Linked Life Data

14716612

Source:http://linkedlifedata.com/resource/pubmed/id/14716612

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2004-1-12
pubmed:abstractText
We used Kaplan-Meier 2-year survival analysis on CAST registry patients to estimate prognostic power of VPC frequency (> or =10/hr), presence of nonsustained ventricular tachycardia (NSVT), left ventricular ejection fraction, and presence of diabetes. We also used meta-analysis of reports in the literature to estimate prognostic power of signal-averaged electrocardiogram (SAECG) and electrophysiological tests (EPS) as well as VPCs, NSVT, and LVEF. Combined results from CAST analysis and literature meta-analysis yielded sensitivity and specificity for VPCs, NSVT, SAECG, LVEF, Diabetes, and EPS. The overall 2 year event rate for life-threatening arrhythmias or death was 7.88% for 51,144 cases in the combined CAST and literature data. After segmenting the population 21.3% were diabetic with a predicted 2 yr event rate of 13.5% and 78.7% were nondiabetic event rate of 6.4%. We defined low risk as <10% and high risk as > or =30%. Otherwise predicted event rate was classified as "unstratified." When all possible combination of noninvasive tests were applied, a prominent difference in the proportions of cases at risk between the diabetics and nondiabetics was revealed. When the unstratified cases were subsequently tested with EPS, the difference between the two groups was even more marked.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0022-0736
pubmed:author
pubmed:issnType
Print
pubmed:volume
36 Suppl
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
121-5
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Risk stratification in diabetic patients with a previous myocardial infarction.
pubmed:affiliation
Center for Information Technology, National Institutes of Health, Bethesda, MD, USA. jjbailey@helix.nih.gov
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Meta-Analysis