Mental disorders impose a disproportionate burden on populations in low- to middle-income countries (LMICs) and low-income countries (LICs), yet longitudinal assessments across these settings remain limited. Using the Global Burden of Disease Study 2023, we investigated prevalence and disability-adjusted life years (DALYs) for 10 mental disorder subcategories across 76 LMICs and LICs from 1990 to 2023 and projected trends through 2050 via a generalized ensemble modeling approach. Age-standardized prevalence rose markedly between 1990 and 2023, from 10,759.9 (95% uncertainty interval, 9,560.1-12,088.6) to 13,929.3 (12,512.5-15,829.0) per 100,000 in LMICs and from 11,723.6 (10,577.7-12,987.5) to 14,979.1 (13,512.9-16,770.7) in LICs, accompanied by corresponding increases in age-standardized DALY rates. The most pronounced increases in both age-standardized prevalence and DALYs were observed during the COVID-19 pandemic. Anxiety disorders (total percentage change: 102.3% in LMICs; 67.3% in LICs), eating disorders (40.7% in LMICs; 4.8% in LICs), depressive disorders (28.6% in LMICs; 29.8% in LICs), and autism spectrum disorders (14.9% in LMICs; 22.5% in LICs) showed the largest increases in prevalence. Under a reference scenario where past trends persist, age-standardized prevalence is projected to reach 17,155.8 (14,449.5-20,212.5) per 100,000 in LMICs and 17,968.4 (15,109.8-21,090.9) in LICs by 2050. These findings reveal persistent and widening disparities in mental health burden across resource-limited settings, substantially exacerbated by the pandemic. Without targeted, scalable, and sustained policy interventions, the burden in LMICs and LICs will continue to worsen, underscoring the critical need for context-specific public health action. This study was funded by the Gates Foundation.
Residual cardiovascular risk remains a significant clinical challenge despite the intensive management of conventional risk factors. This study aimed to evaluate the impact of the Remnant Cholesterol-Inflammation Index (RCII)-a novel metric integrating dyslipidemia and systemic inflammation-on the incidence of hypertension and its subsequent cardiovascular sequelae. We leveraged data from two large-scale prospective cohorts. The China Health and Retirement Longitudinal Study (CHARLS) included a cross-sectional cohort for prevalent hypertension (N = 8,650) and a longitudinal incident-hypertension cohort (N = 5,022). The UK Biobank (UKB) included 273,122 participants with hypertension at baseline. Multivariable logistic regression and Cox proportional hazards models were used to assess incident hypertension and long-term adverse outcomes (all-cause mortality, major adverse cardiovascular events [MACE], and cardiovascular death), respectively. In the CHARLS cohort, high RCII was associated with a higher risk of incident hypertension in the fully adjusted model (OR, 1.346; 95% CI, 1.192-1.519). In quartile analysis, the highest RCII quartile was also associated with incident hypertension compared with the lowest quartile (OR, 1.364; 95% CI, 1.150-1.618; P for trend < 0.001). In the UKB cohort, compared with participants in the lowest RCII quartile, those in the highest quartile had higher risks of MACE (HR, 1.273; 95% CI, 1.232-1.315), all-cause mortality (HR, 1.214; 95% CI, 1.169-1.261), and cardiovascular death (HR, 1.284; 95% CI, 1.205-1.368) in fully adjusted complete-case models. Joint-effect analysis showed that concurrent elevation of remnant cholesterol and systemic inflammation was associated with the highest risk of MACE in UKB (HR, 1.16; 95% CI, 1.12-1.20). Exploratory mediation analyses suggested possible indirect pathways involving insulin resistance and oxidative stress. RCII was associated with both incident hypertension and adverse prognosis among hypertensive participants. These findings support RCII as a complementary lipid-inflammatory residual-risk marker; however, external validation and decision-utility studies are needed before clinical implementation.
