Pedro Marques-Vidal

Background: Conventional diagnostic markers, such as eGFR or albuminuria, often detect established late stages of kidney disease missing early adaptive changes. Acylcarnitines (ACs), intermediates of mitochondrial fatty acid oxidation, have been suggested as markers of metabolic dysfunction and impaired energy metabolism, which are important processes in early kidney injury. However, their role as prognostic biomarkers for early kidney disease remains unclear. Aim: To analyse ACs as an early prognostic biomarker for progression to kidney disease in an apparently healthy European population-based sample. Methods: Data from 1 960 apparently healthy adults in a population-based cohort in Lausanne, Switzerland. Incident chronic kidney disease (CKD) was defined as progression to eGFR90 mL/min/1.73 m² to eGFR 60-90 mL/min/1.73 m² during the follow-up period. Results: Over a median follow-up of 8.5 years, 53 participants (2.7%) developed CKD, and 365 participants (18.4%) developed eGFR trajectory. In multivariate analyses, long-chain ACs (Arachidonyl-) remained positively associated with incident CKD and their baseline standardized log-transformed concentrations AC levels were higher. Baseline levels of short-chain ACs (Butyryl- and Hydroxybutyryl-), long-chain ACs (Tetradecanedienoyl-, Hexadecenoyl-, Stearoyl- and Oleoyl-) were significantly higher in the participants who later developed eGFR trajectory. Conclusion: ACs were independently associated with both incident CKD and eGFR trajectory in healthy adults free from diabetes, obesity or cardiovascular disease. However, the findings of the current study cannot establish the clinical utility of ACs profiling as a prognostic marker for prognostic CKD and require confirmation in studies with sufficient events.

Background and Aims: Major adverse cardiac and cerebrovascular events (MACCE) are significant complications following percutaneous coronary intervention (PCI). Identifying the predictors of these events can aid in improving outcomes, especially in specific populations such as the Iranian cohort. This study aims to investigate the incidence and predictors of short‐ and long‐term MACCE after PCI in patients from the National Persian Registry of Cardiovascular Disease (N‐PROVE). Methods: We conducted a cohort study involving 1921 patients who underwent PCI for acute coronary syndrome at Razi Hospital, Birjand, Iran. Data on demographics, medical history, procedural details, and follow‐up outcomes were collected. The primary endpoint was the occurrence of MACCE, including all‐cause mortality, myocardial infarction (MI), cerebrovascular accident (CVA), and target‐vessel revascularization (TVR), at 1‐, 6‐, and 12‐months post‐PCI. Predictors of MACCE were identified using univariate and multivariate Cox proportional hazards models. Results: MACCE occurred in 8.5% of patients at 1 month, 13.7% at 6 months, and 17.9% at 12 months post‐PCI. Independent predictors of MACCE included age ≥ 75 years, female sex, diabetes mellitus (DM), multi‐vessel disease (MVD), and poor TIMI flow. Multivariate analysis confirmed DM (HR 1.52, 95% CI 1.07–2.23), 2VD (HR 1.59, 95% CI 1.05–2.42), 3VD (HR 1.55, 95% CI 1.01–2.75), and TIMI flow 0‐I (HR 2.31, 95% CI 1.53–3.49) as significant predictors. Conclusions: The study highlights key predictors of MACCE, particularly age, sex, DM, and TIMI flow. These findings underscore the need for tailored interventions for high‐risk groups, especially elderly patients and those with MVD, to improve long‐term outcomes following PCI.

Background and Aims: Despite the high burden of cardiovascular disease (CVD) in Latin America and the Caribbean (LAC), risk prediction models adapted for use in LAC populations remain limited. The aim of this study was to recalibrate the Systematic COronary Risk Evaluation 2 (SCORE2) risk models for estimating 10-year CVD risk in individuals without prior CVD or diabetes mellitus in LAC, resulting in the SCORE2 Latin America and the Caribbean (SCORE2-LAC) models. Methods: Sex-specific, competing risk-adjusted SCORE2 models were recalibrated to contemporary CVD incidence across four risk regions, defined by country-level age- and sex-standardized CVD mortality rates, using region-specific risk factor distributions. Cardiovascular disease incidence was estimated from CVD mortality data and ratios of the total first-to-fatal CVD events, derived from 40 237 152 individuals (1 261 329 CVD events). External validation included 132 512 individuals without prior CVD or diabetes from 11 cohorts across seven countries (3938 CVD events). Discrimination was assessed using Harrell’s C-index. Results: In the external validation datasets, the pooled C-index of SCORE2-LAC was .740 [95% confidence interval (CI) .716–.763], with cohort-specific C-indices ranging from .674 (95% CI .588–.761) to .789 (95% CI .747–.831). Estimated CVD risk varied several-fold across the four LAC risk regions. For a 50-year-old non-smoker with a systolic blood pressure of 140 mmHg, total cholesterol of 213 mg/dL (5.5 mmol/L), and HDL cholesterol of 50 mg/dL (1.3 mmol/L), the predicted risk ranged from 3% in low-risk countries to 10% in very-high-risk countries for women, and from 4% to 10% for men. Conclusions: The SCORE2-LAC models provide region-specific contemporary estimates of 10-year CVD risk in apparently healthy individuals, enabling identification of individuals at high CVD risk across LAC.

