Source:http://linkedlifedata.com/resource/pubmed/id/17991210
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Predicate | Object |
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rdf:type | |
lifeskim:mentions | |
pubmed:issue |
6
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pubmed:dateCreated |
2007-11-9
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pubmed:abstractText |
The term "reverse epidemiology" is used to indicate that such surrogates of cardiovascular risk and metabolic syndrome as obesity, hypercholesterolemia and hypertension are paradoxically associated with greater survival in individuals with chronic disease states and wasting, including dialysis patients, in whom the short-term survival is the issue at hand. It is being debated whether the crossing curves of the obesity-mortality association in dialysis patients vs. the general population reflect the residual confounding that needs to be controlled away statistically, or whether they have biological plausibility in sharp contradistinction to the currently dominating Framingham paradigm. In the rush to define the crossing curves as statistical artifact and to dismiss the term "reverse epidemiology" as a misnomer, we may miss the opportunity to gain information housed in those crossing lines and may miss the bigger picture, i.e., how to improve longevity in dialysis patients. Even though some of the survival paradoxes in dialysis patients appear to fulfill the Hill's criteria of causation, there are still two major drawbacks: (1) convincing pathophysiologic pathways to link dialysis patient survival to obesity, fat accumulation, higher serum lipoprotein levels or slightly higher than normal blood pressure values are yet to be verified in animal and other scientifically sound models; and (2) randomized controlled trials need to show that nutritional interventions resulting in weight gain can lead to greater survival in dialysis patients. Studying the survival paradoxes may lead to a paradigm shift by establishing targets beyond the Framingham guidelines for populations with chronic disease states.
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pubmed:grant | |
pubmed:language |
eng
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pubmed:journal | |
pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:issn |
0894-0959
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pubmed:author | |
pubmed:issnType |
Print
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pubmed:volume |
20
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
593-601
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pubmed:dateRevised |
2011-9-22
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pubmed:meshHeading |
pubmed-meshheading:17991210-Cardiovascular Diseases,
pubmed-meshheading:17991210-Epidemiologic Factors,
pubmed-meshheading:17991210-Humans,
pubmed-meshheading:17991210-Kidney Failure, Chronic,
pubmed-meshheading:17991210-Models, Biological,
pubmed-meshheading:17991210-Obesity,
pubmed-meshheading:17991210-Renal Dialysis,
pubmed-meshheading:17991210-Risk Factors,
pubmed-meshheading:17991210-Survival Rate
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pubmed:articleTitle |
What is so bad about reverse epidemiology anyway?
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pubmed:affiliation |
Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, Los Angeles Biomedical Research Center at Harbor-UCLA, Torrance, USA. kamkal@ucla.edu
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pubmed:publicationType |
Journal Article,
Review,
Research Support, Non-U.S. Gov't,
Research Support, N.I.H., Extramural
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