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Therapeutic Drug Monitoring in the Treatment of Tuberculosis: An Update

Overview of attention for article published in Drugs, May 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

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2 policy sources
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18 X users

Citations

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371 Dimensions

Readers on

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383 Mendeley
Title
Therapeutic Drug Monitoring in the Treatment of Tuberculosis: An Update
Published in
Drugs, May 2014
DOI 10.1007/s40265-014-0222-8
Pubmed ID
Authors

Abdullah Alsultan, Charles A. Peloquin

Abstract

Tuberculosis (TB) is the world's second leading infectious killer. Cases of multidrug-resistant (MDR-TB) and extremely drug-resistant (XDR-TB) have increased globally. Therapeutic drug monitoring (TDM) remains a standard clinical technique for using plasma drug concentrations to determine dose. For TB patients, TDM provides objective information for the clinician to make informed dosing decisions. Some patients are slow to respond to treatment, and TDM can shorten the time to response and to treatment completion. Normal plasma concentration ranges for the TB drugs have been defined. For practical reasons, only one or two samples are collected post-dose. A 2-h post-dose sample approximates the peak serum drug concentration (Cmax) for most TB drugs. Adding a 6-h sample allows the clinician to distinguish between delayed absorption and malabsorption. TDM requires that samples are promptly centrifuged, and that the serum is promptly harvested and frozen. Isoniazid and ethionamide, in particular, are not stable in human serum at room temperature. Rifampicin is stable for more than 6 h under these conditions. Since our 2002 review, several papers regarding TB drug pharmacokinetics, pharmacodynamics, and TDM have been published. Thus, we have better information regarding the concentrations required for effective TB therapy. In vitro and animal model data clearly show concentration responses for most TB drugs. Recent studies emphasize the importance of rifamycins and pyrazinamide as sterilizing agents. A strong argument can be made for maximizing patient exposure to these drugs, short of toxicity. Further, the very concept behind 'minimal inhibitory concentration' (MIC) implies that one should achieve concentrations above the minimum in order to maximize response. Some, but not all clinical data are consistent with the utility of this approach. The low ends of the TB drug normal ranges set reasonable 'floors' above which plasma concentrations should be maintained. Patients with diabetes and those infected with HIV have a particular risk for poor drug absorption, and for drug-drug interactions. Published guidelines typically describe interactions between two drugs, whereas the clinical situation often is considerably more complex. Under 'real-life' circumstances, TDM often is the best available tool for sorting out these multi-drug interactions, and for providing the patient safe and adequate doses. Plasma concentrations cannot explain all of the variability in patient responses to TB treatment, and cannot guarantee patient outcomes. However, combined with clinical and bacteriological data, TDM can be a decisive tool, allowing clinicians to successfully treat even the most complicated TB patients.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 383 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
South Africa 2 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
Philippines 1 <1%
Unknown 376 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 62 16%
Researcher 59 15%
Student > Master 51 13%
Student > Bachelor 32 8%
Other 23 6%
Other 75 20%
Unknown 81 21%
Readers by discipline Count As %
Medicine and Dentistry 114 30%
Pharmacology, Toxicology and Pharmaceutical Science 63 16%
Biochemistry, Genetics and Molecular Biology 27 7%
Agricultural and Biological Sciences 13 3%
Nursing and Health Professions 13 3%
Other 51 13%
Unknown 102 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 April 2023.
All research outputs
#2,025,049
of 25,350,078 outputs
Outputs from Drugs
#212
of 3,482 outputs
Outputs of similar age
#19,592
of 233,100 outputs
Outputs of similar age from Drugs
#3
of 36 outputs
Altmetric has tracked 25,350,078 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,482 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 233,100 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.