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Antimicrobials for bovine respiratory disease (Proceedings)

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Aug 01, 2010


Table: drugs approved in the U.S. for bovine respiratory disease
Bovine respiratory disease complex includes bacterial components, which cause the classic clinical signs of lethargy, depression, and fever, with variable nasal discharge, cough, or other signs. This bacterial component of BRD (most commonly Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, and Mycoplasma bovis) may be treated with antimicrobial drugs designed to kill or inhibit the growth of the pathogenic bacteria. Veterinarians may use antimicrobial drug characteristics, such as physiochemical properties (e.g., lipid solubility), mechanisms of action, and effects on in vitro bacterial growth (e.g., bacteriostatic, bactericidal, peak-dependent, time-dependent), to help make a decision about which drug to use and how to use it (regimen: dose, route, frequency, duration, withdrawal time). While these characteristics may add to the discussion and provide pieces of evidence, the ultimate and most convincing evidence is clinical efficacy. For the treatment of bovine respiratory disease, there is considerable good quality published evidence for the efficacy of a number of antimicrobials, as exemplified in the table below. These drugs, all approved in the U.S. for BRD, span the spectrum of antimicrobials, including lipid-soluble and water-soluble, peak-dependent and time-dependent, and bacteriostatic and bactericidal. Therefore, using drug characteristics to make drug decisions for respiratory disease does not address the real questions related to how well the drug works. With this many drugs approved for the treatment and control of respiratory disease, how does one make a decision about which drug to use, and equally important, how to use it?

Drug selection

Drugs can be selected by using the principles of evidence-based veterinary medicine:

     1. Based on a need for information (a single animal or herd outbreak of respiratory disease), ask a clinically relevant question, including Patient, Intervention, Comparison, and Outcome (PICO).

          • The purpose of the clinical question is to focus your information search and to identify what you are really interested in answering. A vague clinical question will not result in good clinical decision-making.

          • Some examples of relevant clinical questions associated with the therapy of respiratory disease include: In high risk recently weaned calves that have just arrived at a feedlot, which drug product has been shown to decrease mortality? In pre-conditioned, recently-weaned calves headed for backgrounding, has metaphylaxis been shown to reduce costs of disease, including morbidity, mortality, and cost of gain? In dairy cows with signs of respiratory disease, has a particular drug product been show to be more effective at return to production?

          • Clinical questions can be asked about a current problem, or they can be anticipated: a plan to wean calves in the fall suggests a need for information on treating respiratory disease in these calves prior to the fall season.

     2. Using the clinical question, search for all the available published evidence to answer the question.

          • Typically, this step is searching in the published biomedical and animal science literature. While this may be a prolific source of data, in some cases, evidence may be lacking in the published literature and must be found elsewhere. Technical reports from animal health companies on the subject of bovine respiratory disease therapy abound. In addition, well-designed animal record systems with good acquisition of high quality data may also be a source of evidence, although the emphasis needs to be on "high quality data". Bad data is usually worse than no data at all. The use of anecdotal data or clinical impression is always fraught with opportunities for misinterpretation and should generally be avoided. Our minds are not designed to retain the best evidence but rather to retain the interesting, unusual, and exciting evidence. This is not to argue that we do not recognize patterns – that is the basis of many clinical diagnoses. However, patient outcomes are best analyzed via written record rather than recollection of clinical cases.