|Title:||An International Model to Predict Recurrent Cardiovascular Disease||Authors:||Wilson, Peter W. F.
Agostino, Ralph, Sr.
Bhatt, Deepak L.
Pencina, Michael J.
Smith, Sidney C.
Alberts, Mark J.
Hirsch, Alan T.
Ohman, E. Magnus
|Keywords:||Acute coronary syndromes;Cardiovascular disease;Cerebrovascular disease/stroke;Coronary disease;Mortality;Peripheral vascular disease;Risk factors||Issue Date:||2012||Start page/Pages:||695-703.e1||Source:||The American Journal of Medicine||Abstract:||
BACKGROUND: Prediction models for cardiovascular events and cardiovascular death in patients with established cardiovascular disease are not generally available.
METHODS: Participants from the prospective REduction of Atherothrombosis for Continued Health (REACH) Registry provided a global outpatient population with known cardiovascular disease at entry. Cardiovascular prediction models were estimated from the 2-year follow-up data of 49,689 participants from around the world.
RESULTS: A developmental prediction model was estimated from 33,419 randomly selected participants (2394 cardiovascular events with 1029 cardiovascular deaths) from the pool of 49,689. The number of vascular beds with clinical disease, diabetes, smoking, low body mass index, history of atrial fibrillation, cardiac failure, and history of cardiovascular event(s) <1 year before baseline examination increased risk of a subsequent cardiovascular event. Statin (hazard ratio 0.75; 95% confidence interval, 0.69-0.82) and acetylsalicylic acid therapy (hazard ratio 0.90; 95% confidence interval, 0.83-0.99) also were significantly associated with reduced risk of cardiovascular events. The prediction model was validated in the remaining 16,270 REACH subjects (1172 cardiovascular events, 494 cardiovascular deaths). Risk of cardiovascular death was similarly estimated with the same set of risk factors. Simple algorithms were developed for prediction of overall cardiovascular events and for cardiovascular death.
CONCLUSIONS: This study establishes and validates a risk model to predict secondary cardiovascular events and cardiovascular death in outpatients with established atherothrombotic disease. Traditional risk factors, burden of disease, lack of treatment, and geographic location all are related to an increased risk of subsequent cardiovascular morbidity and cardiovascular mortality. (C) 2012 Elsevier Inc. All rights reserved. . The American Journal of Medicine (2012) 125, 695-703
acetylsalicylic acid; hydroxymethylglutaryl coenzyme A reductase inhibitor; aged; algorithm; article; body mass; cardiovascular disease; cardiovascular mortality; diabetes mellitus; female; hazard ratio; heart atrium fibrillation; heart failure; human; major clinical study; male; model; prediction model; priority journal; recurrent disease; risk factor; smoking
|Appears in Collections:||醫學系|
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