[Luces y sombras de la Guía Europea esc-2021 de Prevención de la Enfermedad Cardiovascular en la Práctica Clínica.] / Lights and shadows of the 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice.

General practitioners see in their consultation a a significant number of patients at high vascular risk (VR). The European Guidelines for Cardiovascular Disease Prevention (2021) recommend a new risk classification and intervention strategies on on vascular risk factors (RF), with the aim of providing a shared decision-making recommendations between professionals and patients. In this document we present a critical analysis of these guidelines, offering possible solutions that can be implemented in Primary Care. It should be noted that there are positive aspects (lights) such as that the SCORE2 (from forty to sixty-nine years) and SCORE2-OP models (from seventy to eighty-nine years) are based on more current cohorts and measure cardiovascular risk in a more accurately manner. In addition, it is proposed to differentiate different risk thresholds according to age-groups. For sake of practicality, cardiovascular risk can be estimated using different websites with the new computer models. However, among the negative aspects (shadows), it seems to be add complexity implementing nine subgroups of subjects according to their age or level of risk, with a defined thresholds that could cause a substantial increase in the potential number of subjects susceptible to treatment without a clear evidence that supports it. In addition, two-step RF interventions could delay achievement of therapeutic goals, especially in very high-risk patients, diabetics, or patients with cardiovascular disease. Given these limitations, in this document we propose practical recommendations in order to simplify and facilitate the implementation of the guideline in primary care.

Los médicos de familia atienden un importante número de pacientes con alto riesgo vascular (RV). Las Guías Europeas de Prevención Cardiovascular (2021) proponen una nueva clasificación del riesgo y estrategias de intervención sobre los factores de riesgo (FRV), orientada a la toma de decisiones compartidas entre profesionales y pacientes. En el presente trabajo realizamos un análisis crítico de dichas guías, ofreciendo posibles soluciones prácticas para la Atención Primaria. Son destacables aspectos positivos (luces) que los modelos de RV SCORE2 (entre cuarenta y sesenta y nueve años) y SCORE2-OP (entre setenta y ochenta y nueve años) se basan en cohortes más actuales y miden con mayor exactitud y discriminación dicho riesgo. Además, se propone actuar diferenciadamente sobre el riesgo según la edad. Pragmáticamente, se presentan nuevos modelos informáticos para calcular el riesgo. Sin embargo, entre los aspectos negativos (sombras), parece colegirse una mayor dificultad de implementación al proponerse nueve subgrupos de sujetos según su edad o nivel de riesgo, con un dintel definitorio de alto RV subjetivo que podría ocasionar un incremento sustancial en el número de sujetos susceptibles de tratar sin una discriminación objetiva que lo sustente. Además, las intervenciones sobre los FRV en dos pasos podrían retrasar la consecución de objetivos terapéuticos, sobre todo en pacientes de muy alto riesgo, diabéticos o con enfermedad cardiovascular. Ante las dificultades que plantea la valoración del riesgo, proponemos unificar criterios y simplificar los mensajes claves para hacer unas guías más atractivas y que realmente ayuden a los profesionales de Atención Primaria en su práctica habitual.

Prevalence Rates of Arterial Hypertension According to the Threshold Criteria of 140/90 or 130/80 mmHg and Associated Cardiometabolic and Renal Factors: SIMETAP-HTN Study.

