Diabetes mellitus is a major risk factor for cardiovascular (CV) events. Many algorithms have been devised to assess CV risk, some of which specific for diabetics. Most of them, however, can hardly be extrapolated to Mediterranean countries. AIM of this study was to analyze CV risk and the incidence of CV events in a local cohort of patients with type 2 diabetes. METHODS. Clinical charts of the Diabetes Clinics of Modena in the period 1991-1995 were analyzed. Patients aged 35-65 with type 2 diabetes and no previous CV disease were eligible. Global CV risk was computed according to Framingham, RISCARD, Progetto Cuore and UKPDS algorithms and compared with the actual rate of CV events over the following 10 years. RESULTS. 2416 patients were screened; 1532 of them (63.4%) were eligible on the basis of predefined criteria and completeness of data. In such population an absolute 10-yr risk rate of 14.6% was observed. When looking at the characteristics of the patients who developed a cardiovascular event compared to those who did not, we found a significant difference in the prevalence of risk factors as systolic blood pressure, age at visit, smoke, duration of diabetic disease and HbA1c. COPD and chronic heart failure also display a higher prevalence in patients with events, suggesting a possible role of these chronic conditions in developing cardiovascular disease. Interestingly, most of the subjects presenting with a CV event had a low to moderate risk estimate at the beginning; this was particularly evident with the Progetto Cuore algorithm. CONCLUSIONS. Estimation of CV risk is largely dependent on the algorithm adopted and on the baseline risk of the reference cohort. Equations designed for a specific population should be adopted. The overall performance of presently available functions is however low. Inclusion of additional risk parameters might hopefully increase the performance of such algorithms, which is presently clearly unsatisfactory. The algorithm derived from the present study will be utilized for a prospective evaluation of CV risk in our local cohort.
ESTIMATION OF CARDIOVASCULAR RISK IN TYPE 2 DIABETES / E., Pellegrini; Simonini, M. S.; M., Maurantonio; I. M., Giannico; D'Amico, Roberto; Ganazzi, Dorval; Carulli, Lucia; Loria, Paola; Bertolotti, Marco; Carulli, Nicola. - In: NMCD. NUTRITION METABOLISM AND CARDIOVASCULAR DISEASES. - ISSN 0939-4753. - STAMPA. - 18:(2008), pp. 54-54. (Intervento presentato al convegno XXII national congress of teh italian society for teh study of atherosclerosis tenutosi a Rome, Italy nel 19.11.2008).
ESTIMATION OF CARDIOVASCULAR RISK IN TYPE 2 DIABETES
D'AMICO, Roberto;GANAZZI, Dorval;CARULLI, Lucia;LORIA, Paola;BERTOLOTTI, Marco;CARULLI, Nicola
2008
Abstract
Diabetes mellitus is a major risk factor for cardiovascular (CV) events. Many algorithms have been devised to assess CV risk, some of which specific for diabetics. Most of them, however, can hardly be extrapolated to Mediterranean countries. AIM of this study was to analyze CV risk and the incidence of CV events in a local cohort of patients with type 2 diabetes. METHODS. Clinical charts of the Diabetes Clinics of Modena in the period 1991-1995 were analyzed. Patients aged 35-65 with type 2 diabetes and no previous CV disease were eligible. Global CV risk was computed according to Framingham, RISCARD, Progetto Cuore and UKPDS algorithms and compared with the actual rate of CV events over the following 10 years. RESULTS. 2416 patients were screened; 1532 of them (63.4%) were eligible on the basis of predefined criteria and completeness of data. In such population an absolute 10-yr risk rate of 14.6% was observed. When looking at the characteristics of the patients who developed a cardiovascular event compared to those who did not, we found a significant difference in the prevalence of risk factors as systolic blood pressure, age at visit, smoke, duration of diabetic disease and HbA1c. COPD and chronic heart failure also display a higher prevalence in patients with events, suggesting a possible role of these chronic conditions in developing cardiovascular disease. Interestingly, most of the subjects presenting with a CV event had a low to moderate risk estimate at the beginning; this was particularly evident with the Progetto Cuore algorithm. CONCLUSIONS. Estimation of CV risk is largely dependent on the algorithm adopted and on the baseline risk of the reference cohort. Equations designed for a specific population should be adopted. The overall performance of presently available functions is however low. Inclusion of additional risk parameters might hopefully increase the performance of such algorithms, which is presently clearly unsatisfactory. The algorithm derived from the present study will be utilized for a prospective evaluation of CV risk in our local cohort.
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