Comparison of Two Different Techniques Of Warfarin Dosing Determination - A Chemometrics Study.

A high prevalence of genetic polymorphisms increases sensitivity to warfarin therapy. In this study, we investigated 47 patients with effective long-term therapy by warfarin well-controlled by monitoring of International Normalised Ratio (INR). All patients were tested for gene polymorphisms VKORC1, CYP2C9*C2, and CYP2C9*C3, which were used for a dose calculation employing a program www.WarfarinDosing.org. The main goal was to investigate whether the warfarin doses determined by INR are in accordance with the doses calculated according to the pharmacogenetic algorithm. For this purpose, several chemometric tools, namely principal component analysis, cluster analysis, correlation analysis, correspondence analysis, Passing-Bablock regression, Bland-Altman method, descriptive statistics, and ANOVA were used. We also analysed the relationship between the dose of warfarin determined by INR and several constitutional and genetic factors. Statistically significant association between clinically optimized warfarin dose and indication for the treatment, age, and warfarin sensitivity determined by VKORC1, CYP2C9 gene polymorphisms were confirmed. Finally, we confirmed a good concordance between the INR determined warfarin doses and pharmacogenetic approach.

Development of a novel diagnostic algorithm to predict NASH in HCV-positive patients.

Non-alcoholic steato-hepatitis (NASH) is a severe disease characterised by liver inflammation and progressive hepatic fibrosis, which may progress to cirrhosis and hepatocellular carcinoma. Clinical evidence suggests that in hepatitis C virus patients steatosis and NASH are associated with faster fibrosis progression and hepatocellular carcinoma. A safe and reliable non-invasive diagnostic method to detect NASH at its early stages is still needed to prevent progression of the disease. We prospectively enrolled 91 hepatitis C virus-positive patients with histologically proven chronic liver disease: 77 patients were included in our study; of these, 10 had NASH. For each patient, various clinical and serological variables were collected. Different algorithms combining squamous cell carcinoma antigen-immunoglobulin-M (SCCA-IgM) levels with other common clinical data were created to provide the probability of having NASH. Our analysis revealed a statistically significant correlation between the histological presence of NASH and SCCA-IgM, insulin, homeostasis model assessment, haemoglobin, high-density lipoprotein and ferritin levels, and smoke. Compared to the use of a single marker, algorithms that combined four, six or seven variables identified NASH with higher accuracy. The best diagnostic performance was obtained with the logistic regression combination, which included all seven variables correlated with NASH. The combination of SCCA-IgM with common clinical data shows promising diagnostic performance for the detection of NASH in hepatitis C virus patients.

TRABECULAR BONE SCORE CHANGE DIFFERS WITH REGARD TO 25(OH)D LEVELS IN PATIENTS TREATED FOR ADULT-ONSET GROWTH HORMONE DEFICIENCY.

