AustralieFrV1, PascalFrancis, Curation, bibRecord, 004C98

An International Model to Predict Recurrent Cardiovascular Disease

Identifieur interne : 004C98 ( PascalFrancis/Curation ); précédent : 004C97; suivant : 004C99

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 :

The American journal of medicine [ 0002-9343 ] ; 2012.

RBID : Pascal:12-0310574

Descripteurs français

Pascal (Inist)
- International, Monde, Modèle, Prédiction, Facteur prédictif, Récidive, Récidivant, Pathologie de l'appareil circulatoire, Médecine.
Wicri :
- topic : Médecine.

English descriptors

KwdEn :
- Cardiovascular disease, International, Medicine, Models, Prediction, Predictive factor, Recurrent, Relapse, World.

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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C01	`01`		`ENG`	@0 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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<author><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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<author><name sortKey="Goto, Shinya" sort="Goto, Shinya" uniqKey="Goto S" first="Shinya" last="Goto">Shinya Goto</name>
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<author><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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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">An International Model to Predict Recurrent Cardiovascular Disease</title>
<author><name sortKey="Wilson, Peter W F" sort="Wilson, Peter W F" uniqKey="Wilson P" first="Peter W. F." last="Wilson">Peter W. F. Wilson</name>
<affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Atlanta VA Medical Center and Cardiology Division, Emory University School of Medicine</s1>
<s2>Atlanta, Ga</s2>
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<author><name sortKey="D Agostino, Ralph" sort="D Agostino, Ralph" uniqKey="D Agostino R" first="Ralph" last="D'Agostino">Ralph D'Agostino</name>
<affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Statistics and Consulting Unit, Boston University</s1>
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<author><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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<author><name sortKey="Eagle, Kim" sort="Eagle, Kim" uniqKey="Eagle K" first="Kim" last="Eagle">Kim Eagle</name>
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<affiliation wicri:level="1"><inist:fA14 i1="06"><s1>University of Michigan Cardiovascular Center</s1>
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<author><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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<author><name sortKey="Smith, Sidney C" sort="Smith, Sidney C" uniqKey="Smith S" first="Sidney C." last="Smith">Sidney C. Smith</name>
<affiliation wicri:level="1"><inist:fA14 i1="08"><s1>University of North Carolina at Chapel Hill</s1>
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<country>États-Unis</country>
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<author><name sortKey="Alberts, Mark J" sort="Alberts, Mark J" uniqKey="Alberts M" first="Mark J." last="Alberts">Mark J. Alberts</name>
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</inist:fA14>
<country>États-Unis</country>
</affiliation>
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<author><name sortKey="Dallongeville, Jean" sort="Dallongeville, Jean" uniqKey="Dallongeville J" first="Jean" last="Dallongeville">Jean Dallongeville</name>
<affiliation wicri:level="1"><inist:fA14 i1="10"><s1>Institut Pasteur de Lille</s1>
<s2>Lille</s2>
<s3>FRA</s3>
<sZ>8 aut.</sZ>
</inist:fA14>
<country>France</country>
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<author><name sortKey="Goto, Shinya" sort="Goto, Shinya" uniqKey="Goto S" first="Shinya" last="Goto">Shinya Goto</name>
<affiliation wicri:level="1"><inist:fA14 i1="11"><s1>Department of Medicine, Tokai University School of Medicine</s1>
<s2>Kanagawa</s2>
<s3>JPN</s3>
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<author><name sortKey="Hirsch, Alan T" sort="Hirsch, Alan T" uniqKey="Hirsch A" first="Alan T." last="Hirsch">Alan T. Hirsch</name>
<affiliation wicri:level="1"><inist:fA14 i1="12"><s1>Division of Epidemiology and Community Health, University of Minnesota School of Public Health and Minneapolis Heart Institute Foundation</s1>
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<author><name sortKey="Liau, Chiau Suong" sort="Liau, Chiau Suong" uniqKey="Liau C" first="Chiau-Suong" last="Liau">Chiau-Suong Liau</name>
<affiliation wicri:level="1"><inist:fA14 i1="13"><s1>Department of Internal Medicine, National Taiwan University Hospital and School of Medicine</s1>
<s2>Taipei</s2>
<s3>TWN</s3>
<sZ>11 aut.</sZ>
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<author><name sortKey="Magnus Ohman, E" sort="Magnus Ohman, E" uniqKey="Magnus Ohman E" first="E." last="Magnus Ohman">E. Magnus Ohman</name>
<affiliation wicri:level="1"><inist:fA14 i1="14"><s1>Division of Cardiology, Duke University</s1>
<s2>Durham, NC</s2>
<s3>USA</s3>
<sZ>12 aut.</sZ>
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<country>États-Unis</country>
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<author><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>
</affiliation>
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<author><name sortKey="Reid, Christopher" sort="Reid, Christopher" uniqKey="Reid C" first="Christopher" last="Reid">Christopher Reid</name>
<affiliation wicri:level="1"><inist:fA14 i1="16"><s1>Monash University</s1>
<s2>Victoria</s2>
<s3>AUS</s3>
<sZ>14 aut.</sZ>
</inist:fA14>
<country>Australie</country>
</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="1"><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>
</affiliation>
</author>
<author><name sortKey="Steg, Gabriel" sort="Steg, Gabriel" uniqKey="Steg G" first="Gabriel" last="Steg">Gabriel Steg</name>
<affiliation wicri:level="1"><inist:fA14 i1="18"><s1>INSERM U-698 et Université Paris VII-Denis Diderot, Hôpital Bichat-Claude Bernard</s1>
<s2>Paris</s2>
<s3>FRA</s3>
<sZ>16 aut.</sZ>
</inist:fA14>
<country>France</country>
</affiliation>
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<series><title level="j" type="main">The American journal of medicine</title>
<title level="j" type="abbreviated">Am. j. med.</title>
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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Cardiovascular disease</term>
<term>International</term>
<term>Medicine</term>
<term>Models</term>
<term>Prediction</term>
<term>Predictive factor</term>
<term>Recurrent</term>
<term>Relapse</term>
<term>World</term>
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<term>Monde</term>
<term>Modèle</term>
<term>Prédiction</term>
<term>Facteur prédictif</term>
<term>Récidive</term>
<term>Récidivant</term>
<term>Pathologie de l'appareil circulatoire</term>
<term>Médecine</term>
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<front><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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<sZ>1 aut.</sZ>
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<fA14 i1="02"><s1>Statistics and Consulting Unit, Boston University</s1>
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<fA14 i1="03"><s1>VA Boston Healthcare System, Brigham & Women's Hospital, and Harvard Medical School</s1>
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<sZ>3 aut.</sZ>
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<fA14 i1="04"><s1>University of Michigan Cardiovascular Center</s1>
<s2>Ann Arbor</s2>
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<sZ>4 aut.</sZ>
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<sZ>5 aut.</sZ>
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<sZ>5 aut.</sZ>
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<sZ>9 aut.</sZ>
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<sZ>10 aut.</sZ>
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<sZ>13 aut.</sZ>
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An International Model to Predict Recurrent Cardiovascular Disease

An International Model to Predict Recurrent Cardiovascular Disease

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