Literature DB >> 7015580

Serum drug concentrations in clinical perspective.

J Koch-Weser.   

Abstract

Determination of serum concentrations of certain drugs is becoming increasingly important for optimal patient care. These drugs include many antibiotics, several antiarrhythmics, cardiac glycosides, lithium, phenytoin, some other anticonvulsants, salicylates, and theophylline. Serum level determinations can also be useful for establishing the best individual dosage of benzodiazepines, phenothiazines, and tricyclic antidepressants. On the other hand, information about serum levels is not necessary or useful for many widely used drugs. In general, measurement of serum concentrations is valuable only for drugs whose dosage should be individualized and whose therapeutic and toxic actions are not adequately quantifiable by clinical endpoints. The serum concentration of the drug and of important active metabolites must be accurately measurable, the relation between their concentrations in the serum and the intensity of therapeutic and toxic effects during clinical use must have been clearly defined, and serum levels must always be knowledgeably interpreted in conjunction with careful clinical observation and judgment. Measurements of serum drug concentrations are most often useful during prophylactic drug therapy, in patients with major pharmacokinetic disturbances, and when patients show unusual and unexplained sensitivity or resistance to therapy with a drug.

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Year:  1981        PMID: 7015580

Source DB:  PubMed          Journal:  Ther Drug Monit        ISSN: 0163-4356            Impact factor:   3.681


  9 in total

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6.  Tobramycin serum level monitoring in young patients with normal renal function.

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Review 7.  Serum level monitoring of antibacterial drugs. A review.

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8.  Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.

Authors:  Hui Yu; Kui-Tao Mao; Jian-Yu Shi; Hua Huang; Zhi Chen; Kai Dong; Siu-Ming Yiu
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9.  TMFUF: a triple matrix factorization-based unified framework for predicting comprehensive drug-drug interactions of new drugs.

Authors:  Jian-Yu Shi; Hua Huang; Jia-Xin Li; Peng Lei; Yan-Ning Zhang; Kai Dong; Siu-Ming Yiu
Journal:  BMC Bioinformatics       Date:  2018-11-20       Impact factor: 3.169

  9 in total

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