The risk of stroke and death in patients with aortic and mitral valve endocarditis

被引:139
作者
Cabell, CH
Pond, KK
Peterson, GE
Durack, DT
Corey, GR
Anderson, DJ
Ryan, T
Lukes, AS
Sexton, DJ
机构
[1] Becton Dickinson & Co, Franklin Lakes, NJ 07417 USA
[2] Vet Adm Med Ctr, Durham, NC USA
[3] Duke Clin Res Inst, Durham, NC USA
[4] Duke Univ, Sch Med, Dept Obstet & Gynecol, Durham, NC USA
[5] Duke Univ, Sch Med, Dept Med, Durham, NC 27706 USA
关键词
D O I
10.1067/mhj.2001.115790
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Previous studies have generated inconsistent results when attempting to define predictors of stroke and death in patients with endocarditis. We sought to examine the relationship between vegetation 2-dimensional size and stroke in those with infective endocarditis (IE) and to identify differences between aortic valve (AV) and mitral valve (MV) IE with regard to clinical characteristics, echocardiographic findings, stroke, and death. Methods We used the Duke Endocarditis Database to examine 145 episodes of definite IE involving the AV, n = 62, or MV, n = 83, A logistic regression model was developed to analyze important variables in predicting stroke, and a Cox proportional hazards model was used in predicting mortality. Results The mitral valve was infected in 57% of the cases. Vegetations were more commonly detected in patients with MV IE (92.8% vs 66. 1%, P =.001) and these MV vegetations were significantly larger (P < .05). Thirty-four of 145 episodes (23.4%) were complicated by stroke. MV IE was associated with a greater stroke rate, 32.5% versus 11.3% (P =.003). Strokes tended to occur early in the course of illness, particularly in MV IE, In the multivariable model, the independent predictors of stroke were MV IE (P =.04) and vegetation length (P =.03). Independent predictors of 1-year mortality were age (P =.02) and vegetation area (P =.048). Conclusion stroke is more common in patients with MV IE. Vegetation 2-dimensional size and characteristics are important predictors of stroke and mortality. These findings may lead to predictive models that allow physicians to identify high-risk patients who need aggressive treatment strategies to prevent long-term morbidity and mortality.
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页码:75 / 80
页数:6
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