Search Results (32)

Background/Objectives: The factors contributing to residual atherosclerotic cardiovascular disease (ASCVD) risk in individuals are not fully understood, but knowledge of the specific type of dyslipoproteinemia may help further refine risk assessment. We developed a novel phenotyping and risk assessment system that may be applied automatically using standard lipid panel parameters. Methods: NHANES data collected from 37,056 individuals during 1999–2018 were used to develop a three-dimensional dyslipidemia phenotype classification system. ARIC data from 14,632 individuals were used to train and validate the risk model. Three-dimensional Cartesian coordinates were converted to spherical coordinates, which were used as features in a logistic regression model that provides a probability of ASCVD. UK Biobank data from 354,344 individuals were used to further validate and test the model. Results: Nine lipidemia phenotypes were defined based on the concentrations of HDLC, non-HDLC and TG. These phenotypes were related to the prevalence of metabolic syndrome, pooled cohort equation (PCE) score and ASCVD-free survival. A logistic regression model including age, sex and the spherical coordinates of the phenotype provided a composite risk score with predictive accuracy comparable to that of the PCEs. Conclusions: We provided an example of how a multidimensional coordinate system may be used to define a novel lipoprotein phenotyping system to examine disease associations. When applied to an ASCVD risk model, the composite spherical coordinate risk marker, which can be fully automated, provided an F1 performance score almost as good as the PCEs, which requires other risk factors besides lipids. Full article

Background: The United Arab Emirates (UAE) faces a high burden of type 2 diabetes mellitus (T2DM) and its complications. While sodium-glucose cotransporter-2 inhibitors (SGLT2i) have demonstrated cardiorenal benefits in clinical trials, real-world evidence on their association with calculated cardiovascular risk in Middle Eastern populations remains limited. This study evaluated the long-term real-world outcomes associated with SGLT2i use in Emirati patients with T2DM. Methods: We conducted a retrospective observational study of patients with T2DM initiated on SGLT2i (empagliflozin, dapagliflozin, or canagliflozin) at Tawam Hospital, UAE, between 1 January 2018 and 31 December 2018. Patients were followed for up to 5 years. Primary outcomes included changes in glycated hemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), and body mass index (BMI). A key secondary outcome was the change in 10-year atherosclerotic cardiovascular disease (ASCVD) risk, calculated using the ACC/AHA Pooled Cohort Equations. Results: We included 185 patients (mean age 57 ± 12 years, 56.2% female), with 107 (57.8%) receiving empagliflozin, 54 (29.2%) dapagliflozin, 11 (5.9%) canagliflozin, and 13 (7.0%) who switched between agents. Significant improvements were observed in HbA1c (8.7 ± 1.8% to 8.2 ± 1.9%, p < 0.001), while eGFR showed preservation of renal function with an annual decline of 1.1 mL/min/1.73 m². Among 120 patients eligible for ASCVD risk assessment (excluding 65 with established cardiovascular disease), the mean 10-year ASCVD risk decreased from 22.3 ± 5.3% at baseline to 19.3 ± 4.9% at 5 years (absolute reduction −3.0%, 95% CI −2.4 to −3.6%, p < 0.001). Serious adverse events were rare, including acute kidney injury (1.1%) and fractures (1.6%). No episodes of diabetic ketoacidosis or severe hypoglycemia were observed. Conclusions: In this real-world cohort from the UAE, SGLT2 inhibitor use was associated with sustained glycemic control, preserved renal function, and lower calculated 10-year cardiovascular risk over 5 years. These observational findings, noted in the context of comprehensive risk factor management, support the potential benefits of SGLT2i in high-risk Middle Eastern patients with T2DM, though prospective controlled studies are needed to confirm causality. Full article

