Linked Life Data

8879857

Source:http://linkedlifedata.com/resource/pubmed/id/8879857

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
1997-1-27
pubmed:abstractText
Predicting patient outcome in acute renal failure has become increasingly important as technology advances and ethical questions arise concerning life supporting therapies. We propose a new model which uses mortality as an endpoint and may be applied to the acute renal failure patient in the ICU setting who requires dialysis. This model is based on our ICU acute renal failure registry and has been prospectively validated for our institution. Our registry for the purposes of developing this model consists of data from 512 ICU patients requiring acute dialysis from 1988 until 1992. The model was developed by testing a variety of potential risk factors for mortality in a univariate analysis (Student's t-test and Chi square), and those factors found to be significant (p < 0.05) were subsequently tested in a multivariate fashion. The factors found significant included male gender, respiratory failure requiring intubation, hematologic dysfunction (platelet count < 50,000, leukocyte count < 2,500, or bleeding diathesis), bilirubin < 2.0 mg/dl, the absence of surgery, serum creatinine on the first dialysis treatment day, an increasing number of failed organ systems, and an increased BUN from the time of admission. Weights are assigned to each variable based on the odds ratio, and a score is generated with a range of 0 to 20. The initial data for the registry demonstrates good fit using the Hosmer and Lemeshow goodness-of-fit table. The model is next validated in 88 patients from 1993 through February 1994, then prospectively tested in 35 additional patients using a standard data collection form, and the model continues to demonstrate good fit. Although this model has been prospectively validated at our institution, this model or any such predictive model should be used with caution if not independently validated at any institution which proposes its use.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0301-0430
pubmed:author
pubmed:issnType
Print
pubmed:volume
46
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
206-11
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
Risk modeling in acute renal failure requiring dialysis: the introduction of a new model.
pubmed:affiliation
Department of Nephrology, Cleveland Clinic Foundation, Ohio 44195, USA.
pubmed:publicationType
Journal Article