The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Prevention of Resistance: A Goal for Dose Selection for Antimicrobial Agents
Abstract
Drug-resistant microorganisms have become a major problem around the world. In nosocomial and community settings, many important pathogens have demonstrated high-grade resistance to many of our most important agents. In addition, the adverse impact of resistance has not been limited to the bacterial realm. In chemotherapy to treat human immunodeficiency virus (HIV) and other viral diseases, resistance has become a major problem. We are starting to see the beginnings of a resistance problem, even among fungi. Strangely, little attention has been focused on the impact of dosing on the probability with which emergence of resistance occurs. After delineation of the pharmacodynamically linked variable, it is possible to generate dosing regimens that can lower the probability of resistance. In addition, circumstances exist in which combination therapy may be required (e.g., therapy of HIV and tuberculosis). Here, too, it is possible to optimize therapy to prevent resistance by understanding how the drugs in the regimen interact. We can do better with our choices of dose, schedule, and combinations of agents. We will need to lower the probability of resistance and maintain the utility of the drugs currently in our therapeutic armamentarium.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Perea, S., López-Ribot, J. L., Kirkpatrick, W. R., McAtee, R. K., Santillán, R. A., Martı́nez, M., Calabrese, D., Sanglard, D., & Patterson, T. F. (2001) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.45.10.2676-2684.2001 · Cited by 470
Cited by
Roberts, J. A., Abdul-Aziz, M. H., Lipman, J., Mouton, J. W., Vinks, A. A., Felton, T. W., Hope, W. W., Farkas, A., Neely, M. N., Schentag, J. J., et al. (2014) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(14)70036-2 · Cited by 1,046
Self-citationAntimicrobial pharmacodynamics: critical interactions of 'bug and drug'
Drusano, G. L. (2004) · Nature Reviews Microbiology · doi:10.1038/nrmicro862 · Cited by 930
Self-citationBacterial Resistance: Origins, Epidemiology, and Impact
Livermore, D. M. (2003) · Clinical Infectious Diseases · doi:10.1086/344654 · Cited by 586
Augmented Renal Clearance: Implications for Antibacterial Dosing in the Critically Ill
Udy, A. A., Roberts, J. A., Boots, R. J., Paterson, D. L., & Lipman, J. (2010) · Clinical Pharmacokinetics · doi:10.2165/11318140-000000000-00000 · Cited by 377
Metadata
- Authors
- Drusano, G. L.
- Venue
- Clinical Infectious Diseases
- Publisher
- Oxford University Press (OUP)
- Published
- 2003-01-15
- Volume
- 36
- Issue
- Supplement_1
- Pages
- S42-S50
- ISSN
- 1058-4838 (ISSN-L)
- 1537-6591
- OpenAlex
- W2137194557
- Cited by
- 356
- References
- 1
- FWCI
- 11.17
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.