Cardiomyocyte @entity1184 , oncosis, and autophagic vacuolization predict mortality in @entity1000 with advanced XXXX .

@entity1 @entity82 @entity712 @entity1184 @entity1000 @entity204 @entity9342
OBJECTIVES: The aim of this study was to identify the remodeling parameters cardiomyocyte (CM) damage or @entity204 , @entity1184 , and @entity82 that may be linked to outcomes in @entity1 with advanced @entity712 ( @entity712 ) in an effort to understand the pathogenic mechanisms of @entity712 that may support newer therapeutic modalities. BACKGROUND: There are controversial results on the influence of @entity82 , @entity1184 , and apoptosis on outcomes in @entity1 with @entity712 ; other modalities of cell damage have been poorly investigated. METHODS: In endomyocardial biopsy specimens from 100 @entity1 with @entity1000 and advanced @entity712 , CM diameter and the extent of @entity82 were determined by morphometry. The proportion of CMs with evidence of apoptosis, autophagic vacuolization (AuV), and oncosis was investigated by immunohistochemical methods and by terminal deoxynucleotidyl transferase-mediated @entity9342 nick end labeling. Those parameters were correlated with mortality in 3 years of follow-up by univariate analysis and with multivariate models incorporating the clinical variables more relevant to the prediction of outcomes. RESULTS: CM AuV occurred in 28 @entity1 (0.013    0.012%) and oncosis in 41 (0.109    0.139%). Nineteen @entity1 showed both markers. Apoptotic CM nuclei were observed in 3 @entity1 . In univariate analysis, CM diameter and AuV, either alone or associated with oncosis, were predictors of mortality. In multivariate analysis, CM diameter (hazard ratio: 1.37; 95% confidence interval: 1.12 to 1.68; p = 0.002) and simultaneous presence in the same endomyocardial biopsy specimen of AuV and oncosis (hazard ratio: 2.82; 95% confidence interval: 1.12 to 7.13; p = 0.028) were independent predictors of mortality. CONCLUSIONS: @entity1184 and AuV, especially in association with oncosis, are predictors of outcome in @entity1 with @entity1000 and severe @entity712 .
