Linked Life Data

8135302

Source:http://linkedlifedata.com/resource/pubmed/id/8135302

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1994-4-18
pubmed:abstractText
In an effort to identify features indicative of underlying bipolarity within the unipolar relatives of bipolar probands, we compared unipolar relatives of bipolars with unipolar relatives of unipolars. Using data from the Collaborative Study of the Psychobiology of Depression, we compared a number of demographic and clinical features individually, and then developed a logistic regression model for the differences found. Unipolar relatives of bipolars were somewhat more likely to be male and to have subthreshold bipolar features, and less likely to have panic symptoms. In addition, they had a small but significant decrease in the number of depressive symptoms and a large decrease in all treatment indicators. A multiple logistic regression model for these differences was highly significant, but had limited ability to discriminate between the two groups. These differences are not large enough to effectively discriminate between the groups for the purposes of classification. These particular results may result from a number of factors, most likely the choice of comparison group. Nonetheless, the work demonstrates a potential method for the construction of caseness indices for use in genetic studies of bipolar and other psychiatric disorders.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0148-7299
pubmed:author
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
48
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
192-9
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1993
pubmed:articleTitle
Unipolar relatives in bipolar pedigrees: a search for indicators of underlying bipolarity.
pubmed:affiliation
Program in Psychiatric Epidemiology, Harvard School of Public Health, Harvard Medical School, Boston, Massachusetts.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't