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An International Model to Predict Recurrent Cardiovascular Disease

Identifieur interne : 001368 ( PascalFrancis/Checkpoint ); précédent : 001367; suivant : 001369

An International Model to Predict Recurrent Cardiovascular Disease

Auteurs : Peter W. F. Wilson [États-Unis] ; Ralph D'Agostino [États-Unis] ; Deepak L. Bhatt [États-Unis] ; Kim Eagle [États-Unis] ; Michael J. Pencina [États-Unis] ; Sidney C. Smith [États-Unis] ; Mark J. Alberts [États-Unis] ; Jean Dallongeville [France] ; Shinya Goto [Japon] ; Alan T. Hirsch [États-Unis] ; Chiau-Suong Liau [Taïwan] ; E. Magnus Ohman [États-Unis] ; Joachim Röther [Allemagne] ; Christopher Reid [Australie] ; Jean-Louis Mas [France] ; Gabriel Steg [France]

Source :

RBID : Pascal:12-0310574

Descripteurs français

English descriptors

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.


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Pascal:12-0310574

Le document en format XML

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<name sortKey="Steg, Gabriel" sort="Steg, Gabriel" uniqKey="Steg G" first="Gabriel" last="Steg">Gabriel Steg</name>
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<title xml:lang="en" level="a">An International Model to Predict Recurrent Cardiovascular Disease</title>
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<name sortKey="D Agostino, Ralph" sort="D Agostino, Ralph" uniqKey="D Agostino R" first="Ralph" last="D'Agostino">Ralph D'Agostino</name>
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<name sortKey="Bhatt, Deepak L" sort="Bhatt, Deepak L" uniqKey="Bhatt D" first="Deepak L." last="Bhatt">Deepak L. Bhatt</name>
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<s1>VA Boston Healthcare System, Brigham & Women's Hospital, and Harvard Medical School</s1>
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<name sortKey="Eagle, Kim" sort="Eagle, Kim" uniqKey="Eagle K" first="Kim" last="Eagle">Kim Eagle</name>
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<s1>University of Michigan Cardiovascular Center</s1>
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<country>États-Unis</country>
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<s1>University of Michigan Cardiovascular Center</s1>
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<name sortKey="Pencina, Michael J" sort="Pencina, Michael J" uniqKey="Pencina M" first="Michael J." last="Pencina">Michael J. Pencina</name>
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<s1>Statistics and Consulting Unit, Department of Biostatistics</s1>
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<s1>Statistics and Consulting Unit, Department of Biostatistics, Boston University</s1>
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<name sortKey="Smith, Sidney C" sort="Smith, Sidney C" uniqKey="Smith S" first="Sidney C." last="Smith">Sidney C. Smith</name>
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<name sortKey="Dallongeville, Jean" sort="Dallongeville, Jean" uniqKey="Dallongeville J" first="Jean" last="Dallongeville">Jean Dallongeville</name>
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<name sortKey="Goto, Shinya" sort="Goto, Shinya" uniqKey="Goto S" first="Shinya" last="Goto">Shinya Goto</name>
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<name sortKey="Hirsch, Alan T" sort="Hirsch, Alan T" uniqKey="Hirsch A" first="Alan T." last="Hirsch">Alan T. Hirsch</name>
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<name sortKey="Liau, Chiau Suong" sort="Liau, Chiau Suong" uniqKey="Liau C" first="Chiau-Suong" last="Liau">Chiau-Suong Liau</name>
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<name sortKey="Magnus Ohman, E" sort="Magnus Ohman, E" uniqKey="Magnus Ohman E" first="E." last="Magnus Ohman">E. Magnus Ohman</name>
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<country>États-Unis</country>
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<name sortKey="Rother, Joachim" sort="Rother, Joachim" uniqKey="Rother J" first="Joachim" last="Röther">Joachim Röther</name>
<affiliation wicri:level="1">
<inist:fA14 i1="15">
<s1>Department of Neurology, Klinikum Minden</s1>
<s2>Minden</s2>
<s3>DEU</s3>
<sZ>13 aut.</sZ>
</inist:fA14>
<country>Allemagne</country>
<wicri:noRegion>Minden</wicri:noRegion>
<wicri:noRegion>Klinikum Minden</wicri:noRegion>
<wicri:noRegion>Minden</wicri:noRegion>
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<name sortKey="Reid, Christopher" sort="Reid, Christopher" uniqKey="Reid C" first="Christopher" last="Reid">Christopher Reid</name>
<affiliation wicri:level="1">
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<s1>Monash University</s1>
<s2>Victoria</s2>
<s3>AUS</s3>
<sZ>14 aut.</sZ>
</inist:fA14>
<country>Australie</country>
<wicri:noRegion>Monash University</wicri:noRegion>
</affiliation>
</author>
<author>
<name sortKey="Mas, Jean Louis" sort="Mas, Jean Louis" uniqKey="Mas J" first="Jean-Louis" last="Mas">Jean-Louis Mas</name>
<affiliation wicri:level="3">
<inist:fA14 i1="17">
<s1>Service de Neurologie, Centre Raymond Garcin, Hôpital Sainte-Anne</s1>
<s2>Paris</s2>
<s3>FRA</s3>
<sZ>15 aut.</sZ>
</inist:fA14>
<country>France</country>
<placeName>
<region type="region">Île-de-France</region>
<region type="old region">Île-de-France</region>
<settlement type="city">Paris</settlement>
</placeName>
</affiliation>
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<author>
<name sortKey="Steg, Gabriel" sort="Steg, Gabriel" uniqKey="Steg G" first="Gabriel" last="Steg">Gabriel Steg</name>
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<s1>INSERM U-698 et Université Paris VII-Denis Diderot, Hôpital Bichat-Claude Bernard</s1>
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<sZ>16 aut.</sZ>
</inist:fA14>
<country>France</country>
<placeName>
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<div type="abstract" xml:lang="en">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.</div>
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