Prolonged half-life of argatroban in patients with renal dysfunction and antiphospholipid antibody syndrome being treated for heparin-induced thrombocytopenia.

Argatroban is a direct thrombin inhibitor approved for the treatment of heparin-induced thrombocytopenia (HIT) type II. Argatroban is predominantly metabolized in the liver. It is widely believed that no dosage adjustment is required in patients with renal insufficiency, making it a preferred agent in patients on renal replacement therapy (Reddy and Grossman, Ann Pharm 2005;39:1601-1605). The elimination half-life of argatroban is approximately 50 min. Lupus anticoagulants can cause baseline elevation of the PTT and hence it is difficult to monitor the effects of anticoagulants such as heparin, lepirudin, or argatroban in patients with antiphospholipid antibody syndrome. Heparin levels may be used as an alternative for heparin monitoring but plasma levels of argatroban are not commercially available. A chromogenic antifactor IIa assay could be useful for monitoring argatroban in the presence of a lupus anticoagulant, but it is not widely available at present. We report a patient with end-stage renal disease, maintained on peritoneal dialysis with HIT, who demonstrated a markedly prolonged half-life when treated with argatroban despite the discontinuation of therapy. This case also demonstrates the lack of guidelines for the monitoring of argatroban therapy in the presence of an underlying lupus anticoagulant.

Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets.

We describe here the implementation of the statistical total correlation spectroscopy (STOCSY) analysis method for aiding the identification of potential biomarker molecules in metabonomic studies based on NMR spectroscopic data. STOCSY takes advantage of the multicollinearity of the intensity variables in a set of spectra (in this case 1H NMR spectra) to generate a pseudo-two-dimensional NMR spectrum that displays the correlation among the intensities of the various peaks across the whole sample. This method is not limited to the usual connectivities that are deducible from more standard two-dimensional NMR spectroscopic methods, such as TOCSY. Moreover, two or more molecules involved in the same pathway can also present high intermolecular correlations because of biological covariance or can even be anticorrelated. This combination of STOCSY with supervised pattern recognition and particularly orthogonal projection on latent structure-discriminant analysis (O-PLS-DA) offers a new powerful framework for analysis of metabonomic data. In a first step O-PLS-DA extracts the part of NMR spectra related to discrimination. This information is then cross-combined with the STOCSY results to help identify the molecules responsible for the metabolic variation. To illustrate the applicability of the method, it has been applied to 1H NMR spectra of urine from a metabonomic study of a model of insulin resistance based on the administration of a carbohydrate diet to three different mice strains (C57BL/6Oxjr, BALB/cOxjr, and 129S6/SvEvOxjr) in which a series of metabolites of biological importance can be conclusively assigned and identified by use of the STOCSY approach.