The neutrophil percentage-to-albumin ratio (NPAR) is a composite biomarker reflecting systemic inflammation and nutritional imbalance. Its prognostic significance for mortality in patients with hyperuricemia (HUA) or gout remains incompletely understood, and whether this association differs between asymptomatic HUA and gout has not been examined. We utilized data from the National Health and Nutrition Examination Survey (NHANES, 1999-2018). After applying exclusion criteria, 4,344 adults were identified, comprising 3,659 with asymptomatic hyperuricemia and 685 with gout (56.8% male; median age 52 years). The neutrophil percentage-to-albumin ratio (NPAR) was calculated for each participant. All analyses were stratified by clinical subgroup (asymptomatic hyperuricemia vs. gout). Associations between NPAR and all-cause and cardiovascular mortality were evaluated using Kaplan-Meier analysis, weighted multivariable Cox proportional hazards regression, and restricted cubic spline (RCS) models. To account for competing risks from non-cardiovascular death, Fine-Gray subdistribution hazard models were fitted, and cumulative incidence functions were estimated by the Aalen-Johansen method. In the asymptomatic HUA subgroup, participants in the highest NPAR quartile (Q4) exhibited significantly elevated risks of all-cause mortality (adjusted HR = 2.08, 95% CI: 1.56-2.78, P < 0.001) and cardiovascular mortality (adjusted HR = 2.24, 95% CI: 1.41-3.56, P = 0.001) after full adjustment, compared with the lowest quartile (Q1). In the gout subgroup, the corresponding HR was 2.14 (P = 0.028) for all-cause mortality; for cardiovascular mortality, the quartile-based HR was 3.51 (P = 0.060), while RCS analysis showed a peak HR of 4.95 at the highest NPAR values. NPAR demonstrated strong predictive accuracy in the full cohort, with an AUC of 0.875 for both all-cause and cardiovascular mortality (Model 4, 10-year). In the competing risks analysis, the association between NPAR and cardiovascular mortality remained significant after accounting for non-cardiovascular death as a competing event, with Q4 maintaining an elevated risk across all adjustment levels (fully adjusted sHR = 1.899, 95% CI: 1.366-2.640, P < 0.001; P for trend < 0.001). NPAR is a robust independent predictor of all-cause and cardiovascular mortality in patients with asymptomatic HUA. The association was attenuated in the gout subgroup, likely due to the smaller sample size and limited cardiovascular events, likely reflecting the smaller sample size and limited cardiovascular events. NPAR may serve as a practical clinical biomarker for risk stratification in HUA and gout populations.
Cardiovascular-kidney-metabolic (CKM) syndrome, characterized by the interplay of metabolic risk factors, chronic kidney disease, and cardiovascular dysfunction, is a key driver of cardiovascular disease (CVD) incidence. The cholesterol, high-density lipoprotein, and glucose (CHG) index, which integrates total cholesterol, high-density lipoprotein, and fasting blood glucose, and its modified indices (combined with obesity indicators) have potential for CVD risk prediction. However, their role across CKM stages 0-3 remains unclear. A nationwide prospective cohort study included 5,404 participants with CKM stages 0-3, screened from 17,708 individuals screened between 2011 and 2020. CHG index and modified indices (CHG-BMI, CHG-Wc, CHG-WHtR) were calculated. Logistic regression, restricted cubic spline (RCS) analysis, subgroup analysis, and sensitivity analysis were used to evaluate associations with CVD incidence and identify exploratory threshold association. During follow-up, 25.5% of participants developed CVD. CHG and modified indices were independently associated with increased CVD risk (all P < 0.001). In fully adjusted models, CHG as continuous data showed a 28% higher risk (OR = 1.28, 95% CI: 1.06-1.58) of outcome, and CHG-WHtR was 54% higher (OR = 1.28, 95% CI: 1.16-2.04). Meanwhile, the highest quartile (Q4) of CHG-WHtR was associated with a 43% higher risk (OR = 1.43, 95% CI: 1.03-1.98) compared to Q1, while CHG-BMI (OR = 1.68, 95% CI: 1.22-2.31) showed stronger associations. RCS analysis identified exploratory inflection points like CHG ≥ 5.15 and CHG-WHtR ≥ 2.41, above which CVD risk significantly increased (P < 0.005) and validated by bootstrap sampling. Subgroup analysis confirmed consistent associations across age, gender, and CKM stages subpopulations. Multiple sensitivity analysis supported the robustness of these associations across CKM stages. CHG index and its modified indices, particularly CHG-WHtR and CHG-Wc, are valuable indicators associated with reported incident CVD across CKM stages 0-3. Their stage-specific associations and exploratory threshold association support their utility in risk stratification for CKM syndrome.