Background and objectives: Arterial hypertension (HTN) is the leading preventable cause of atherosclerotic cardiovascular diseases (ASCVD) and death from all causes. This study aimed to determine the prevalence rates of HTN diagnosed according to the threshold diagnostic criteria 130/80 mmHg and 140/90 mmHg, to compare blood pressure (BP) control, and to evaluate their associations with cardiovascular diseases and cardiometabolic and renal risk factors. Materials and Methods: This was a cross-sectional observational study conducted in primary care with a population-based random sample: 6588 people aged 18.0-102.8 years. Crude and adjusted prevalence rates of HTN were calculated. BP control was compared in HTN patients with and without ASCVD or chronic kidney disease (CKD). Their associations with cardiovascular diseases and cardiometabolic and renal factors were assessed using bivariate and multivariate analysis. Results: Adjusted prevalence rates of HTN diagnosed according to 140/90 and 130/90 criteria were 30.9% (32.9% male; 29.7% female) and 54.9% (63.2% male; 49.3% female), respectively. BP < 130/80 mmHg was achieved in 60.5% of HTN patients without ASCVD or CKD according to 140/90 criterion, and 65.5% according to 130/80 criterion. This BP-control was achieved in 70% of HTN patients with ASCVD and 71% with CKD, according to both criteria. Coronary heart disease (CHD), heart failure, atrial fibrillation, stroke, diabetes, prediabetes, low glomerular filtration rate (eGFR), hyperuricemia, hypercholesterolemia, obesity, overweight, and increased waist-to-height ratio were independently associated with HTN according to both criteria. Conclusions: Almost a third of the adult population has HTN according to the 140/90 criterion, and more than half according to the 130/90 criterion, with a higher prevalence in men. The main clinical conditions associated with HTN were heart failure, diabetes, CHD, low eGFR, and obesity.

Regional differences in the degree of glycaemic diabetes control in Spain and associated factors. IBERICAN study.

BACKGROUND AND OBJECTIVE: The prevalence of type 2 diabetes (T2D) is high, it is increasing and its degree of control seems to be improvable with important social and health consequences. The objective of this study is to determine the regional differences in the degree of glycaemic control of T2D in Spain and its associated factors. MATERIAL AND METHODS: Cross-sectional, multicentre, observational study in patients with T2D between 18 and 85 years of age selected by consecutive sampling between 2014 and 2018. The population was divided into four regions: north, centre, Mediterranean and south-east. The main variable was the value of glycated haemoglobin (HbA1c). Sociodemographic and clinical variables, presence or absence of other risk factors and treatment were recorded. RESULTS: A total of 1587 patients with T2D were analysed, with a mean age of 65.93 years (standard deviation [SD] 10.14); 54.5% were men; the mean duration of T2D was 8.63 years (SD 6.64) and the mean HbA1c value was 7.05%. Of the total, 59.8% had an HbA1c value ≤ 7% (north 59.5%, centre 59.5%, Mediterranean 60.6% and south-east 59.8%; P=.99). The factors for poor control were: in the north, duration of T2D and being sedentary; in the centre, duration of T2D and having a low income; in the Mediterranean, duration of T2D; and in the south-east, duration of T2D and having a low level of education or income. Overall, 76.2% of the subjects had hypertension, 75.1% dyslipidaemia, and 51.7% obesity, with significant differences between regions only being observed in the case of dyslipidaemia (P<.001). CONCLUSIONS: No differences were observed in the degree of diabetes control in the different regions, with the percentage of patients needing intensification in their control being high in all of them. The factors associated with poor control were the duration of the disease, a low level of education or income, and a sedentary lifestyle.

Clusters of Cardiovascular Risk Factors and Their Impact on the 20-Year Cardiovascular Risk in a General Population.

BACKGROUND: Clustering of cardiovascular risk factors (CVRFs) is extraordinarily common and is associated with an increased risk of cardiovascular disease (CVD). However, the particular impact of the sum of CVRFs on cardiovascular morbidity and mortality has not been sufficiently explored in Europe. OBJECTIVE: The aim of this study was to analyze the differences in survival-free probability of CVD in relation to the number of CVRFs in a Spanish population. METHODS: A prospective cohort study was conducted from 1992 to 2016 in a Spanish population that included 1144 subjects with no history of CVD (mean age, 46.7 years) drawn from the general population. We calculated the number of CVRFs for each subject (male sex, smoking, diabetes, hypertension, dyslipidemia, obesity, and left ventricular hypertrophy). Cardiovascular morbidity and mortality records were collected, and survival analysis was applied (competing risk models). RESULTS: There were 196 cardiovascular events (17.1%). The differences in total survival-free probability of cardiovascular morbidity and mortality of the different values of the sum of CVRFs were significant, increasing the risk of CVD (hazard ratio, 1.30; 95% confidence interval, 1.13-1.50) per each additional risk factor. CONCLUSION: Differences in survival-free probability of CVD in relation to the number of CVRFs present were statistically significant. Further studies are needed to corroborate our results.

