Journal Information
Vol. 30. Issue 7 - 8.
Pages 655-663 (July - August 2011)
Vol. 30. Issue 7 - 8.
Pages 655-663 (July - August 2011)
Artigo Original
Open Access
Predição do risco de evento cerebrovascular após um enfarte agudo do miocárdio
Prediction of cerebrovascular event risk following myocardial infarction
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Sérgio Barra
Corresponding author
sergioncbarra@gmail.com

Autor para correspondência.
, Rui Providência, Pedro Lourenço Gomes, Joana Silva, Luís Seca, José Nascimento, A.M. Leitão-Marques
Serviço de Cardiologia, Centro Hospitalar de Coimbra, Coimbra, Portugal
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Article information
Resumo
Introdução

Doentes com doença coronária (DC) têm risco aumentado de acidente vascular cerebral (AVC). O objectivo deste estudo foi analisar o poder prognóstico de determinadas variáveis clínicas e analíticas na predição do risco de evento cerebrovascular (CBV) após enfarte agudo do miocárdio (EAM).

Métodos

404 doentes consecutivos (idade média 68,1 ± 13,7, 63,5% do sexo masculino, 37,4% com diabetes mellitus [DM]) sem antecedentes de AVC admitidos com o diagnóstico de EAM e que sobreviveram ao internamento. Dados recolhidos: factores de risco cardiovascular (CV), glicemia na admissão (GlicAd), HbA1c, creatinina, níveis máximos de troponina I (MaxTrop), taxa de filtração glomerular (TFG) calculada pelas fórmulas MDRD e Cockcroft-Gault, GRACE score para mortalidade intra-hospitalar e aos 6 meses (MIH e M6M, respectivamente), Killip Class máximo (KCm) e extensão da coronariopatia. Os doentes tiveram alta em ritmo sinusal, foram seguidos por dois anos e cada variável avaliada como possível preditor de AVC ou acidente isquémico transitório (AIT).

Resultados

Durante o follow-up, 27 doentes foram admitidos por evento cerebrovascular. A presença de DM, hipertensão, dislipidemia e DC prévia, o tipo de EAM (STEMI versus NSTEMI) e a extensão da coronariopatia não ajudaram a prever o risco de AVC/AIT. As seguintes variáveis associaram-se a maior risco de AVC/AIT: TFG < 60ml/min/m2 (p=0,029, OR 2,65, IC95% 1,07-6,55); KCm > 1 (p = 0,025, OR 2,71, CI95% 1,10-6,69); GRACE MIH > 180 (p=0,001, OR 4,09, CI95% 1,64-10,22); GRACE M6M > 150 (p=0,001, OR 4,50, CI95% 1,80-6,27); GlicAd > 140mg/dL (p=0,001, OR 5,74, CI95% 1,87-17,58); MaxTrop > 42 ng/mL (p=0,032, OR 2,64, CI95% 1,06-6,59). Regressão Logística obteve um modelo com os preditores GRACE M6M > 150 (OR 3,26, p=0,014) e GlicAd > 7,7 mmol/L (OR 4,09, p=0,017) que se ajustou bem aos dados (Hosmer-Lemeshow: p=0,969).

Discussão/conclusões

Em doentes com EAM, varáveis habitualmente úteis na predição do risco de MIH, como GlicAd e função renal, insuficiência cardíaca aguda e o score de GRACE mostraram valor como preditores de AVC/AIT durante um follow-up de 2 anos. Enquanto um valor do Score de GRACE M6M > 150 e GlicAd > 7,7 mmol/L se assumiram como preditores independentes de AVC/AIT, os factores de risco CV, a presença de CAD prévia e a extensão da coronariopatia não acrescentaram valor preditivo. Este estudo reforça a necessidade de uma prevenção secundária ainda mais agressiva em doentes com GRACE e GlicAD na admissão mais altos e com maior grau de disfunção renal.

Palavras-chave:
Acidente vascular cerebral
Enfarte agudo do miocárdio
Predição de risco
Eventos vasculares
Abstract
Introduction

Patients with coronary artery disease (CAD) are at increased risk of stroke. The aim of this study was to analyze the prognostic accuracy of selected clinical and laboratory variables in stroke risk prediction following discharge after myocardial infarction (MI).

Methods

We analyzed 404 consecutive patients (aged 68.1±13.7 years; 63.4% male; 37.4% with diabetes) without previous stroke who were discharged in sinus rhythm after being admitted for MI. The following data were collected: cardiovascular risk factors, admission blood glucose (BG), HbA1c, creatinine, peak troponin levels; glomerular filtration rate (GFR) by the MDRD formula; maximum Killip class; GRACE score for in-hospital and 6-month mortality; and extent of CAD. Patients were followed for two years and each variable was tested as a possible predictor of cerebrovascular events (stroke or transient ischemic attack [TIA]).

Results

During follow-up, 27 patients were admitted for stroke or TIA. The presence of diabetes, hypertension, dyslipidemia and previously known CAD, type of MI (STEMI vs NSTEMI) and extent of CAD did not predict cerebrovascular risk. The following variables were associated with higher stroke risk: GFR <60ml/min/m2 (p=0.029, OR 2.65, 95% CI 1.07-6.55); maximum Killip class >1 (p=0.025, OR 2.71, 95% CI 1.10-6.69); GRACE in-hospital mortality >180 (p=0.001, OR 4.09, 95% CI 1.64-10.22); admission BG >140 mg/dl (p=0.001, OR 5.74, 95% CI 1.87-17.58); GRACE 6-month mortality >150 (p=0.001, OR 4.50, 95% CI 1.80-6.27); and peak troponin >42ng/ml (p=0.032, OR 2.64, 95% CI 1.06-6.59). Logistic regression analysis produced a model with the predictors GRACE 6-month mortality >150 (OR 3.26; p=0.014) and admission BG >7.7mmol/l (OR 4.09; p=0.017) that fi tted the data well (Hosmer-Lemeshow: p=0.916).

Discussion/conclusions

In patients with MI, variables known to be predictors of in-hospital mortality, including admission BG, renal function, acute heart failure and GRACE score, were found to be useful predictors of stroke during 2-year follow-up. While both GRACE score for 6-month mortality >150 and admission BG >7.7 mmol/l were independent predictors of stroke, CV risk factors, previously known CAD, and extent of CAD assessed by coronary angiography did not improve stroke risk prediction. This study highlights the need for even more aggressive secondary prevention in patients most at risk.

Keywords:
Cerebrovascular disorders
Acute myocardial infarction
Risk prediction
Vascular events
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