Evolocumab, a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor, potently reduces low-density lipoprotein cholesterol. However, its effects on hard clinical endpoints and safety in patients with atherosclerotic cardiovascular disease (ASCVD) require updated synthesis, particularly incorporating data from recent long-term extension studies and diverse subpopulations. To systematically evaluate the efficacy and safety of evolocumab in patients with ASCVD. PubMed, Embase, Cochrane Library, OVID, China National Knowledge Infrastructure (WANFANG MED ONLINE and CNKI), and ClinicalTrials.gov were systematically searched from January 2014 to March 2026. Randomized controlled trials (RCTs) comparing evolocumab with placebo in patients with ASCVD were included. The primary endpoint was major adverse cardiovascular events (MACE). A random-effects model was used for meta-analysis, with subgroup analyses, meta-regression, sensitivity analyses, and publication bias assessment. Eight RCTs comprising 40,658 patients were included. Regarding lipid parameters, evolocumab significantly reduced levels of low-density lipoprotein cholesterol (LDL-C; standardized mean difference [SMD]: -2.546, 95% confidence interval [CI]: -3.024 to -2.067, P < 0.001), total cholesterol (TC; SMD: -1.543, 95% CI: -1.947 to -1.139, P < 0.001), apolipoprotein B (Apo B; SMD: -1.598, 95% CI: -2.169 to -1.027, P < 0.001), and lipoprotein(a) (Lp(a); SMD: -0.713, 95% CI: -0.938 to -0.489, P < 0.001) compared with placebo, but showed no significant effect on high-density lipoprotein cholesterol (HDL-C; SMD: 0.233, 95% CI: -0.058 to 0.524, P = 0.117) or triglycerides (TG; SMD: -0.315, 95% CI: -0.765 to 0.136, P = 0.171). For clinical endpoints, evolocumab significantly reduced the odds of MACE compared with placebo (OR: 0.416, 95% CI: 0.248-0.698, P < 0.001; I2 = 86.7%); however, the 95% prediction interval crossed unity (0.13-1.36), indicating uncertainty about the true effect in future studies. Myocardial infarction (OR: 0.711, 95% CI: 0.661-0.765, P < 0.001), stroke (OR: 0.774, 95% CI: 0.693-0.864, P < 0.001), and coronary revascularization (OR: 0.777, 95% CI: 0.734-0.821, P < 0.001) all showed significant odds reductions. Evolocumab significantly reduced odds of cardiovascular death (OR: 0.771, 95% CI: 0.657-0.904, P = 0.002) and all-cause mortality (OR: 0.852, 95% CI: 0.762-0.953, P = 0.004). Safety analysis indicated that injection site reactions were more common with evolocumab (OR: 1.33, 95% CI: 1.12-1.59, P < 0.01), with no significant differences in serious adverse events, neurocognitive events, muscle-related events, or liver function abnormalities. In the context of optimized background therapy, evolocumab significantly reduces the odds of MACE, myocardial infarction, and stroke, and improves multiple atherogenic lipid parameters in patients with ASCVD. Notably, significant reductions in both cardiovascular and all-cause mortality were also observed in this updated analysis. Its overall safety profile is favorable.
