Linked Life Data

2335329

Source:http://linkedlifedata.com/resource/pubmed/id/2335329

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1-2
pubmed:dateCreated
1990-6-13
pubmed:abstractText
The present study deals with the computation of linear and multilinear regression formulae for reconstruction of ulnar length and stature through eleven fregmentary measures pertaining to linear, transverse, sagittal and circumferential dimensions of the ulna bone. A total of 288 ulnae, belonging to 82 male and 62 female documented skeletons have been measured for this purpose. The data reveals a non-significant bilateral variation in the fragmentary measures of the ulna while the sex differences are highly significant at 1% level. Keeping this in view, separate regression equations have been formulated for both the sexes. The study further highlights that the upper shaft circumference is the best predictor of ulnar length among all the fragmentary measures while stature can best be reconstructed using the breadth of olecranon. However, the maximum length as a non-fragmentary measure provides the most accurate estimate. In order to increase the accuracy in prediction of ulnar length and stature, multiple regression equations have also be constructed and used.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0379-0738
pubmed:author
pubmed:issnType
Print
pubmed:volume
45
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
15-25
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
1990
pubmed:articleTitle
Use of regression analysis in reconstruction of maximum bone length and living stature from fragmentary measures of the ulna.
pubmed:affiliation
Medico-legal Institute, Gandhi Medical College, Bhopal (M.P.), India.
pubmed:publicationType
Journal Article