BackgroundThe question about what risk function should be used in primary prevention remains unanswered. The Framingham Study proposed a new algorithm based on three key ideas: use of the four risk factors with the most weight (cholesterol, blood pressure, diabetes and smoking), prediction of overall cardiovascular diseases and incorporating the concept of vascular age. The objective of this study was to apply this new function in a cohort of the general non Anglo-Saxon population, with a 10-year follow-up to determine its validity.MethodsThe cohort was studied in 1992-94 and again in 2004-06. The sample comprised 959 randomly-selected persons, aged 30-74 years, who were representative of the population of Albacete, Spain. At the first examination cycle, needed data for the new function were collected and at the second examination, data on all events were recorded during the follow-up period. Discrimination was studied with ROC curves. Comparisons of prediction models and reality in tertiles (Hosmer-Lemeshow) were performed, and the individual survival functions were calculated.ResultsThe mean risks for women and men, respectively, were 11.3% and 19.7% and the areas under the ROC curve were 0.789 (95%CI, 0.716-0.863) and 0.780 (95%CI, 0.713-0.847) (P<0.001, both). Cardiovascular disease events occurred in the top risk tertiles. Of note were the negative predictive values in both sexes, and a good specificity in women (85.6%) and sensitivity in men (79.1%) when their risk for cardiovascular disease was high. This model overestimates the risk in older women and in middle-aged men. The cumulative probability of individual survival by tertiles was significant in both sexes (P<0.001).ConclusionsThe results support the proposal for “reclassification” of Framingham. This study, with a few exceptions, passed the test of discrimination and calibration in a random sample of the general population from southern Europe.

BackgroundObesity represents an important health problem and its association with cardiovascular risk factors is well-known. The aim of this work was to assess the correlation between obesity and mortality (both, all-cause mortality and the combined variable of all-cause mortality plus the appearance of a non-fatal first cardiovascular event) in a general population sample from the south-east of Spain.Materials and MethodsThis prospective cohort study used stratified and randomized two-stage sampling. Obesity [body mass index (BMI) ≥30 kg/m2] as a predictive variable of mortality and cardiovascular events was assessed after controlling for age, sex, cardiovascular disease history, high blood pressure, diabetes mellitus, hypercholesterolemia, high-density lipoprotein/triglycerides ratio, total cholesterol and smoking with the Cox regression model.ResultsThe mean follow-up time of the 1,248 participants was 10.6 years. The incidence of all-cause mortality during this period was 97 deaths for every 10,000 person/years (95% CI: 80–113) and the incidence of all-cause mortality+cardiovascular morbidity was 143 cases for every 10,000 person/years (95% CI: 124–163). A BMI ≥35 kg/m2 yielded a hazard ratio for all-cause mortality of 1.94 (95% CI: 1.11–3.42) in comparison to non-obese subjects (BMI <30 kg/m2). For the combination of cardiovascular morbidity plus all-cause mortality, a BMI ≥35 kg/m2 had a hazard ratio of 1.84 (95% CI: 1.15–2.93) compared to non-obese subjects.ConclusionsA BMI ≥35 kg/m2 is an important predictor of both overall mortality and of the combination of cardiovascular morbidity plus all-cause mortality.

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The current cardiovascular risk tables are based on a 10-year period and therefore, do not allow for predictions in the short or medium term. Thus, we are unable to take more aggressive therapeutic decisions when this risk is very high.To develop and validate a predictive model of cardiovascular disease (CVD), to enable calculation of risk in the short, medium and long term in the general population.Cohort study with 14 years of follow-up (1992–2006) was obtained through random sampling of 342,667 inhabitants in a Spanish region.Main outcome: time-to-CVD. The sample was randomly divided into 2 parts [823 (80%), construction; 227 (20%), validation]. A stepwise Cox model was constructed to determine which variables at baseline (age, sex, blood pressure, etc) were associated with CVD. The model was adapted to a points system and risk groups based on epidemiological criteria (sensitivity and specificity) were established. The risk associated with each score was calculated every 2 years up to a maximum of 14. The estimated model was validated by calculating the C-statistic and comparison between observed and expected events.In the construction sample, 76 patients experienced a CVD during the follow-up (82 cases per 10,000 person-years). Factors in the model included sex, diabetes, left ventricular hypertrophy, occupational physical activity, age, systolic blood pressure × heart rate, number of cigarettes, and total cholesterol. Validation yielded a C-statistic of 0.886 and the comparison between expected and observed events was not significant (P: 0.49–0.75).We constructed and validated a scoring system able to determine, with a very high discriminating power, which patients will develop a CVD in the short, medium, and long term (maximum 14 years). Validation studies are needed for the model constructed.