This study aimed to construct and validate a machine learning classifier for cross-sectionally stratifying existing cardiovascular-kidney-metabolic (CKM) syndrome stages using routine composite inflammatory, metabolic and anthropometric indices, and to interpret core driving biomarkers via SHAP analysis. We analyzed data from 12,106 participants from the National Health and Nutrition Examination Survey (NHANES). Among 24 initial biomarkers, 10 were selected after addressing multicollinearity and applying feature selection. Several machine learning algorithms were evaluated, with the LightGBM model demonstrating the highest performance (ROC AUC: 0.88). External validation using the China Health and Retirement Longitudinal Study (CHARLS) dataset confirmed the model's generalizability (ROC AUC: 0.84). SHapley Additive exPlanations (SHAP) analysis revealed that metabolic markers-specifically eGDR, METS_VF, TyG, and TyG_BMI-were consistently the strongest predictors across CKM stages, whereas inflammatory indicators showed more limited utility. Key metabolic composite indices exhibit significant associations with CKM staging and may serve as practical, clinically feasible tools for risk stratification. The model's robust performance across distinct populations (U.S. and China) supports its potential clinical utility. Further validation in diverse populations and prospective studies is needed to confirm their predictive value and translational potential.
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Atherosclerotic cardiovascular disease (ASCVD) represents a broad spectrum of phenotypes with shared pathology. However, the joint genetic architecture across different vascular beds remains incompletely characterized. We applied genomic structural equation modeling (Genomic SEM) to integrate GWAS summary statistics from six ASCVD-related traits: coronary artery disease, myocardial infarction, ischemic stroke, peripheral artery disease, carotid intima-media thickness, and intracranial aneurysm. Downstream analyses included multivariate GWAS, fine-mapping, TWAS with FOCUS, MAGMA, pathway enrichment, cell-type and functional annotation, gsMAP and polygenic risk score. A single latent common factor model demonstrated an excellent fit to the genetic covariance matrix (CFI = 0.9837, SRMR = 0.1448). The multivariate GWAS identified 839 genome-wide significant SNPs, delineating 85 independent lead loci, of which 67 were novel. Integration of TWAS and FOCUS prioritized 6 high-confidence putative effector genes, including CDKN2B, MIA3, and NBEAL1. Functional enrichment highlighted lipid remodeling and apolipoprotein binding as predominant pathways. Notably, heritability was significantly localized in endothelial cell lineages across multiple tissues. Spatial mapping further identified the lung and kidney as key developmental tissue contexts for ASCVD genetic risk. Our study provides a unified genetic framework for ASCVD, demonstrating that its shared liability is anchored in lipid homeostasis and systemic endothelial dysfunction. These findings offer a foundational atlas for early genomic-based risk stratification and therapeutic targeting.
Complete blood count-derived inflammatory indices have been associated with coronary artery disease (CAD), but their substantial overlap may limit interpretability when assessed individually. We used principal component analysis (PCA) to integrate six commonly used inflammatory indices into a composite Inflammatory Burden Score (IBS) and evaluated its association with angiographically confirmed CAD alongside the Prognostic Nutritional Index (PNI). This retrospective cross-sectional study included 1,261 individuals (477 with CAD and 784 without CAD) who underwent invasive coronary angiography at a tertiary referral center. PCA was applied to six standardized inflammatory indices, and the first principal component was retained as the IBS. Hierarchical logistic regression models were constructed to evaluate the incremental contribution of IBS and PNI beyond conventional cardiovascular risk factors. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC), calibration metrics, and likelihood-ratio testing. XGBoost and SHAP analyses were performed as complementary explainable machine-learning approaches. The first principal component explained 68.1% of the total variance across inflammatory indices, with all variables contributing positively to the composite score. IBS was significantly higher among participants with CAD (p < 0.001). In univariable analyses, both IBS (OR 1.11, 95% CI 1.05-1.17, p < 0.001) and PNI (OR 0.05, 95% CI 0.02-0.14, p < 0.001) were associated with CAD. After adjustment for conventional cardiovascular risk factors, IBS (OR 1.12, 95% CI 1.06-1.19) and PNI (OR 0.06, 95% CI 0.02-0.20) remained independently associated with CAD. Addition of either IBS or PNI significantly improved model fit (both likelihood-ratio test p < 0.001). The AUC increased from 0.727 in the conventional risk-factor model to 0.734 after inclusion of IBS and to 0.737 after inclusion of PNI. The XGBoost model achieved an AUC of 0.802, while SHAP analysis identified age and sex as the dominant predictors, followed by IBS and PNI. In this single-center cross-sectional cohort, a PCA-derived inflammatory burden score and the Prognostic Nutritional Index were independently associated with angiographically confirmed CAD beyond conventional cardiovascular risk factors. Both measures contributed similarly in explainable machine-learning analyses. These findings are exploratory and require prospective external validation before clinical application.