OBJECTIVE: Vitamin D is important in bone health. However, potential relationships of concomitant vitamin D deficiency with growth hormone deficiency (GHD) and the possibility that vitamin D inadequacy may alter the skeletal effects of growth hormone (GH) replacement therapy have not been adequately evaluated. METHODS: A prospective study was conducted in adult-onset GHD patients treated with recombinant human GH (rhGH) for 2 years. Trabecular bone score (TBS), lumbar spine (LS) bone mineral density (BMD), total hip (TH) BMD, and 25-hydroxyvitamin D (25(OH)D) levels were assessed at baseline and 24 months. The study cohort was divided based on 25(OH)D levels into 2 groups with the cutoff defined as the 50(th) percentile at each follow-up time point. RESULTS: Fifty-seven patients (29 males/28 females, mean age 34.4 years) were studied. After 24 months of GH replacement, LS BMD increased by 7.6% and TH BMD increased by 4.5% (both P<.05), with no difference according to 25(OH)D levels. TBS increased (+1.39 ± 3.6%) in those whose 25(OH)D was above the 50(th) percentile but decreased (-1.36 ± 5.6%, P<.05) in the cohort below the 50(th) percentile of 25(OH)D. Positive correlations were observed between baseline levels of IGF-1 and 25(OH)D (R = 0.37, P<.001) and between 24-month 25(OH)D and TBS (R = 0.25, P<.05). CONCLUSION: A differential effect of GH on TBS change was observed; TBS increased only in the cohort with 25(OH)D above the 50(th) percentile. Vitamin D sufficiency may be required to obtain optimal effects of GH treatment on bone quality, as assessed by TBS, in GHD adults. ABBREVIATIONS: AO-GHD = adult-onset GHD BMD = bone mineral density BMI = body mass index Ca = calcium CTx = carboxyterminal collagen crosslinks CV = coefficient of variation DXA = dual energy X-ray absorptiometry ECLIA = enzyme-labeled chemiluminescent immunometric assay GH = growth hormone GHD = growth hormone deficiency IGF-1 = insulin-like growth factor 1 LS BMD = lumbar spine BMD OC = osteocalcin 25(OH)D = 25-hydroxyvitamin D P = phosphorus PTH = parathyroid hormone rhGH = recombinant human GH TBS = trabecular bone score TH BMD = total hip BMD.

Characterization of Slovenian wines using Multidimensional data analysis from simple enological descriptors.

Determination of the product's origin is one of the primary requirements when certifying a wine's authenticity. Significant research has described the possibilities of predicting a wine's origin using efficient methods of wine components' analyses connected with multivariate data analysis. The main goal of this study was to examine the discrimination ability of simple enological descriptors for the classification of Slovenian red and white wine samples according to their varieties and geographical origins. Another task was to investigate the inter-relations available among descriptors such as relative density, content of total acids, non-volatile acids and volatile acids, ash, reducing sugars, sugar-free extract, SO2, ethanol, pH, and an important additional variable - the sensorial quality of the wine, using correlation analysis, principal component analysis (PCA), and cluster analysis (CLU). 739 red and white wine samples were scanned on a Wine Scan FT 120, from wave numbers 926 cm(-1) to 5012 cm(-1). The applied methods of linear discriminant analysis (LDA), general discriminant analysis (GDA), and artificial neural networks (ANN), demonstrated their power for authentication purposes.

Multivariate analysis and chemometric characterisation of textile wastewater streams.

The aim of this work was to design a quick and reliable method for the evaluation and classification of wastewater streams into treatable and non-treatable effluents for reuse/recycling. Different chemometric methods were used for this purpose handling the enormous amount of data, and additionally to find any hidden information, which would increase our knowledge and improve the classification. The data obtained from the processes description, together with the analytical results of measured parameters' characterising the wastewater of a particular process, enabled us to build a fast-decision model for separating different textile wastewater outlets. Altogether 49 wastewater samples from the textile finishing company were analysed, and 19 different physical chemical measurements were performed for each of them. The resulting classification model was aimed at an automated decision about the choice of treatment technologies or a prediction about the reusability of wastewaters within any textile finishing or other company having similar characteristics of wastewater streams.

Use of multidimensional data analysis for prediction of lung malignity.

Diagnosis of lung malignity can be predicted or confirmed not only according to the values of appropriate laboratory tests but also using multidimensional statistical analysis, which uses simultaneously all performed tests in the form of their optimal combination. The developed new way of diagnosis prediction is applied here to the results of laboratory analysis of lung tumor markers in serum as well as pleural effusion (exudate). Four laboratory tests were used and investigated in detail: carcinoembryonic antigen, CEA, in serum as well as in pleural exudate, and cytokeratin 19 fragment, CYFRA, in serum and exudate, as well. Each test represents one dimension in the investigated biomedical problem from the statistical point of view. Joint utilization of the performed laboratory tests is based on their optimized combination into a new statistical variable using a selected chemometric principle (principal component, discriminant function, or logit in logistic regression). This approach results in enhancement of diagnostic effectiveness applied for the specified purpose.