Background/Objectives: As part of the human adaptation to dairy consumption, the presence of the rs4988235-T variant in the MCM6 gene primarily determines lactase persistence in adult European populations, increasing the expression of the lactase-encoding LCT gene. Carriers of the C/C variant are lactose intolerant, while carriers of the T/T or T/C variant have persistent lactase enzyme activity and are able to digest lactose in adulthood. While the association between lactose intolerance and increased cardiovascular risk (CVR) is well-known, the underlying causes have only been partly explored. The present study aimed to investigate the association of rs4988235 polymorphism with significant lipids affecting cardiovascular health and estimated CVR. Methods: The rs4988235 polymorphism was genotyped in 397 subjects from the general Hungarian population and 368 individuals from the Roma population. To characterize the overall lipid profile, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), high density lipoprotein cholesterol (HDL-C), apolipoprotein AI (ApoAI), and apolipoprotein B100 (ApoB100) levels were measured, and their ratios (TG/HDL-C, LDL-C/HDL-C, and ApoB100/ApoAI) were calculated. Cardiovascular risk was estimated using the Framingham Risk Score (FRS), Pooled Cohort Equations (PCE), Revised Pooled Cohort Equations (RPCE), and the Systematic Coronary Risk Evaluations (SCORE and SCORE2) algorithms. Adjusted linear and logistic regression analyses were performed, with p < 0.05 considered significant. Results: The Roma population had a significantly higher prevalence of the C/C genotype than the general population (65.5% vs. 40.3%, respectively). The results of the adjusted linear regression analysis showed a significant association between the C/C genotype and higher LDL-C level (B = 0.126, p = 0.047) and ApoB100 level (B = 0.046, p = 0.013), as well as a higher LDL-C/HDL-C ratio (B = 0.174, p = 0.021) and a higher ApoB100/ApoAI ratio (B = 0.045, p = 0.002), as well as a lower HDL-C level (B = −0.041, p = 0.049). The C/C genotype was also significantly associated with an increased cardiovascular risk (CVR) as estimated by the SCORE (B = 0.235, p = 0.034), SCORE2 (B = 0.414, p = 0.009), PCE (B = 0.536, p = 0.008), and RPCE (B = 0.289, p = 0.045) but not the FRS. After adjusting the statistical model further for ApoAI and ApoB100 levels, the significant correlation with the risk estimation algorithms disappeared (SCORE: p = 0.099; SCORE2: p = 0.283; PCE: p = 0.255; and RPCE: p = 0.370). Conclusions: Our results suggest that the C/C genotype of rs4988235 is associated with significantly higher ApoB100 and lower ApoAI levels and consequently higher ApoB100/ApoAI ratios, potentially contributing to an increased risk of cardiovascular disease. The results of the statistical analyses suggest that the association between lactose intolerant genotype and cardiovascular risk may be mediated indirectly via modification of the apolipoprotein profile. Full article

Background: Correct assessment of resting metabolic rate (RMR) is fundamental for estimating total energy expenditure in both clinical nutrition and sports sciences research. Various methods have been proposed for RMR determination, including predictive equations, isotopic dilution techniques, and indirect calorimetry. Over the past two decades, portable gas analyzers have emerged as promising alternatives, offering more accessible and cost-effective solutions for metabolic assessment. However, evidence regarding their validity remains inconsistent, particularly across diverse populations and varying metabolic assessment protocols. Methods: This systematic review was conducted in May 2025 using the PubMed, Web of Science, and EBSCO databases, following the PRISMA-DTA guidelines, and included observational studies with the objective of examining the available evidence regarding the validity of portable gas analyzers to determine RMR in humans. The methodological quality of each study was assessed using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results: From an initial pool of 230 studies, 16 met the eligibility criteria. The findings revealed notable variability in measurement validity among devices, mainly influenced by device model, population characteristics, and methodological factors. While portable analyzers such as FitMate and Q-NRG exhibited high validity, MedGem exhibited systematic biases, particularly in individuals with higher adiposity, leading to RMR overestimations. Conclusions: The main results demonstrated the critical need for rigorous validation of portable gas analyzers before their implementation in clinical and research settings to ensure their applicability across diverse populations and metabolic assessments. Full article