Older patients often suffer from multiple disorders and are hence frequently burdened by polypharmacy. Prevention of cardiovascular events using antiplatelet drugs might be indicated among older populations, but there are no studies assessing platelet function in these patients. Using impedance aggregometry, we compared platelet reactivity to 7 aggregation inducers between a group of 44 polymorbid older patients aged 78 + years (PP), and 50 generally healthy younger controls (median age, 44 years). None of the subjects were treated with antiplatelet therapy. We also examined their response to antiplatelet drugs (acetylsalicylic acid, ticagrelor, vorapaxar) and an experimental compound, 4-methylcatechol, a small polyphenol metabolite of many natural polyphenolic compounds. Data analysis was performed in the whole group as well as after removing or splitting the groups based on concomitantly administered drugs. Linear mixed-effects modelling was used to investigate the impact of both drugs and comorbidities on the obtained results. A clinically achievable concentration of ASA (30 µM) failed to block platelet aggregation when arachidonic acid was used as an inducer, but the response to ticagrelor, vorapaxar, and 4-methylcatechol with relevant inducers was significant. However, the sensitivity to ticagrelor and vorapaxar was lower in PP when compared to healthy controls. The analysis also confirmed similar activity for 4-methylcatechol, but lower activity for acetylsalicylic acid in our PP. Further analyses excluding specific drugs did not significantly alter these outcomes. Inflammatory markers and the presence of type 2 diabetes mellitus were significant predictors of platelet reactivity while basic blood parameter data had no clear impact. The ex vivo response of platelets from PP to the standard antiplatelet drugs was lower. In contrast, they responded well to 4-methylcatechol.
The triglyceride-glucose (TyG) index has been proposed as an accessible indicator of insulin resistance and cardiometabolic risk. However, its prognostic relevance in patients with premature acute coronary syndrome has not been well defined. We therefore examined baseline clinical features and long-term cardiovascular outcomes in patients with premature acute coronary syndrome (PACS) stratified by TyG status. This retrospective cohort study screened 820 consecutive patients hospitalized with PACS, of whom 804 had complete fasting triglyceride and fasting plasma glucose measurements for TyG calculation. TyG was calculated as ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL) / 2]. Patients were categorized into high and low TyG groups using the 66.7th percentile as the cutoff. The primary outcome was major adverse cardiovascular and cerebrovascular events (MACCE). Among 804 eligible patients, 268 (33.3%) were assigned to the high TyG group and 536 (66.7%) to the low TyG group. Patients with high TyG showed a more unfavorable cardiometabolic profile and a higher coronary disease burden at baseline than those with low TyG. During follow-up, MACCE occurred in 17.2% of patients in the high TyG group and in 10.4% of those in the low TyG group. After multivariable adjustment, high TyG remained associated with a higher risk of MACCE (adjusted HR 1.61, 95% CI 1.05-2.47; P = 0.029). TyG analyzed as a standardized continuous variable was also independently associated with MACCE (adjusted HR 1.306, 95% CI 1.039-1.643; P = 0.022). Landmark analysis indicated that the association was more prominent after 365 days. In this PACS cohort, elevated TyG was independently associated with an increased risk of MACCE, particularly during longer-term follow-up. TyG may provide a simple adjunctive marker for identifying residual cardiometabolic risk in relatively young patients after ACS.
