Multivariate analysis applied to clinical analysis data
|Keywords:||Cluster analysis; Spearman correlation; Folate; Vitamin B12; Biomarkers; Kruskal-Wallis|
|Full text PDF:||http://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/12288|
Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial Folate, vitamin B12, iron and hemoglobin are essential for metabolic functions in the body. The deficiency of these can be the cause of several known pathologies and, untreated, can be responsible for severe morbidity and even death. The objective of this study is to characterize a population, residing in the metropolitan area of Lisbon and Setubal, concerning serum levels of folate, vitamin B12, iron and hemoglobin, as well as finding evidence of correlations between these parameters and illnesses, mainly cardiovascular, gastrointestinal, neurological and anemia. Clinical analysis data was collected and submitted to multivariate analysis. First the data was screened with Spearman correlation and Kruskal-Wallis analysis of variance to study correlations and variability between groups. To characterize the population, we used cluster analysis with Ward’s linkage method. Finally a sensitivity analysis was performed to strengthen the results. A positive correlation between iron with, ferritin and transferrin, and with hemoglobin was observed with the Spearman correlation. Kruskal-Wallis analysis of variance test showed significant differences between these biomarkers in persons aged 0 to 29, 30 to 59 and over 60 years old. Cluster analysis proved to be a useful tool when characterizing a population based on its biomarkers, showing evidence of low folate levels for the population in general, and hemoglobin levels below the reference values. Iron and vitamin B12 were within the reference range for most of the population. Low levels of the parameters were registered mainly in patients with cardiovascular, gastrointestinal, and neurological diseases and anemia.