Cardiovascular disease remains the leading cause of morbidity and mortality worldwide, underscoring the importance of effective primary prevention strategies. Current total cardiovascular disease (CVD) risk assessment tools, such as the Systematic Coronary Risk Evaluation 2 (SCORE2) in Europe and the Pooled cohort equations (PCEs) and Predicting Risk of CVD EVENTs (PREVENT) in the USA, aim to identify individuals at high CVD risk and guide clinical decision-making in the primary prevention setting. Statin therapy reduces cardiovascular events and is recommended as the first step for individuals with estimated CVD risk above specific thresholds. Moreover, the presence of risk modifiers, as well as the detection of asymptomatic atherosclerosis, reclassifies low-moderate CVD risk individuals into higher risk categories, contributing to tailored therapeutic decisions in primary prevention. However, differences in the performance of the available CVD risk assessment tools, the recommended thresholds for intervention, and the treatment targets by scientific societies introduce considerable inconsistency to the statin therapy practices. In addition, physicians’ inertia and poor patients’ adherence contribute to inadequate dyslipidemia control rates. This narrative review examines the available evidence on the current most used CVD risk assessment tools and the respective lipid-lowering recommendations, and highlights the role of targeted screening for asymptomatic atherosclerosis in terms of individualized therapy for primary prevention. Full article

Background and Objectives: Cardiovascular diseases (CVDs), primarily driven by atherosclerosis, are the leading cause of mortality worldwide. In Saudi Arabia, the prevalence of atherosclerotic cardiovascular disease (ASCVD) poses a significant public health challenge. To estimate the 10-year ASCVD risk among adults in Al-Ahsa, Saudi Arabia, and identify prevalent risk factors such as age, gender, diabetes, hypertension, smoking, cholesterol, and preventive medication use. Materials and Methods: This cross-sectional study included 58,743 adults aged 35–75 years from the Al-Ahsa Health Cluster. The ASCVD risk was calculated using the ACC/AHA Pooled Cohort Equations. Statistical analysis identified predictors of high ASCVD risk. Results: Most participants (76.3%) were at low ASCVD risk (≤10%), 13.3% at borderline to intermediate risk (10–19%), and 10.4% at high risk (≥20%). Smoking, diabetes (39.6%), hypertension (40.8%), and male gender were key predictors of high ASCVD risk. High-density lipoprotein (HDL) was protective, reducing ASCVD risk by 3%. Among high-risk individuals, 29.7% used aspirin, and 58.3% used statins. Conclusions: While most adults in Al-Ahsa are at low ASCVD risk, a significant portion remains at elevated risk. Modifiable risk factors, including smoking, diabetes, and hypertension, combined with statin and aspirin adherence, highlight critical areas for targeted interventions to reduce the ASCVD burden in this population. Full article

Background: The utility of synthetic ECV, which does not require hematocrit values, has been reported; however, high-quality CT images are essential for accurate quantification. Second-generation Deep Learning Reconstruction (DLR) enables low-noise and high-resolution cardiac CT images. The aim of this study is to compare the differences among four reconstruction methods (hybrid iterative reconstruction (HIR), model-based iterative reconstruction (MBIR), DLR, and second-generation DLR) in the quantification of synthetic ECV. Methods: We retrospectively analyzed 80 patients who underwent cardiac CT scans, including late contrast-enhanced CT (derivation cohort: n = 40, age 71 ± 12 years, 24 males; validation cohort: n = 40, age 67 ± 11 years, 25 males). In the derivation cohort, a linear regression analysis was performed between the hematocrit values from blood tests and the CT values of the right atrial blood pool on non-contrast CT. In the validation cohort, synthetic hematocrit values were calculated using the linear regression equation and the right atrial CT values from non-contrast CT. The correlation and mean difference between synthetic ECV and laboratory ECV calculated from actual blood tests were assessed. Results: Synthetic ECV and laboratory ECV showed a high correlation across all four reconstruction methods (R ≥ 0.95, p < 0.001). The bias and limit of agreement (LOA) in the Bland–Altman plot were lowest with the second-generation DLR (hybrid IR: bias = −0.21, LOA: 3.16; MBIR: bias = −0.79, LOA: 2.81; DLR: bias = −1.87, LOA: 2.90; second-generation DLR: bias = −0.20, LOA: 2.35). Conclusions: Synthetic ECV using second-generation DLR demonstrated the lowest bias and LOA compared to laboratory ECV among the four reconstruction methods, suggesting that second-generation DLR enables more accurate quantification. Full article

