmann-Álvarez, Pedro Camacho-Martínez, José Antonio Lepe
{"title":"商业智能对支气管脓毒杆菌等罕见微生物感染的抗菌治疗决策的指导作用。","authors":"Ángel Rodríguez-Villodres, María Valentina Hoffmann-Álvarez, Pedro Camacho-Martínez, José Antonio Lepe","doi":"10.37201/req/125.2024","DOIUrl":null,"url":null,"abstract":"<p><p>Human infections by <i>Bordetella bronchiseptica</i> are increasing in recent years. However, due to the lack of clinical susceptibility/resistance breakpoints, antimicrobial treatment is complex. Business Intelligence (BI) is a tool that allows to record and analyze large amounts of data in a very short time. The aim of this study was to analyze a cohort of patients with <i>B. bronchiseptica</i> infections focusing on how BI can help guide empirical antimicrobial therapy Demographic, clinical, and microbiological data about <i>B. bronchiseptica</i> infections were recovered. Then, MIC<sub>50/90</sub> of several antibiotics was automatically calculated through the BI. Thirteen <i>B. bronchiseptica</i> infections were identified. The lowest MICs<sub>90</sub> were for carbapenem, aminoglycoside, fluoroquinolones, and tetracyclines. The EUCAST PK-PD (non-species related) breakpoints showed that only piperacillin/tazobactam, imipenem and meropenem would be appropriate treatments to use empirically. In conclusion, BI systems have great potential to optimize the empirical antibiotic treatment in these types of infections.</p>","PeriodicalId":94198,"journal":{"name":"Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia","volume":"38 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Usefulness of business intelligence to guide antimicrobial treatment decision in infections by infrequent microorganism such as <i>Bordetella bronchiseptica</i>.\",\"authors\":\"Ángel Rodríguez-Villodres, María Valentina Hoffmann-Álvarez, Pedro Camacho-Martínez, José Antonio Lepe\",\"doi\":\"10.37201/req/125.2024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Human infections by <i>Bordetella bronchiseptica</i> are increasing in recent years. However, due to the lack of clinical susceptibility/resistance breakpoints, antimicrobial treatment is complex. Business Intelligence (BI) is a tool that allows to record and analyze large amounts of data in a very short time. The aim of this study was to analyze a cohort of patients with <i>B. bronchiseptica</i> infections focusing on how BI can help guide empirical antimicrobial therapy Demographic, clinical, and microbiological data about <i>B. bronchiseptica</i> infections were recovered. Then, MIC<sub>50/90</sub> of several antibiotics was automatically calculated through the BI. Thirteen <i>B. bronchiseptica</i> infections were identified. The lowest MICs<sub>90</sub> were for carbapenem, aminoglycoside, fluoroquinolones, and tetracyclines. The EUCAST PK-PD (non-species related) breakpoints showed that only piperacillin/tazobactam, imipenem and meropenem would be appropriate treatments to use empirically. In conclusion, BI systems have great potential to optimize the empirical antibiotic treatment in these types of infections.</p>\",\"PeriodicalId\":94198,\"journal\":{\"name\":\"Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia\",\"volume\":\"38 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37201/req/125.2024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista espanola de quimioterapia : publicacion oficial de la Sociedad Espanola de Quimioterapia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37201/req/125.2024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Usefulness of business intelligence to guide antimicrobial treatment decision in infections by infrequent microorganism such as Bordetella bronchiseptica.
Human infections by Bordetella bronchiseptica are increasing in recent years. However, due to the lack of clinical susceptibility/resistance breakpoints, antimicrobial treatment is complex. Business Intelligence (BI) is a tool that allows to record and analyze large amounts of data in a very short time. The aim of this study was to analyze a cohort of patients with B. bronchiseptica infections focusing on how BI can help guide empirical antimicrobial therapy Demographic, clinical, and microbiological data about B. bronchiseptica infections were recovered. Then, MIC50/90 of several antibiotics was automatically calculated through the BI. Thirteen B. bronchiseptica infections were identified. The lowest MICs90 were for carbapenem, aminoglycoside, fluoroquinolones, and tetracyclines. The EUCAST PK-PD (non-species related) breakpoints showed that only piperacillin/tazobactam, imipenem and meropenem would be appropriate treatments to use empirically. In conclusion, BI systems have great potential to optimize the empirical antibiotic treatment in these types of infections.