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Use of microbiological and patient data for choice of empirical antibiotic therapy in acute cholangitis.

ABSTRACT: BACKGROUND:Ineffective antibiotic therapy increases mortality of acute cholangitis. The choice of antibiotics should reflect local resistance patterns and avoid the overuse of broad-spectrum agents. In this study, we analysed how results of bile and blood cultures and patient data can be used for selection of empirical antibiotic therapy in acute cholangits. METHODS:Pathogen frequencies and susceptibility rates were determined in 423 positive bile duct cultures and 197 corresponding blood cultures obtained from 348 consecutive patients with acute cholangitis. Patient data were retrieved from the medical records. Associations of patient and microbiological data were assessed using the Chi-2 test and multivariate binary logistic regression. RESULTS:In bile cultures, enterobacterales and enterococci were isolated with equal frequencies of approximately 30% whereas in blood cultures, enterobacterales predominated (56% compared to 21% enterococci). Antibiotic resistance rates of enterobacterales were?>?20% for fluorochinolones, cephalosporines and acylureidopenicillins but not for carbapenems (

SUBMITTER: Kruis T

PROVIDER: S-EPMC7066745 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Use of microbiological and patient data for choice of empirical antibiotic therapy in acute cholangitis.

Kruis Tassilo T Güse-Jaschuck Sarah S Siegmund Britta B Adam Thomas T Epple Hans-Jörg HJ

BMC gastroenterology 20200312 1

<h4>Background</h4>Ineffective antibiotic therapy increases mortality of acute cholangitis. The choice of antibiotics should reflect local resistance patterns and avoid the overuse of broad-spectrum agents. In this study, we analysed how results of bile and blood cultures and patient data can be used for selection of empirical antibiotic therapy in acute cholangits.<h4>Methods</h4>Pathogen frequencies and susceptibility rates were determined in 423 positive bile duct cultures and 197 correspondi ...[more]

PMID: 32164573

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Project description:Personalized medicine (PM) operates with biological data to optimize therapy or prevention and to achieve cost reduction. Associated data may consist of large variations of informational subtypes e.g. genetic characteristics and their epigenetic modifications, biomarkers or even individual lifestyle factors. Present innovations in the field of information technology have already enabled the procession of increasingly large amounts of such data ('volume') from various sources ('variety') and varying quality in terms of data accuracy ('veracity') to facilitate the generation and analyzation of messy data sets within a short and highly efficient time period ('velocity') to provide insights into previously unknown connections and correlations between different items ('value'). As such developments are characteristics of Big Data approaches, Big Data itself has become an important catchphrase that is closely linked to the emerging foundations and approaches of PM. However, as ethical concerns have been pointed out by experts in the debate already, moral concerns by stakeholders such as patient organizations (POs) need to be reflected in this context as well. We used an empirical-ethical approach including a website-analysis and 27 telephone-interviews for gaining in-depth insight into German POs' perspectives on PM and Big Data. Our results show that not all POs are stakeholders in the same way. Comparing the perspectives and political engagement of the minority of POs that is currently actively involved in research around PM and Big Data-driven research led to four stakeholder sub-classifications: 'mediators' support research projects through facilitating researcher's access to the patient community while simultaneously selecting projects they preferably support while 'cooperators' tend to contribute more directly to research projects by providing and implemeting patient perspectives. 'Financers' provide financial resources. 'Independents' keep control over their collected samples and associated patient-related information with a strong interest in making autonomous decisions about its scientific use. A more detailed terminology for the involvement of POs as stakeholders facilitates the adressing of their aims and goals. Based on our results, the 'independents' subgroup is a promising candidate for future collaborations in scientific research. Additionally, we identified gaps in PO's knowledge about PM and Big Data. Based on these findings, approaches can be developed to increase data and statistical literacy. This way, the full potential of stakeholder involvement of POs can be made accessible in discourses around PM and Big Data.

Project description:The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling). Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43-0.48] and resistant infections by 7.2 [14.00-0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing). We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call "adjustable cycling/mixing". In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that "adjustable cycling" is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that "adjustable cycling" suppresses multiple resistance and warrants further investigations that allow comparing various diseases and hospital settings.

Dataset Information

Use of microbiological and patient data for choice of empirical antibiotic therapy in acute cholangitis.

Publications

Use of microbiological and patient data for choice of empirical antibiotic therapy in acute cholangitis.

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