Background and Objectives: In the context of female cardiovascular risk categorization, we aimed to assess the inter-model agreement between nine risk prediction models (RPM): the novel Predicting Risk of cardiovascular disease EVENTs (PREVENT) equation, assessing cardiovascular risk using SIGN, the Australian CVD risk score, the Framingham Risk Score for Hard Coronary Heart Disease (FRS-hCHD), the Multi-Ethnic Study of Atherosclerosis risk score, the Pooled Cohort Equation (PCE), the QRISK3 cardiovascular risk calculator, the Reynolds Risk Score, and Systematic Coronary Risk Evaluation-2 (SCORE2). Materials and Methods: A cross-sectional study was conducted on 6527 40–65-year-old women with diagnosed metabolic syndrome from a single tertiary university hospital in Lithuania. Cardiovascular risk was calculated using the nine RPMs, and the results were categorized into high-, intermediate-, and low-risk groups. Inter-model agreement was quantified using Cohen’s Kappa coefficients. Results: The study uncovered a significant diversity in risk categorization, with agreement on risk category by all models in only 1.98% of cases. The SCORE2 model primarily classified subjects as high-risk (68.15%), whereas the FRS-hCHD designated the majority as low-risk (94.42%). The range of Cohen’s Kappa coefficients (−0.09–0.64) reflects the spectrum of agreement between models. Notably, the PREVENT model demonstrated significant agreement with QRISK3 (κ = 0.55) and PCE (κ = 0.52) but was completely at odds with the SCORE2 (κ = −0.09). Conclusions: Cardiovascular RPM selection plays a pivotal role in influencing clinical decisions and managing patient care. The PREVENT model revealed balanced results, steering clear of the extremes seen in both SCORE2 and FRS-hCHD. The highest concordance was observed between the PREVENT model and both PCE and QRISK3 RPMs. Conversely, the SCORE2 model demonstrated consistently low or negative agreement with other models, highlighting its unique approach to risk categorization. These findings accentuate the need for additional research to assess the predictive accuracy of these models specifically among the Lithuanian female population. Full article

Background: The assessment of future risk of cardiovascular diseases (CVD) is strongly recommended for all asymptomatic adults without CVD history. Carotid atherosclerosis (CA) is a preclinical phenotype of CVDs. However, data on estimated future CVD risks with respect to preclinical atherosclerosis are limited. This community-based study aimed to assess the relationships between predicted CVD risks and CA. Methods: We enrolled 3908 subjects aged 40–74 years without CVD history and calculated their 10-year CVD risks using the Framingham Risk Score (FRS) and the Pooled Cohort Equations (PCE). Carotid plaque (CP) at the extracranial carotid arteries was determined by high-resolution B-mode ultrasonography and further classified into mild or advanced CA. Results: The means of FRS for CP-negative and mild and advanced CA were 9.0%, 14.4%, and 22.1%, respectively (p-value < 0.0001). The corresponding values for PCE score were 4.8%, 8.8%, and 15.0%, respectively (p-value < 0.0001). The odds ratios (ORs) of having CP per 5.0% increase in FRS and PCE score were 1.23 (95% CI, 1.19–1.28) and 1.36 (95% CI, 1.28–1.44), respectively. The corresponding values of having advanced CA were 1.24 (95% CI, 1.19–1.29) and 1.38 (95% CI, 1.30–1.48), respectively. Among the models of FRS or PCE plus other conventional CVD risk factors, the FRS + age model had the highest discrimination for the presence of CP (AUROC, 0.7533; 95% CI, 0.7375–0.7691) as well as for the presence of advanced CA (AUROC, 0.8034; 95% CI, 0.7835–0.8232). The calibration of the FRS + age models for the presences of CP and advanced CA was excellent (χ² = 8.45 [p = 0.49] and 10.49 [p = 0.31], respectively). Conclusions: Estimated future CVD risks were significantly correlated with risks of having CA. Both FRS and PCE had good discrimination for the presences of CP and advanced CA. Full article

