Linked Life Data

6843631

Source:http://linkedlifedata.com/resource/pubmed/id/6843631

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
23
pubmed:dateCreated
1983-6-23
pubmed:abstractText
To develop a model that would forecast neurologic recovery after out-of-hospital cardiac arrest, we reviewed charts on 389 consecutive patients who were not awake on admission to the hospital after resuscitation from asystole or ventricular fibrillation. The outcome variable was "awakening," which was defined as having comprehensible speech or the ability to follow commands. Predictor variables that we considered included both preadmission and admission data. Using discriminant analysis, we derived models from a 60 per cent random sample of cases and tested the models on the remaining 40 per cent. We judged that the best model contained four variables from the admission examination: motor response, pupillary light response, spontaneous eye movements, and blood glucose (levels below 300 mg per deciliter predicted awakening). Overall correct classification was 80 per cent in the derivation sample and 77 per cent in the test sample. In a simplified form, the model's predictions of awakening had a sensitivity of 0.92, a specificity of 0.65, a positive predictive value of 0.80, and a negative predictive value of 0.84. This rule should be clinically useful in estimating the neurologic prognosis of patients resuscitated after out-of-hospital cardiac arrest.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0028-4793
pubmed:author
pubmed:issnType
Print
pubmed:day
9
pubmed:volume
308
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1378-82
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1983
pubmed:articleTitle
Prediction of awakening after out-of-hospital cardiac arrest.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't