Full-text resources of PSJD and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl
Preferences help
Polish version English version Language
enabled [disable] Abstract
Number of results

Results found: 1

Number of results on page
first rewind previous Page / 1 next fast forward last

Search results

Search:
in the keywords:  Biochemical parameters
help Sort By:

help Limit search:
first rewind previous Page / 1 next fast forward last
1
Content available remote

Determination and modelling of clinical laboratory data of healthy individuals and patients with end-stage renal failure

100%
Papaioannou A., Karamanis G., Rigas I., Spanos T., Roupa Z.
Open Medicine
|
2009
|
vol. 4
|
issue 1
37-48
EN
The analyses of 18 biochemical parameters (alanine aminotransferase, albumin, aspartate aminotransferase, calcium, cholesterol, chloride, creatinine, iron, glucose, γ- glutamyl transferase, alkaline phosphatase, phosphorus, potassium, sodium, total protein, triglycerides, uric acid, and urea nitrogen) were performed for 166 healthy individuals and 108 patients with end-stage renal failure (ESRF). The application of cluster analysis proved that there were points of similarity among all 18 biochemical parameters that formed major groups; these groups corresponded to the authors’ assumption of the existence of several overall patterns of biochemical parameters that may be termed “enzyme-specific”; “general health indicator”; “major component excretion”; “blood-specific indicator”; and “protein-specific”. These patterns also appear in the subsets of males and females that were obtained by separation of the general dataset. In addition, the performance of factor analysis similarly proved the validity of this assumption. This projection and modelling method indicated the existence of seven latent factors, which explained 70.05% of the total variance in the system for healthy individuals and more than 72% of the total variance in the system for patients with ESRF. All these results support the probability that a general health indicator could be constructed by taking into account the existing classification groups in the list of biochemical parameters.
first rewind previous Page / 1 next fast forward last
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.