The Depression, Anxiety, and Stress Scale-21 (DASS-21) has been used in various countries to assess the mental states of individuals. The objectives of this study were to validate the DASS-21 for use in Guam, an island that endures a high burden of mental health challenges, such as suicide, and examine the predictive impact of selected health indicators on DASS-21 variables. Three years of data (2017–2019) were pooled from the Pacific Islands Cohort of College Students (PICCS) study conducted annually at the University of Guam. In total, 726 students were included in the secondary data analysis. MPlus statistical software was used to perform a confirmatory factor analysis (CFA) for the validation and structural equation modeling (SEM) for the predictive modeling. The results from the CFA suggested an acceptable model fit (RMSEA: 0.073, CFI: 0.901, TLI: 0.889, RMR: 0.044), while SEM suggested that sleep quality and physical activity were significant predictors of DASS-21 variables. Therefore, the DASS-21 is a valid instrument for measuring depression, anxiety, and stress among emerging adults in Guam. Full article

Background: Numerous cardiovascular risk prediction models (RPM) have been developed, however, agreement studies between these models are scarce. We aimed to assess the inter-model agreement between eight RPMs: assessing cardiovascular risk using SIGN, the Australian CVD risk score (AusCVDRisk), the Framingham Risk Score for Hard Coronary Heart Disease, the Multi-Ethnic Study of Atherosclerosis risk score, the Pooled Cohort Equation (PCE), the QRISK3 cardiovascular risk calculator, the Reynolds Risk Score, and Systematic Coronary Risk Evaluation-2 (SCORE2). Methods: A cross-sectional study was conducted on 11,174 40–65-year-old individuals with diagnosed metabolic syndrome from a single tertiary university hospital in Lithuania. Cardiovascular risk was calculated using the eight RPMs, and the results were categorized into high, intermediate, and low-risk groups. Inter-model agreement was quantified using Cohen’s Kappa coefficients. Results: The study revealed significant heterogeneity in risk categorizations with only 1.49% of cases where all models agree on the risk category. SCORE2 predominantly categorized participants as high-risk (67.39%), while the PCE identified the majority as low-risk (62.03%). Cohen’s Kappa coefficients ranged from −0.09 to 0.64, indicating varying degrees of inter-model agreement. Conclusions: The choice of RPM can substantially influence clinical decision-making and patient management. The PCE and AusCVDRisk models exhibited the highest degree of agreement while the SCORE2 model consistently exhibited low agreement with other models. Full article

The hepatokine leukocyte cell-derived chemotaxin-2 (LECT2) promotes insulin resistance and hepatic fibrogenesis. In rodents, acute exercise suppresses circulating LECT2; however, human data are lacking. This study compared circulating LECT2 across populations and explored whether acute exercise impacts circulating LECT2. In Part A (n = 43), data were pooled from three experimental studies, regarding the following groups: healthy individuals, individuals with impaired glycaemic regulation (IGR), and individuals with type 2 diabetes and metabolic dysfunction-associated steatotic liver disease (T2DM-MASLD). Generalised linear models assessed differences in circulating LECT2 among groups. Part B (n = 20) involved exercise (30 min, 65% peak oxygen uptake) and control (resting) trials in the healthy and IGR groups. Circulating LECT2 was measured before and at 0, 1, 2 and 3 h post-exercise. Generalised estimating equations assessed differences in LECT2 responses to the trials among groups. In Part A, circulating LECT2 levels were 28.7% and 37.3% higher in the IGR and T2DM-MASLD groups, vs. healthy individuals (p ≤ 0.038), with BMI identified as the main predictor (p = 0.008). In Part B, average circulating LECT2 levels were 6.3% higher after exercise vs. in the control (p < 0.001), with similar responses between groups (p = 0.829). In the combined cohort, circulating LECT2 levels were elevated 1–3 h after exercise vs. control (p ≤ 0.009). LECT2 is elevated in people with dysglycaemia, with BMI as a leading predictor. Contrary to previous rodent work, acute exercise augments, rather than suppresses, circulating LECT2 in humans. Full article

