Cargando…
Non-fasting lipid profile determination in presumably healthy children: Impact on the assessment of lipid abnormalities
OBJECTIVE: Despite the common use of non-fasting measurements for lipid profile in children it remains unclear as to the extent non-fasting conditions have on laboratory results of lipids measurements. We aimed to assess the impact of non-fasting lipid profile on the occurrence of dyslipidemia in ch...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013146/ https://www.ncbi.nlm.nih.gov/pubmed/29927973 http://dx.doi.org/10.1371/journal.pone.0198433 |
Sumario: | OBJECTIVE: Despite the common use of non-fasting measurements for lipid profile in children it remains unclear as to the extent non-fasting conditions have on laboratory results of lipids measurements. We aimed to assess the impact of non-fasting lipid profile on the occurrence of dyslipidemia in children. MATERIALS AND METHODS: Basic lipid profile including: total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglycerides (TG), as well as small, dense-LDL-C (sd-LDL-C), apolipoprotein AI (ApoAI), apolipoprotein B (ApoB) and lipoprotein(a) [Lp(a)], were measured in 289 presumably healthy children aged 9–11 in both fasting and non-fasting condition. The clinical impact of non-fasting lipid profile was evaluated individually for each child with estimation of false positive (FP) and false negative (FN) results. RESULTS: The highest percentage of FP results in non-fasting condition was observed for TG (42.3%) being significantly higher when compared to FN results (p = 0.003). In contrast, the highest percentage of FN results in a non-fasting state were shown for LDL-C (14.3%), but the difference was statistically insignificant when compared to FP results. When comparing fasting and non-fasting lipid profile a number of significant differences was shown for: TG (p<0.001), HDL-C (p = 0.002) LDL-C (p<0.001) and ApoAI (p<0.001), respectively. The occurrence of dyslipidemia, recognized on the basis of non-fasting lipids was significantly higher (p = 0.010) when compared to fasting lipid profile. CONCLUSIONS: A higher occurrence of dyslipidemia, based on the measurement of non-fasting lipids in children, is suggestive of possible disorders in lipid metabolism. However, accurate identification of dyslipidemia by assessment of non-fasting lipids requires the establishment of appropriate cut-off values for children. |
---|