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However, the immune stain used in the present research cannot cover all forms of chemically identified AGE.
Multivariate analysis identified age, gamma glutamyl transpeptidase (GGT), cholesterol, platelet count, and prothrombin time as independent predictors of fibrosis.
Multivariate analysis identified age and economic status as significant predictors of arsenicosis controlling for education and gender.
Our analysis identified age at admission, concurrent chronic systemic diseases and dementia, and walking disability before injury as risk factors predicting difficulties with discharge to home.
The regression model of any injury identified age, sex, race/ethnicity, marital status, diabetes, asthma, depressive symptoms, region, and MSA status to be independent predictors of injury recidivism.
Discussion Many significant prognostic factors were identified: Age, existence of hemodynamic failure with renal involvement, long operative time and the use of vasoactive drugs.
However, multivariate regression analysis also identified age (P = 0.027) as an independent variable with significant correlation to blood loss (Table 6).
These findings support previous studies that identified age as a significant predictive factor for transfusion in patients undergoing elective THA [6, 11, 12].
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Longitudinal work is required to establish the relationship between identified age-associated genes/pathways and aging-related diseases.
We identified age-related differences in the levels of the aforementioned proteins (e.g., VAChT and HACT/CHT in hippocampus).
Gene expression profiling of individual nematodes has identified age-related gene expression changes (Golden & Melov, 2004).
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