Individuals with diabetes have an increased risk of cardiovascular disease, infection, hospitalization, and premature mortality. However, less is known about how diabetes shapes the broader pattern of emergency department (ED) presentations, acute care use, clinical complexity, and short-term mortality in an unselected ED population. We aimed to describe ED presentation patterns and outcomes among individuals with and without diabetes in a large regional cohort. We conducted a population-based cohort study including all adult ED visits to nine hospitals in Region Skåne, Sweden, between 2017 and 2018. ED visits for patients with a registered diabetes diagnosis (n = 60,654) were compared with those without diabetes (n = 502,800). We analysed ED visit frequency, recurrent ED use, arrival by ambulance, triage priority, length of stay, comorbidity burden, presenting complaints, and mortality after ED presentation. The most common presenting complaints were broadly similar in both groups, with dyspnoea, chest pain, and abdominal pain among the leading causes of ED presentation. However, diabetes visits were characterized by greater acute care complexity. Compared with visits by individuals without diabetes, visits by individuals with diabetes more often involved a previous ED visit within 90 days, higher triage priority, ambulance arrival, longer ED stay, and substantially higher comorbidity burden. Early mortality after ED presentation was also higher among individuals with diabetes and occurred at younger ages, particularly among men. Mortality diagnoses differed between groups, with cardiovascular causes more prominent among individuals with diabetes. In this large population-based ED cohort, individuals with diabetes presented with broadly similar symptom categories as those without diabetes, but with markedly greater clinical complexity, higher acuity, recurrent acute care use, and earlier mortality. Diabetes in emergency care may therefore identify a patient group with substantial multimorbidity, reduced physiological reserve, and increased vulnerability during acute illness.
Drug-drug interactions (DDIs) are a critical safety issue in clinical practice, as they can lead to severe and often unpredictable adverse effects. This risk becomes significantly higher in multi-drug therapies, which are increasingly used in the treatment of complex and chronic diseases such as cancer, cardiovascular disorders, and diabetes. However, identifying DDIs through in vivo studies is costly and time-consuming. In this study, a novel DDI prediction model, Mol2Image, has been proposed that utilizes chemical structure features derived from Simplified Molecular Input Line Entry System (SMILES) representations, including molecular property descriptors and structural fingerprints. The proposed model combines chemical structure information with automated feature learning. Molecular descriptors and structural fingerprints extracted from SMILES representations are converted into visual patterns that capture key chemical characteristics of each drug. These images are then processed by a Convolutional Neural Network (CNN) to learn high-level structural features associated with drug-drug interactions. The model is trained and evaluated using two benchmark DDI datasets: the Drugbank dataset, which consists of 443,046 interactions, and ChCh-Miner, which consists of 48,514 DDIs. Experimental results demonstrate that the proposed model (Mol2Image) achieves competitive performance compared with several state-of-the-art methods. Experimental results demonstrate that the proposed model consistently outperforms existing approaches, achieving accuracies of 0.9608 and 0.9683 using the Drugbank dataset and ChCh-Miner dataset, respectively. Ultimately, Mol2Image provides a highly scalable, strictly structure-centric framework that ensures superior predictive accuracy with minimal computational overhead, operating entirely independently of clinical data.
Heart failure with reduced ejection fraction (HFrEF) patients remain at substantial risk despite quadruple guideline-directed medical therapy (GDMT [ARNI + SGLT2 inhibitor + β-blocker + MRA]). Data on vericiguat in stable HFrEF patients without recent worsening heart failure receiving contemporary quadruple GDMT are limited. This observational study aimed to explore the efficacy and safety of vericiguat in this population. A total of 450 adult patients with LVEF < 45% were enrolled (200 received quadruple GDMT plus vericiguat, 250 received quadruple GDMT alone). After 1:1 propensity score matching (PSM), 144 well-matched pairs were identified. The primary outcome was the composite of cardiovascular death or first HF hospitalization within 12 months. Secondary outcomes included changes in NYHA functional class, KCCQ-12 scores, and occurrence of hypotension. Due to the non-randomized design, all efficacy findings except the primary composite endpoint are considered exploratory. ChiCTR, ChiCTR2500095278. Registered 4 January 2025. Retrospectively registered. Over 12 months, the primary composite endpoint occurred in 5.56% of the vericiguat group versus 9.03% of the control group (P = 0.365; HR 0.616, 95% CI 0.255-1.486). No statistically significant differences were observed for cardiovascular death or all-cause mortality. Exploratory analyses showed that the vericiguat group had higher KCCQ-12 Overall Summary Scores (91.61 ± 9.56 vs. 87.93 ± 11.25, P = 0.003) and a greater proportion achieving a ≥ 5-point improvement (94.44% vs. 81.25%, P = 0.001). NYHA functional class distribution also differed between groups (P = 0.029). Hypotension rates were similar between groups. Among HFrEF patients without recent worsening, vericiguat did not significantly reduce the primary composite endpoint at 12 months. Exploratory observations suggest potential associations with improved quality of life and functional class without increased hypotension risk. These hypothesis‑generating findings require confirmation in adequately powered randomized controlled trials.
