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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Canadian Journal of ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Canadian Journal of Cardiology
Article . 2011 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
https://pubmed.ncbi.nlm.nih.go...
Other literature type . 2011
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Framing Cardiovascular Disease Event Risk Prediction

Authors: James A, Stone;

Framing Cardiovascular Disease Event Risk Prediction

Abstract

Prediction about anything, as so aptly pointed out by the famous Danish physicist Niels Bohr, is not easy. Without knowledge of all the variables in an equation, their exact behaviour under all conditions, precisely the way each variable interacts with the others, and all of the plausible, potential outcomes of those interactions, predicting the outcomes of a system or (patho)physiological process involves as much art as science. Add to this already heady mixture of uncertainty the frequently chaotic (ie, nonlinear) behaviour of biological systems, and the prediction of clinical outcomes becomes very difficult indeed! And yet, a thing does not have to be perfect to be quite useful. Most current cardiovascular disease (CVD) prevention strategies and therapeutic interventions are far from perfect in the outcomes they deliver. However, their clinical utility in substantially reducing (recurrent) events and delaying death remains undeniably useful. With any therapeutic intervention, it is axiomatic that the greatest absolute improvements in outcomes are seen in those at the greatest risk of adverse events. However, the total number of adverse events prevented will virtually always accrue in lesser-risk populations, based on the simple reality of population demographics and the observation that the number of low-risk persons is usually comparatively large. Thus, any intervention or treatment aimed at reducing event rates within these lower-risk populations will require treating the largest proportion of the population at risk. And despite the clinical information clearly demonstrating the benefits of preventing individual CVD events in these lesser-risk populations, the relatively low overall population risk suggests that the number of individuals who must be treated, and the costs incurred in order to prevent a single adverse outcome, may be quite large. Furthermore, of critical but often underestimated clinical importance is the reality that in any low-risk population, the risks (and costs) of preventing an event may actually exceed the risks of not intervening. These clinical and economic realities are precisely the reason that Canadian CVD prevention guidelines recommend some

Keywords

Canada, Cardiovascular Diseases, Risk Factors, Practice Guidelines as Topic, Humans, Morbidity, Prognosis, Lipids, Risk Assessment, Hypolipidemic Agents

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Average
Top 10%
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