ArticleNuclear medicine communications2015
The early plasma concentration of 51Cr-EDTA in patients with cirrhosis and ascites: a comparison of three models.
Article in Nuclear medicine communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Comparison of the gamma-Pareto convolution with conventional methods of characterising metformin pharmacokinetics in dogs.Journal of pharmacokinetics and pharmacodynamics · 2020Pooled it
- A gamma-distribution convolution model ofEJNMMI physics · 2016Article
- Accurate and precise plasma clearance measurement using four 99mTc-DTPA plasma samples over 4 h.Nuclear medicine communications · 2016Article
- Time Varying Apparent Volume of Distribution and Drug Half-Lives Following Intravenous Bolus Injections.PloS one · 2016Article
- Glomerular Filtration Rate and Error Calculation Based on the Slope-Intercept Method with Chromium-51 Ethylenediaminetetraacetic Acid via a New Clinical Software: GFRcalc.Medical principles and practice : international journal of the Kuwait University, Health Science CentreArticle
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe aim of the study was to determine which of three two-parameter fitting functions (exponential, linear-log, and negative-power function of time) most accurately models early chromium-51-EDTA (51Cr-EDTA) plasma concentration data prior to 120 min in patients with cirrhosis and ascites and understand how these fitting functions affect the calculation of the area under the plasma concentration curve (AUC).
methodsA bolus, antecubital intravenous injection of 2.6 MBq of 51Cr-EDTA was given to 13 patients with cirrhosis and ascites. Up to 16 blood samples were drawn at time points ranging from 5 to 1440 min following injection. The concentration data prior to 120 min were used as reference data. Early time concentration values, estimated by fitting exponential, linear-log, and negative-power functions of time to the time samples at 120, 180, and 240 min, were then compared with reference data. The AUC was calculated for each patient using the exponential, Bröchner-Mortensen-corrected exponential, and linear-log functions, and these values were compared.
resultsThe withheld, observed plasma concentrations were (a) most accurately estimated by linear-log functions (Wilcoxon P=0.4548), (b) significantly underestimated by exponential functions (Wilcoxon P=0.0002), and (c) significantly overestimated by negative-power functions (Wilcoxon P=0.0034). The relative errors when ranked from best to worst were those for the linear-log (12.0%, 9.0%), exponential (22.9%, 14.2%), and negative-power (31.9%, 48.4%) functions of time, respectively (median, interquartile range). For each patient, the values for AUC calculated by the exponential function differed significantly (range=3.4-15.3%, median=8.3%) from those calculated by the corrected Bröchner-Mortensen exponential, as to a lesser extent did those values calculated using linear-log functions (range=0.4-8.0%, median=3.0%).
conclusionIn patients with cirrhosis, linear-log functions were significantly more accurate than exponential or power functions in estimating early time plasma concentrations (<120 min). However, the improved linear-log early time plasma concentration model does not provide as much correction to the total AUC as does the corrected Bröchner-Mortensen exponential method. This is likely because of the large contribution of late time data to the AUC, and future work is suggested to explore the late time fit problem.
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