Over the past decades, there has been a notable increase in the risk of Cardiovascular Disease (CVD), even among younger individuals. Policymakers and the health community have revised CVD prevention programs to include younger people in order to take these new circumstances into account. A variety of CVD risk assessment tools have been developed in the past years with the aim of identifying potential CVD candidates at the population level; however, they can hardly discriminate against younger individuals at high risk of CVD.Therefore, in addition to the traditional 10-year CVD risk assessment, lifetime CVD risk assessment has recently been recommended by the American Heart Association/American College of Cardiology and the European Society of Cardiology prevention guidelines, particularly for young individuals. Methodologically, the benefits of these lifetime prediction models are the incorporation of left truncation observed in survival curves and the risk of competing events which are not considered equivalent in the common survival analysis. Thus, lifetime risk data are easily understandable and can be utilized as a risk communication tool for Public Health surveillance. However, given the peculiarities behind these estimates, structural harmonization should be conducted in order to create a sex-, race-specific tool that is sensitive to accurately identifying individuals who are at high risk of CVD. In this review manuscript, we present the most commonly used lifetime CVD risk tools, elucidate several methodological and critical points, their limitations, and the rationale behind their integration into everyday clinical practice.

Background Type 2 diabetes mellitus (T2DM) often coexists with hypertension, significantly increasing cardiovascular risks. Lifestyle modification counseling has shown promise in managing T2DM and its comorbidities. However, the optimal frequency and structure of counseling for blood pressure control remain uncertain. Our study examines the best approach for managing blood pressure in T2DM patients by comparing the outcomes of two counseling strategies: a single session and periodic counseling over time. Methodology A total of 110 diabetic patients were enrolled, with 52 patients in each group after loss to follow-up. A randomized controlled trial compared one-time counseling (control) to six months of periodic counseling (intervention) on lifestyle modification. A weighing machine, stadiometer, 24-hour dietary recall, food frequency questionnaire, biochemical blood sugar level analysis, and telephonic follow-up were the essential tools used. The data were analyzed using SPSS version 24.0 (IBM Corp., Armonk, NY, USA), employing descriptive statistics, including frequencies, percentages, graphs, mean, and standard deviation. Statistical significance at the 5% level was tested using probability (p) calculations. The Kolmogorov-Smirnov test confirmed normal distribution (p > 0.05). Parametric tests, specifically independent t-tests, were used for between-group comparisons of continuous variables, while categorical variables were analyzed using the chi-square test or Fisher\'s exact test. Intragroup comparisons over time employed repeated-measures analysis of variance for continuous variables. Changes within groups after six months were assessed using paired t-tests. All statistical analyses adhered to a significance level of p < 0.05. Results The gender distribution at baseline was similar between the control (55.8% male, 44.2% female) and intervention (46.2% male, 53.8% female) groups, with no significant differences (p = 0.327). The mean weight was 66.67 ± 11.51 kg in the control group and 67.14 ± 11.19 kg in the intervention group (p = 0.835), and the body mass index was 25.61 ± 4.09 kg/m² and 26.29 ± 6.01 kg/m², respectively (p = 0.503). Clinical parameters such as fasting blood sugar, postprandial blood sugar, glycosylated hemoglobin, and blood pressure showed no significant differences between the control and intervention groups at baseline (p > 0.05). After six months, the intervention group exhibited a trend toward lower blood pressure compared to the control group, but the differences were not statistically significant. The mean systolic blood pressure was 132.15 ± 14.867 mmHg in the control group and 129.15 ± 9.123 mmHg in the intervention group (p = 0.218). Changes in blood pressure over the six-month period showed significant decreases within the intervention group, while changes in the control group did not reach statistical significance. The mean difference in systolic blood pressure in the intervention group was 5.54 ± 9.77 mmHg (p = 0.0001), indicating a notable reduction, while the control group had a smaller and statistically insignificant increase of 2.308 ± 9.388 mmHg (p = 0.082). Conclusions This study addresses a significant gap in the literature by comparing the efficacy of one-time vs. periodic counseling in T2DM management. While periodic counseling shows promise in improving diastolic blood pressure, further research is needed to understand its nuanced effects and optimize lifestyle interventions for T2DM patients.

OBJECTIVE: Cardiovascular diseases are the leading cause of mortality worldwide, originating in the first decades of life. A better understanding of their early determinants would allow for better prevention. This study aimed to evaluate the impact of nutritional and activity-related characteristics during adolescence on young adult cardiovascular risk factors.
METHODS: The Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study included adolescents (aged 12.5-17.5 years) in 10 European centres. Four centres designed a nested cohort including 236 participants who were reassessed as young adults (21-32 years). Food consumption was evaluated by dietary recalls, physical activity by accelerometers, physical fitness using physical tests and nutritional knowledge by questionnaires. Cardiovascular health was assessed by Pathobiological Determinants of Atherosclerosis in Youth (PDAY) Study risk scores and its components. Factors associated with cardiovascular risk were identified using a multivariable regression model.
RESULTS: Higher Diet Quality Index (DQI, P = 0.012) and nutritional knowledge (P = 0.015) were significantly associated with lower modified PDAY risk scores. Ultra-processed foods were associated with a lower non-high-density lipoprotein (non-HDL) cholesterol (P = 0.003), whereas DQI (P = 0.014) and Planetary Health Diet Index (P = 0.016) were associated with a higher HDL cholesterol. Higher DQI was also related to a lower body mass index (BMI, P = 0.006). In addition, cardiorespiratory fitness was related to a lower BMI (P = 0.004).
CONCLUSIONS: Nutritional knowledge, diet quality and adherence to a sustainable diet in adolescence decrease cardiovascular risk in adulthood, whereas ultra-processed food consumption increases risk. These factors appear as targeted prevention tools for promoting a healthier adolescent lifestyle to decrease long-term cardiovascular risk.
BACKGROUND: Clinicaltrials.gov NCT02899416.

OBJECTIVE: This post-hoc analysis explored the semaglutide effects on eGFR slope by baseline glycemic control, blood pressure (BP), body mass index (BMI), and albuminuria status in people with type 2 diabetes and high cardiovascular risk.
METHODS: Pooled SUSTAIN 6 and PIONEER 6 data were analyzed for change in estimated glomerular filtration (eGFR) slope by baseline HbA1c (<8%/≥8%; <64 mmol/mol/≥64 mmol/mol), systolic BP (<140/90 mmHg/≥140/90 mmHg), and BMI (<30 kg/m2/≥30 kg/m2). SUSTAIN 6 data were analyzed by baseline urinary albumin: creatinine ratio (UACR; <30/30 - 300/>300 mg/g).
RESULTS: The estimated absolute treatment differences (ETD) overall in eGFR slope [95% confidence intervals] favored semaglutide versus placebo in the pooled analysis (0.59 [0.29;0.89] mL/min/1.73m2/year) and in SUSTAIN 6 (0.60 [0.24;0.96] mL/min/1.73m2/year); the absolute benefit was consistent across all HbA1c, BP, BMI, and UACR subgroups (all p-interaction > 0.5).
CONCLUSIONS: A clinically meaningful reduction in risk of chronic kidney disease progression was observed with semaglutide versus placebo regardless of HbA1c, BP, BMI, and UACR levels.

暂无摘要。

暂无摘要。

暂无摘要。

暂无摘要。

暂无摘要。

暂无摘要。