Atherosclerosis is a major contributor to cardiovascular disease and is strongly associated with cigarette smoking. Carotid intima-media thickness (CIMT) is a well-established noninvasive marker of subclinical atherosclerosis; however, limited evidence exists regarding the association between smoking intensity and CIMT among young adults in the Middle East. This study assessed the association between cigarette smoking and CIMT in Saudi adults aged 20-30 years compared with non-smoking. This cross-sectional comparative study was conducted at Majmaah University, Saudi Arabia, between November 2025 and March 2026 and included 50 adults (25 smokers and 25 non-smokers). CIMT was measured bilaterally in plaque-free segments of the distal common carotid arteries using high-resolution B-mode ultrasonography. Three manual measurements were obtained from each artery by trained sonographers, and the mean CIMT was calculated for each participant. Group differences were analyzed using independent-samples t-tests. Correlations between CIMT and smoking exposure variables were assessed using Pearson's correlation analysis, and multivariable linear regression was performed to evaluate whether smoking was independently associated with CIMT after adjustment for age and body mass index (BMI). Smokers had significantly higher mean CIMT values than nonsmokers (0.5404 ± 0.0218 mm vs. 0.4695 ± 0.0222 mm, p < 0.001). CIMT was weakly correlated with smoking duration (r = 0.244, p = 0.239) but moderately associated with daily cigarette consumption (r = 0.419, p = 0.037). Smoking remained an independent predictor of CIMT after adjustment (β = 0.0690, p < 0.001). Cigarette smoking is significantly associated with increased CIMT in young Saudi adults, supporting CIMT as an important marker for early vascular alterations.
Heart failure with preserved ejection fraction (HFpEF) is a complex systemic syndrome characterized by inflammation, metabolic dysregulation, and immune imbalance. However, simple and integrative biomarkers for risk stratification remain limited. The C-reactive protein-albumin-lymphocyte (CALLY) index, reflecting inflammation, nutritional status, and immune function, has shown prognostic value in various diseases, but its role in HFpEF remains unclear. In this single-center retrospective cohort study, 308 patients with HFpEF were enrolled. The CALLY index was calculated as albumin × lymphocyte count / CRP. The primary endpoint was major adverse cardiovascular events (MACE), defined as all-cause death or heart failure rehospitalization. Cox proportional hazards models, restricted cubic spline (RCS), receiver operating characteristic (ROC) analysis, and Kaplan-Meier curves were applied. During follow-up, 87 patients (28.25%) experienced MACE. Multivariable Cox analysis identified the CALLY index (HR = 0.98, 95% CI: 0.96-0.99) and E/e' (HR = 1.08, 95% CI: 1.01-1.17) as independent predictors of MACE. RCS analysis demonstrated a nonlinear inverse association between the CALLY index and MACE risk. ROC analysis showed good predictive performance (AUC = 0.82). Patients with lower CALLY index (< 11.8) had significantly higher event rates (log-rank p < 0.001). The CALLY index is an independent predictor of long-term outcomes in HFpEF, integrating inflammation, nutrition, and immune status. It may serve as a simple and practical tool for risk stratification.
