The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Treatment of Infections Due to MDR Gram-Negative Bacteria
Open accessAbstract
The treatment of multidrug-resistant Gram-negative bacteria (MDR-GNB) infections in critically ill patients presents many challenges. Since an effective treatment should be administered as soon as possible, resistance to many antimicrobial classes almost invariably reduces the probability of adequate empirical coverage, with possible unfavorable consequences. In this light, readily available patient’s medical history and updated information about the local microbiological epidemiology remain critical for defining the baseline risk of MDR-GNB infections and firmly guiding empirical treatment choices, with the aim of avoiding both undertreatment and overtreatment. Rapid diagnostics and efficient laboratory workflows are also of paramount importance both for anticipating diagnosis and for rapidly narrowing the antimicrobial spectrum, with de-escalation purposes and in line with antimicrobial stewardship principles. Carbapenem-resistant Enterobacteriaceae, Pseudomonas aeruginosa, and Acinetobacter baumannii are being reported with increasing frequencies worldwide, although with important variability across regions, hospitals and even single wards. In the past few years, new treatment options, such as ceftazidime/avibactam, meropenem/vaborbactam, ceftolozane/tazobactam, and plazomicin have become available, and others will become soon, which have provide some much awaited resources for effectively counteracting severe infections due to these organisms. However, their optimal use should be guaranteed in the long term, for delaying as much as possible the emergence and diffusion of resistance to novel agents. Despite important progresses, PK/PD optimization of dosages and treatment duration in critically ill patients has still some areas of uncertainty requiring further study, that should take into account also resistance selection as a major endpoint. Treatment of severe MDR-GNB infections in critically ill patients in the near future will require an expert and complex clinical reasoning, of course taking into account the peculiar characteristics of the target population, but also the need for adequate empirical coverage and the more and more specific enzyme-level activity of novel antimicrobials with respect to the different resistance mechanisms of MDR-GNB.
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Clinical epidemiology of the global expansion of Klebsiella pneumoniae carbapenemases
Munoz-Price, L. S., Poirel, L., Bonomo, R. A., Schwaber, M. J., Daikos, G. L., Cormican, M., Cornaglia, G., Garau, J., Gniadkowski, M., Hayden, M. K., et al. (2013) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(13)70190-7 · Cited by 1,627
Tumbarello, M., Viale, P., Viscoli, C., Trecarichi, E. M., Tumietto, F., Marchese, A., Spanu, T., Ambretti, S., Ginocchio, F., Cristini, F., et al. (2012) · Clinical Infectious Diseases · doi:10.1093/cid/cis588 · Cited by 1,016
Self-citationTsuji, B. T., Pogue, J. M., Zavascki, A. P., Paul, M., Daikos, G. L., Forrest, A., Giacobbe, D. R., Viscoli, C., Giamarellou, H., Karaiskos, I., et al. (2019) · Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy · doi:10.1002/phar.2209 · Cited by 949
Self-citationGaronzik, S. M., Li, J., Thamlikitkul, V., Paterson, D. L., Shoham, S., Jacob, J., Silveira, F. P., Forrest, A., & Nation, R. L. (2011) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.01733-10 · Cited by 696
Paul, M., Daikos, G. L., Durante-Mangoni, E., Yahav, D., Carmeli, Y., Benattar, Y. D., Skiada, A., Andini, R., Eliakim-Raz, N., Nutman, A., et al. (2018) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(18)30099-9 · Cited by 623
Kadri, S. S., Adjemian, J., Lai, Y. L., Spaulding, A. B., Ricotta, E., Prevots, D. R., Palmore, T. N., Rhee, C., Klompas, M., Dekker, J. P., et al. (2018) · Clinical Infectious Diseases · doi:10.1093/cid/ciy378 · Cited by 605
Daikos, G. L., Tsaousi, S., Tzouvelekis, L. S., Anyfantis, I., Psichogiou, M., Argyropoulou, A., Stefanou, I., Sypsa, V., Miriagou, V., Nepka, M., et al. (2014) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.02166-13 · Cited by 597
Peptidomimetic Antibiotics Target Outer-Membrane Biogenesis in Pseudomonas aeruginosa
Srinivas, N., Jetter, P., Ueberbacher, B. J., Werneburg, M., Zerbe, K., Steinmann, J., Van der Meijden, B., Bernardini, F., Lederer, A., Dias, R. L. A., et al. (2010) · Science · doi:10.1126/science.1182749 · Cited by 554
Tumbarello, M., Trecarichi, E. M., De Rosa, F. G., Giannella, M., Giacobbe, D. R., Bassetti, M., Losito, A. R., Bartoletti, M., Del Bono, V., Corcione, S., et al. (2015) · Journal of Antimicrobial Chemotherapy · doi:10.1093/jac/dkv086 · Cited by 511
Self-citationShields, R. K., Nguyen, M. H., Chen, L., Press, E. G., Potoski, B. A., Marini, R. V., Doi, Y., Kreiswirth, B. N., & Clancy, C. J. (2017) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.00883-17 · Cited by 495
Cited by
Antimicrobial Resistance: Implications and Costs
Dadgostar, P. (2019) · Infection and Drug Resistance · doi:10.2147/idr.s234610 · Cited by 2,024
Population genomics of Klebsiella pneumoniae
Wyres, K. L., Lam, M. M. C., & Holt, K. E. (2020) · Nature Reviews Microbiology · doi:10.1038/s41579-019-0315-1 · Cited by 1,160
Bloodstream infections in critically ill patients: an expert statement
Timsit, J.-F., Ruppé, E., Barbier, F., Tabah, A., & Bassetti, M. (2020) · Intensive Care Medicine · doi:10.1007/s00134-020-05950-6 · Cited by 448
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Metadata
- Authors
- Bassetti, M., Peghin, M., Vena, A., & Giacobbe, D. R.
- Venue
- Frontiers in Medicine
- Publisher
- Frontiers Media SA
- Published
- 2019-04-16
- Volume
- 6
- Pages
- 74-74
- ISSN
- 2296-858X (ISSN-L)
- OpenAlex
- W2924739878
- Cited by
- 326
- References
- 59
- FWCI
- 12.81
- Type
- journal article
- Language
- en
- Open access
- gold
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