Dyslipidemia elevates the risk of metabolic disorders and cardiovascular disease (CVD). While various dietary and lifestyle factors contribute to dyslipidemia, healthier eating habits may decrease this risk. This longitudinal study investigated the association between dietary habits score (DHS) and the 9.9‐year risk of dyslipidemia among urban adults. A total of 1042 adults without dyslipidemia at baseline were enrolled, and 693 participants who completed follow‐up were included in the final analysis. Dietary habits were assessed in 2005–2006, and participants were followed for an average of 9.9 years. DHS was calculated for each participant by summing the hazard ratios (HRs) associated with individual dietary habits in relation to dyslipidemia risk, thereby generating a cumulative score reflecting overall dietary habits quality. A higher DHS indicates unhealthier dietary habits. The association between DHS and the incidence of dyslipidemia was analyzed using Cox regression. During the 9.9‐year follow‐up, the incidence of dyslipidemia was 65.8%. After adjustment for confounders, the incidence of dyslipidemia (HR; 95% CI) was found to be associated with poor weight management (HR = 1.68; 95% CI: 1.14–2.47), low salad consumption (HR = 2.46; 95% CI: 1.56–3.90), and frequent fast‐food intake (HR = 1.90; 95% CI: 1.08–3.34). Overall, individuals in the highest DHS quartile exhibited a greater risk of dyslipidemia (HR = 2.58; 95% CI: 1.50–4.43, p = 0.001) compared with the lowest quartile of DHS. The same positive association was found in males (HR = 3.56; 95% CI: 1.95–6.51, p = 0.034). The findings indicate a significant positive association between poor weight management, low salad consumption, frequent fast‐food intake, and higher DHS with the 9.9‐year incidence of dyslipidemia. Further large‐scale prospective studies are needed to validate these findings.

Background: Increased body mass index (BMI) is associated with increased medical costs, but no information is available for Switzerland. We investigated the association of individual BMI categories with healthcare use and healthcare expenditures. Methods: Data from an ongoing prospective, community-based study conducted in Lausanne, Switzerland. Information on healthcare use, type of insurance and deductible level were provided by the participants for period 2018–2021. Health expenditures were obtained from health insurers. Results: 1960 participants (64.5 ± 9.6 years, 50.4% women) had data on healthcare use. After multivariable adjustment on socioeconomic and health covariates, participants with obesity were less likely to use complementary medicines or over the counter drugs, odds ratio and (95% confidence interval): 0.74 (0.56–0.98) and 0.61 (0.44–0.85), respectively, while being more likely to be on polypharmacy [1.52 (1.05–2.20)] and benefitting from home care [2.25 (1.19–4.25)]. 907 participants (64.4 ± 9.4 years, 48.6% women) had data on health expenditures. BMI levels were positively associated with total health expenditures (median and [interquartile range]: 3740 [1717–7935], 2815 [666–6170] and 1680 [248–4975] CHF for obesity, overweight and normal weight, respectively, p < 0.001) and expenditures paid by insurance (3189 [820–7262], 2179 [0–5604] and 1019 [0–4205] CHF, respectively, p < 0.001). After multivariable adjustment, participants with obesity still presented higher total expenditures, while no difference was found for insurance-paid expenditures or participants with overweight. Conclusion: People with obesity have higher healthcare use and higher total health expenditures than people with normal weight.

