التفاصيل البيبلوغرافية
| العنوان: |
Evaluating cardiovascular mortality in type 2 diabetes patients: an analysis based on competing risks Markov Chains and additive regression models. |
| المؤلفون: |
Rosato, Rosalba, Ciccone, G., Bo, S., Pagano, G. F., Merletti, F., Gregori, D. |
| المصدر: |
Journal of Evaluation in Clinical Practice; Jun2007, Vol. 13 Issue 3, p422-428, 7p, 4 Charts, 8 Graphs |
| مصطلحات موضوعية: |
TYPE 2 diabetes, CARDIOVASCULAR disease related mortality, MORTALITY, MARKOV processes, DIABETES |
| مستخلص: |
Rationale, aims and objectives Type 2 diabetes represents a condition significantly associated with increased cardiovascular mortality. The aims of the study are: (i) to estimate the cumulative incidence function for cause-specific mortality using Cox and Aalen model; (ii) to describe how the prediction of cardiovascular or other causes mortality changes for patients with different pattern of covariates; (iii) to show if different statistical methods may give different results. Methods Cox and Aalen additive regression model through the Markov chain approach, are used to estimate the cause-specific hazard for cardiovascular or other causes mortality in a cohort of 2865 type 2 diabetic patients without insulin treatment. The models are compared in the estimation of the risk of death for patients of different severity. Results For younger patients with a better covariates profile, the Cumulative Incidence Function estimated by Cox and Aalen model was almost the same; for patients with the worst covariates profile, models gave different results: at the end of follow-up cardiovascular mortality rate estimated by Cox and Aalen model was 0.26 [95% confidence interval (CI) = 0.21–0.31] and 0.14 (95% CI = 0.09–0.18). Conclusions Standard Cox and Aalen model capture the risk process for patients equally well with average profiles of co-morbidities. The Aalen model, in addition, is shown to be better at identifying cause-specific risk of death for patients with more severe clinical profiles. This result is relevant in the development of analytic tools for research and resource management within diabetes care. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
