CARDIOVASCULAR RISK PROFILE IN A FAMILY HEALTH UNIT
DOI:
https://doi.org/10.58043/rphrc.38Keywords:
Lesão de órgão alvo (LOA), Fatores de risco cardiovascular (FRCV ), Tabagismo, Hipertensão, Score de risco de Framingham (FRS)Abstract
Background: Cardiovascular diseases (CVD) are the leading cause of death in Portugal and worldwide, accounting for 37% of all causes in the EU. Smoking plays a key role in the development of premature coronary disease. The Framingham Risk Score (FRS) developed by D ‘Agostino et al is used to stratify CVD risk as well as to identify at-risk individuals who are candidates for cardiovascular risk factors (CVRF) modification strategies. The aim of this study was to characterize the subpopulation of a USF regarding the prevalence of CVRF and Target Organ Damage (TOD), relating the clustering of the main CVRF with TOD using a statistical logistic regression (LR) model.
Methods: We performed a multivariate exploratory data analysis, based on a convenience sample (n=6290), anonymized of patients between 30 and 74 years old and with at least one appointment in 2018 at a USF.
Estimated overall risk of TOD was based on a composite of coronary heart disease (CHD), cerebrovascular disease (stroke, TIA), peripheral arterial disease (PAD) and heart failure (HF) according to the Framingham Heart Study criteria developed by Ralph B. D ‘Agostino et al in 2007. The RL model describes the association of TOD with major predictors of cardiovascular risk (i.e. age, sex, hypertension, smoking, dyslipidemia, DM2, obesity). Model calibration X2 was assessed by applying the statistic test Hosmer-Lemeshow goodness of fit (GOF) 8 df. To calculate the estimated CV risk, patients diagnosed with TOD were excluded, obtaining a sample with n=4360 cases.
Results: From a total of 6290 patients between 30 and 74 years old, the median age is 52 years old. Approximately 32.4% are hypertensive, 20.7% are active smokers and 6.7% have diagnosed TOD. Applying to the LR model, the GOF test, no statistically significant difference was found between the observed and predicted distribution of the model: X2=10.517, df=8, p-value=0.2306.
A one-year increase in age is associated with an 8% increase in the chance of having TOD. Being hypertensive more than doubles (OR=2.1) the chance of TOD and smoking status almost doubles the chance of TOD (OR=1.8). There was a difference between the mean age of smokers and non-smokers with TOD (Mann-Whitney U test, w=7899.5, p<0.00001), respectively 57.8 years and 64.4 years.
Conclusions: Applying the FRS to 10-year individual TOD risk estimation (i.e. CHD, stroke, PAD, and HF) by combining multiple CVRF`s will allow an individualized and more cost-effective therapeutic approach. The difference between the average age of smokers and non-smokers with TOD, respectively 57.8 years old and 64.4 years old, highlights the impact of smoking status on the onset of TOD especially in younger people. Thus, smoking cessation is a crucial measure in preventing/delaying TOD.
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References
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