Background: White matter hyperintensities (WMH) represent the most visible manifestation of cerebral small vessel disease and of white matter pathology more broadly, yet empirical evidence points to a brain tissue injury extending beyond radiologically detectable lesions on fluid-attenuated inversion recovery (FLAIR) MRI. We present RADAR-WMH (Relaxometry And Diffusion Analysis for Radiological WMH), a multicontrast MRI machine learning framework that characterises white matter pathology through tissue microstructural information rather than lesion contrast alone. Methods: RADAR-WMH was trained on quantitative relaxometry and diffusion-weighted MRI acquired in community-dwelling participants (mean age 59.6 years [SD 22.4], 60.8% women, n=148) using a LightGBM classifier integrating local, textural, and anatomical features at the voxel level. Biological validity was assessed through longitudinal analyses and associations with age, cardio-vascular risk, and cognitive performance in independent cohorts. Results: RADAR-WMH achieved segmentation performance comparable to state-of-the-art FLAIR-based approaches without requiring FLAIR or T1-weighted data. Mean diffusivity was the most influential feature for lesion classification. Beyond FLAIR-defined WMH, RADAR-WMH identified tissue pathology extending outside lesion borders characterised by myelin loss, axonal injury, and increased extracellular water. These microstructural signatures persisted over follow-up and showed stronger association with age, systolic blood pressure, and cognitive performance than corresponding tissue properties restricted to FLAIR-defined WMH extent. Conclusions: RADAR-WMH reveals a significant burden of biologically meaningful white matter injury that remains invisible to FLAIR-defined WMH segmentation. By capturing microstructural pathology linked to vascular risk, cognitive decline, and lesion evolution, RADAR-WMH may provide more sensitive markers of cerebral small vessel disease than FLAIR-visible WMH alone.

Introduction: Chronic kidney disease (CKD) is a growing public health challenge, yet impaired kidney function may substantially alter urinary biomarker profiles, complicating their interpretation. We aimed to investigate the associations between urinary element concentrations and prevalent CKD, and to explore whether impaired kidney function and altered urinary excretion may contribute to reverse causality in the interpretation of urinary biomarkers. Methods: We conducted a cross-sectional analysis of urinary element mixtures and prevalent CKD among 6,192 adults (51.7% female; mean age 52.4 ± 10.7 years). Associations between urinary element concentrations and prevalent CKD were evaluated using logistic regression, restricted cubic spline models, and three mixture modeling approaches, including Bayesian kernel machine regression, weighted quantile sum regression, and quantile g-computation. Results: Participants with CKD exhibited lower urinary concentrations of selenium, molybdenum, cadmium, mercury, lead, and thallium, whereas urinary zinc concentrations were higher. Non-linear associations were observed for several elements. Across multiple mixture models, higher combined urinary element concentrations were consistently associated with lower odds of prevalent CKD. Cadmium, mercury, selenium, and thallium contributed most strongly to these inverse associations, whereas zinc showed a positive contribution. Discussion: These findings are unlikely to reflect protective effects and may instead reflect impaired urinary excretion resulting from kidney dysfunction. Our findings suggest that urinary elements in CKD reflect not only exposure but also disease-related alterations in renal excretory function. These findings highlight the potential for reverse causality when interpreting urinary elements as biomarkers or predictors of kidney outcomes.

Folate is a vital micronutrient involved in many essential biosynthetic pathways in the human body. Increased requirements during pregnancy make folate deficiency a global health concern. Supplemental folic acid prescribed to prevent/correct the deficiency has its limitations, making dietary folate superior to supplementation. This review provides a comprehensive overview of traditional fermented foods worldwide, their folate concentrations, microbial strains, and potential to improve folate status in animal models. Relevant studies investigating the folate content in fermented foods were identified. This review covers a variety of traditional plant‐ and animal‐based fermented foods. Nigerian ogi fermented with Lactiplantibacillus plantarum (formerly known as Lactobacillus plantarum ) and Candida tropicalis had the highest folate among plant‐based foods (3097 μg/100 mL), while yogurt containing L. plantarum had the highest folate in animal‐based foods (6323 μg/100 mL), providing ~500%–1000% of the recommended dietary allowance for pregnant women. L. plantarum was the most common strain found in foods with high folate concentrations. Seven animal studies demonstrated promising results supporting the effectiveness of fermented foods in improving folate status. This review concludes that traditional fermented foods are a good source of folate, with certain bacteria boosting folate levels, making biofortified fermented products a promising alternative to folic acid supplementation to decrease folate deficiency.