Obesity is linked to prolonged ventricular repolarization (QT interval) in older populations, but its electrophysiological impact in healthy Asian youth remains unclear. This study aimed to assess the association between adiposity and ventricular repolarization in this population. This cross-sectional study included 3,156 healthy Asian youth (mean age 19.6 years). Adiposity was quantified using body mass index (BMI), body fat percentage (BFP), waist circumference (WC), and waist-to-hip ratio (WHR). The primary outcome was the Fridericia-corrected QT interval (QTcF). Sex-stratified robust regression was employed, and mediation by heart rate variability (HRV) was explored. Greater adiposity was associated with shorter QTcF, contrary to the conventional paradigm. This association exhibited marked sexual dimorphism. In males, all four adiposity indices were significantly linked to QTcF shortening (e.g., β = -2.97 ms per SD increase in BMI). In females, significant associations were confined to BMI and BFP. Furthermore, in females, vagal tone (rMSSD) and sympathovagal balance (LF/HF) statistically mediated part of the BMI/BFP-QTcF relationship, accounting for 6.3% to 9.8% of the effect. Sensitivity analyses confirmed robustness. In healthy Asian youth, obesity is associated with shorter ventricular repolarization, modulated by sex and adiposity type. These findings suggest unique early-life electrophysiological adaptations and underscore the importance of considering sex and body composition in cardiovascular risk assessment for young populations.
Dilated cardiomyopathy (DCM) is the most prevalent form of cardiomyopathy in children, characterized by left ventricle dilation and impaired systolic function. The etiology critically influences clinical trajectory and prognosis. Mitochondrial disorders represent a rare but increasingly recognized cause of DCM. Herein, we report three pediatric patients, diagnosed with early-onset DCM at ages of 8, 9, and 8, who progressed rapidly to end stage heart failure, resulting in two fatalities and one cardiac transplantation. Whole exome sequencing (WES) analysis identified compound heterozygous TOP3A pathogenic variants in all three cases, accompanied by reduced mitochondrial DNA copy number. Therefore, this report expands the recognized etiologies of childhood DCM and delineates a severe cardiac phenotype within the TOP3A pathogenic variant spectrum. Trial Registration: Registered at Chinese Clinical Trial Registry (ChiCTR2600117173). Registered 20/01/2026. Retrospectively registered.
Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C-related burden is critical for guiding prevention and treatment strategies. To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Population-level LDL-C concentrations. Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C-attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C-attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.
Transition of care (ToC) for patients with cardiovascular diseases is a complex, high-risk period often leading to medication-related harm (MRH) and hospital readmissions. While specialised programs exist, a gap in individualised medication management services exist for specific cardiology patient populations. Pharmacist-led, interdisciplinary ToC services have demonstrated a positive impact on patient outcomes. The REducing hospital re-admission for high-risk CARDiology patients (RECARD) program aims to address this by co-designing, implementing, and evaluating a new pharmacist-led ToC service in post-acute myocardial infarction (AMI) or cardiac surgery patients. The current study focuses on understanding the experiences and expectations of patients and clinicians to inform the development of this service. This qualitative study utilised semi-structured interviews and focus groups to gather data from patients and hospital and community clinicians aligned with three Queensland hospitals and surrounding primary and community care settings. Patients who had experienced an AMI or cardiac surgery in the past three months were interviewed via telephone or Microsoft TEAMS. Clinicians participated in focus groups or individual interviews. Data were audio-recorded, transcribed, and analysed using the six-phase thematic analysis method by Braun and Clarke, guided by Bradshaw's model of need to understand stakeholders' expressed and comparative needs. Data were obtained from 13 patient interviews and 40 clinicians, through seven focus groups and one interview. Three main themes, with associated subthemes, emerged from the data; Patient-level issues, System and process issues and Interprofessional collaboration. Patients described information overload, medication uncertainty, and anxiety at discharge, while clinicians identified delayed discharge summaries, fragmented communication with primary care, and service gaps - particularly impacting rural patients- as key risks for medication‑related harm. The study's findings highlight the critical need for a patient-centred, pharmacist-led interdisciplinary ToC service that addresses patient knowledge deficits, psychosocial barriers, and the communication gaps between hospital and community care settings. The results from this study will inform the development of the RECARD program's "Adaptive ToC Pathway," ensuring it is tailored to meet the specific needs and expectations of both patients and clinicians, ultimately aiming to reduce MRH and hospital readmissions.