Age-related distribution of longitudinal pre-strain in abdominal aorta with emphasis on forensic application
Jazyk angličtina Země Irsko Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
21794993
DOI
10.1016/j.forsciint.2011.07.007
PII: S0379-0738(11)00322-7
Knihovny.cz E-zdroje
- MeSH
- aorta abdominalis patologie MeSH
- aterosklerotický plát patologie MeSH
- ateroskleróza patologie MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mechanický stres * MeSH
- regresní analýza MeSH
- soudní patologie MeSH
- stárnutí fyziologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
It is a well-known fact that the length of an artery in situ and the length of an excised artery differs. Retraction of blood vessels is usually observed. This pre-tension plays crucial role in arterial biomechanics. It augments an artery wall load-bearing capacity. This paper presents the longitudinal pre-strain of the human aorta as an index of human age. The length of abdominal aortas was measured during autopsies before and after segment resection. The longitudinal pre-strain was calculated in 130 donors; 100 male and 30 female bodies. The pre-strain was defined as the ratio between in situ length and the length after the excision. The mean pre-strain was found to be 1.18±0.10 for male and 1.14±0.10 for female sample (mean±standard deviation). The age in the male group was 41.6±15.9 years; and 47.7±17.7 years in the female group. Statistical analysis revealed the correlation coefficient between age and pre-strain r=-0.821 and r=-0.839 in male and female group, respectively. The analysis also confirmed close correlation between aortic circumference and age; and between circumference and pre-strain. Linear and power law regression equations were employed and prediction intervals were computed. The power law estimates the age more accurately than linear one model. Nevertheless, especially for small values of the pre-strain (aged individuals) the linear model can be advantageous.
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