Cardiovascular diseases (CVDs), such as arterial hypertension, myocardial infarction, stroke, heart failure, atrial fibrillation, etc., still represent the main cause of morbidity and mortality worldwide. They significantly modify the patients’ quality of life with a tremendous economic impact. It is well established that cardiovascular risk factors increase the probability of fatal and non-fatal cardiac events. These risk factors are classified into modifiable (smoking, arterial hypertension, hypercholesterolemia, low HDL cholesterol, diabetes, excessive alcohol consumption, high-fat and high-calorie diet, reduced physical activity) and non-modifiable (sex, age, family history, of previous cardiovascular disease). Hence, CVD prevention is based on early identification and management of modifiable risk factors whose impact on the CV outcome is now performed by the use of CV risk assessment models, such as the Framingham Risk Score, Pooled Cohort Equations, or the SCORE2. However, in recent years, emerging, non-traditional factors (metabolic and non-metabolic) seem to significantly affect this assessment. In this article, we aim at defining these emerging factors and describe the potential mechanisms by which they might contribute to the development of CVD. Full article

This cross-sectional study aimed to investigate the association between non-alcoholic fatty liver disease (NAFLD) and atherosclerotic cardiovascular disease (ASCVD), a global public health concern. A total of 9044 out of 10,104 adults from Guangzhou, China, were included in the analysis. We utilized the fatty liver index (FLI), a noninvasive indicator of NAFLD, and the pooled cohort equations (PCE) based on the 2013 ACC/AHA Guideline, the China-PAR model, and the Framingham Risk Score to assess the 10-year ASCVD risk. The results demonstrated a significant association between FLI and 10-year ASCVD risk (p < 0.001). Adjusted for age, individuals with high FLI (≥60) had an odds ratio of 3.91 (95% CI 2.52–6.08) compared to those with low FLI (<30). These findings persisted after adjusting for metabolic indicators. Notably, this association was consistently observed across all three risk prediction models: the PCE model, the China-PAR model, and the Framingham Risk Score. In conclusion, our study provides evidence supporting FLI as a reliable indicator of increased 10-year ASCVD risk in Chinese NAFLD patients. FLI serves as a valuable marker for early detection of ASCVD, highlighting its potential in clinical practice for risk assessment and prevention strategies. Full article

Background: The risk of developing atherosclerotic cardiovascular disease (ASCVD) is unknown for subjects with both gallstones and renal stones, nor is it known whether there is a difference in the risk between gallstones and renal stones. This study aimed to determine the risk relationship between gallstones and renal stones and the risk of ASCVD in a male population. Methods: We recruited 6371 eligible males aged 40 to 79 years old who did not have a documented ASCVD history. The ten-year ASCVD risk was calculated using the pooled cohort equations developed by the American College of Cardiology (ACC) and the American Heart Association (AHA). The ASCVD risk score was classified as a low risk (<7.5%), an intermediate risk (7.5% to 19.9%), or a high risk (≥20%). The diagnosis of gallstones and renal stones was established based on the results of abdominal sonography. Results: Both gallstones and renal stones were associated with a high level of intermediate risk (OR = 3.21, 95% CI = 1.89–5.49, p < 0.001) and high risk (OR = 3.01, 95% CI = 1.48–6.12, p < 0.001), compared to individuals with no stones at all, after adjusting for the effects of other clinical variables. The possession of gallstones was associated with a higher level of high ASCVD risk (OR = 1.84, 95% CI = 1.31–2.59, p < 0.05) than that of renal stones. Conclusions: The ASCVD risk was higher for males with gallstones than for those with renal stones. Men with both types of stones faced a risk of ASCVD that was three times higher than that of men without stones. Full article