Linked Life Data

11202210

Source:http://linkedlifedata.com/resource/pubmed/id/11202210

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2001-1-30
pubmed:abstractText
Prediction models describing the response of various pathophysiological states to intervention can be of value in confirming a diagnosis, determining the prognosis and promoting compliance with treatment. The rigorous evaluation process of evidence-based medicine, used to assess any diagnostic test or therapeutic intervention, should be applied to studies reporting the development, validation and application of these prediction models. The models can provide only an estimate of the average effect to be expected, so the failure of an individual to exhibit an 'average' response does not necessarily imply a problem with that patient. Further development of the models is required to overcome inherent statistical problems and to allow greater applicability to the individual patient.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0334-018X
pubmed:author
pubmed:issnType
Print
pubmed:volume
13 Suppl 6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1359-64
pubmed:dateRevised
2008-11-27
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Evidence-based growth hormone therapy prediction models.
pubmed:affiliation
London Centre for Paediatric Endocrinology and Metabolism, Institute of Child Health, University College London, UK. p.hindmarsh@ucl.ac.uk
pubmed:publicationType
Journal Article, Review