Renal Dysfunction, Metabolic Syndrome and Cardiovascular Disease Mortality
Background. Renal disease is commonly described as a complication of metabolic syndrome (MetS) but some recent studies suggest that Chronic Kidney disease (CKD) may actually antecede MetS. Few studies have explored the predictive utility of co-clustering CKD with MetS for cardiovascular disease (CVD...
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| Format: | Article |
| Language: | English |
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Wiley
2010-01-01
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| Series: | Journal of Nutrition and Metabolism |
| Online Access: | http://dx.doi.org/10.1155/2010/167162 |
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| _version_ | 1832561443816341504 |
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| author | David Martins Chizobam Ani Deyu Pan Omolola Ogunyemi Keith Norris |
| author_facet | David Martins Chizobam Ani Deyu Pan Omolola Ogunyemi Keith Norris |
| author_sort | David Martins |
| collection | DOAJ |
| description | Background. Renal disease is commonly described as a complication of metabolic syndrome (MetS) but some recent studies suggest that Chronic Kidney disease (CKD) may actually antecede MetS. Few studies have explored the predictive utility of co-clustering CKD with MetS for cardiovascular disease (CVD) mortality. Methods. Data from a nationally representative sample of United States adults (NHANES) was utilized. A sample of 13115 non-pregnant individuals aged ≥35 years, with available follow-up mortality assessment was selected. Multivariable Cox Proportional hazard regression analysis techniques explored the relationship between co-clustered CKD, MetS and CVD mortality. Bayesian analysis techniques tested the predictive accuracy for CVD Mortality of two models using co-clustered MetS and CKD and MetS alone. Results. Co-clustering early and late CKD respectively resulted in statistically significant higher hazard for CVD mortality (HR = 1.80, CI = 1.45–2.23, and HR = 3.23, CI = 2.56–3.70) when compared with individuals with no MetS and no CKD. A model with early CKD and MetS has a higher predictive accuracy (72.0% versus 67.6%), area under the ROC (0.74 versus 0.66), and Cohen's kappa (0.38 versus 0.21) than that with MetS alone. Conclusion. The study findings suggest that the co-clustering of early CKD with MetS increases the accuracy of risk prediction for CVD mortality. |
| format | Article |
| id | doaj-art-9cb717777dfa4a379cf54e6b77e488e7 |
| institution | Kabale University |
| issn | 2090-0724 2090-0732 |
| language | English |
| publishDate | 2010-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Nutrition and Metabolism |
| spelling | doaj-art-9cb717777dfa4a379cf54e6b77e488e72025-02-03T01:25:02ZengWileyJournal of Nutrition and Metabolism2090-07242090-07322010-01-01201010.1155/2010/167162167162Renal Dysfunction, Metabolic Syndrome and Cardiovascular Disease MortalityDavid Martins0Chizobam Ani1Deyu Pan2Omolola Ogunyemi3Keith Norris4Department of Medicine, Charles Drew University of Medicine and Science, 1731 E 20th Street, Los Angeles, CA 90059, USADepartment of Medicine, Charles Drew University of Medicine and Science, 1731 E 20th Street, Los Angeles, CA 90059, USADepartment of Medicine, Charles Drew University of Medicine and Science, 1731 E 20th Street, Los Angeles, CA 90059, USADepartment of Medicine, Charles Drew University of Medicine and Science, 1731 E 20th Street, Los Angeles, CA 90059, USADepartment of Medicine, Charles Drew University of Medicine and Science, 1731 E 20th Street, Los Angeles, CA 90059, USABackground. Renal disease is commonly described as a complication of metabolic syndrome (MetS) but some recent studies suggest that Chronic Kidney disease (CKD) may actually antecede MetS. Few studies have explored the predictive utility of co-clustering CKD with MetS for cardiovascular disease (CVD) mortality. Methods. Data from a nationally representative sample of United States adults (NHANES) was utilized. A sample of 13115 non-pregnant individuals aged ≥35 years, with available follow-up mortality assessment was selected. Multivariable Cox Proportional hazard regression analysis techniques explored the relationship between co-clustered CKD, MetS and CVD mortality. Bayesian analysis techniques tested the predictive accuracy for CVD Mortality of two models using co-clustered MetS and CKD and MetS alone. Results. Co-clustering early and late CKD respectively resulted in statistically significant higher hazard for CVD mortality (HR = 1.80, CI = 1.45–2.23, and HR = 3.23, CI = 2.56–3.70) when compared with individuals with no MetS and no CKD. A model with early CKD and MetS has a higher predictive accuracy (72.0% versus 67.6%), area under the ROC (0.74 versus 0.66), and Cohen's kappa (0.38 versus 0.21) than that with MetS alone. Conclusion. The study findings suggest that the co-clustering of early CKD with MetS increases the accuracy of risk prediction for CVD mortality.http://dx.doi.org/10.1155/2010/167162 |
| spellingShingle | David Martins Chizobam Ani Deyu Pan Omolola Ogunyemi Keith Norris Renal Dysfunction, Metabolic Syndrome and Cardiovascular Disease Mortality Journal of Nutrition and Metabolism |
| title | Renal Dysfunction, Metabolic Syndrome and Cardiovascular Disease Mortality |
| title_full | Renal Dysfunction, Metabolic Syndrome and Cardiovascular Disease Mortality |
| title_fullStr | Renal Dysfunction, Metabolic Syndrome and Cardiovascular Disease Mortality |
| title_full_unstemmed | Renal Dysfunction, Metabolic Syndrome and Cardiovascular Disease Mortality |
| title_short | Renal Dysfunction, Metabolic Syndrome and Cardiovascular Disease Mortality |
| title_sort | renal dysfunction metabolic syndrome and cardiovascular disease mortality |
| url | http://dx.doi.org/10.1155/2010/167162 |
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