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Interpretation of data in patients with enteral and parenteral nutrition

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Tomova R., Tzaneva P., Nikolov M., Simeonov V.
Open Medicine
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2012
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vol. 7
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issue 6
720-728
EN
Multivariate statistical analysis is performed using clinical data characterizing the state of patients subject to early enteral (EEN) and pareneteral (PN) nutrition after major gastrointestinal surgery. Several patterns of linkage, between the clinical parameters for both groups of observed patients (with mixed (EEN+PN) and with parenteral nutrition only (TPN)), were found and interpreted. Discriminating indices for the internal grouping of patients were found related to the type of nutrition and the clinical status of the patients. It was found that the mixed (enteral and parenteral) nutrition offers better options for the overcoming of the metabolic stress after the surgery.
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Multivariate statistical assessment of polluted soils

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Simeonov V., Einax J., Tsakovski S., Kraft J.
Open Chemistry
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2005
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vol. 3
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issue 1
1-9
EN
This study deals with the application of several multivariate statistical methods (cluster analysis, principal components analysis, multiple regression on absolute principal components scores) for assessment of soil pollution by heavy metals. The sampling was performed in a heavily polluted region and the chemometric analysis revealed four latent factors, which describe 84.5 % of the total variance of the system, responsible for the data structure. These factors, whose identity was proved also by cluster analysis, were conditionally named “ore specific”, “metal industrial”, “cement industrial”, and “steel production” factors. Further, the contribution of each identified factor to the total pollution of the soil by each metal pollutant in consideration was determined.
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