Comparison Between Non-High-Density Lipoprotein Cholesterol and Low-Density Lipoprotein Cholesterol to Estimate Cardiovascular Risk Using a Multivariate Model.

BACKGROUND: Although studies exist comparing low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (HDL-C) in the development of cardiovascular disease (CVD), most have limitations in the mathematical models used to evaluate their prognostic power adjusted for the other risk factors (cardiovascular risk). OBJECTIVE: The aim of this study was to compare LDL-C and non-HDL-C in patients with CVD to determine whether both parameters predict CVD similarly. METHODS: A cohort of 1322 subjects drawn from the general population of a Spanish region was followed between 1992 and 2006. The outcome was time to CVD. Secondary variables were gender, age, hypertension, diabetes, personal history of CVD, current smoker, body mass index, LDL-C, and non-HDL-C. Two CVD prediction models were constructed with the secondary variables, with only the lipid parameter varying (non-HDL-C or LDL-C). In the construction of the models, the following were considered: multiple imputation, events per variable of 10 or more, and continuous predictors as powers. The validation was conducted by bootstrapping obtaining the distribution of the C statistic (discrimination) and the probabilities observed by smooth curves. These results were compared in both models using graphical and analytical testing. RESULTS: There were a total of 137 CVD events. The models showed no differences in the distributions of the C statistic (discrimination, P = .536) or in the calibration plot. CONCLUSIONS: In our population, LDL-C and non-HDL-C were equivalent at predicting CVD. More studies using this methodology are needed to confirm these results.

Construction and Validation of a 14-Year Cardiovascular Risk Score for Use in the General Population: The Puras-GEVA Chart.

UNLABELLED: 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.

Prognostic value of obesity on both overall mortality and cardiovascular disease in the general population.

BACKGROUND: Obesity 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 METHODS: This prospective cohort study used stratified and randomized two-stage sampling. Obesity [body mass index (BMI) ≥ 30 kg/m(2)] 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. RESULTS: The 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/m(2) 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/m(2)). For the combination of cardiovascular morbidity plus all-cause mortality, a BMI ≥ 35 kg/m(2) had a hazard ratio of 1.84 (95% CI: 1.15-2.93) compared to non-obese subjects. CONCLUSIONS: A BMI ≥ 35 kg/m(2) is an important predictor of both overall mortality and of the combination of cardiovascular morbidity plus all-cause mortality.

[Association of insulin resistance to different anthropometric measures and cardiovascular risk factors in a non-diabetic population]. / Relación de la resistencia a la insulina con diferentes medidas antropométricas y factores de riesgo cardiovascular en una población no diabética.

BACKGROUND AND OBJECTIVE: Insulin resistance (IR) has been directly related to obesity, particularly central obesity, and to other cardiovascular risk factors (CVRFs). Direct IR quantification is difficult in clinical practice, and indirect methods such as HOMA (homeostasis model assessment) have therefore been developed. The aim of this study was to assess the association of IR, as measured by HOMA, with different anthropometric measures and some CVRFs. MATERIALS AND METHODS: A cross-sectional, observational study was carried out in a general population sample older than 18 years in the province of Albacete, Spain. Sample size was 678 subjects. Participants completed a survey and underwent physical examinations and laboratory tests. Obesity measures included body mass index, waist perimeter, and sagittal abdominal diameter. Data analysis was performed using SPSS 15.0 software. RESULTS: Mean values of obesity measures were higher in males as compared to females and increased with age. IR prevalence was 39.8%. All assessed anthropometric measures, decreased HDL (high density lipoprotein) cholesterol and increased non-HDL cholesterol were independently associated to the risk of IR. CONCLUSIONS: A clear association exists between different anthropometrical measures and IR in the general population. There is also an association between lipid profile cahnges and the risk of experiencing IR.