Vascular Health and Risk Management最新文献

Background: Acute myocardial infarction (AMI) disproportionately affects older adults, highlighting the need for equitable, high-quality cardiovascular care. In Kazakhstan, recent primary health care reforms may have improved outcomes, but it remains unclear whether these gains are comparable for women and men. This study aimed to assess sex-specific trends in AMI outcomes and identify independent predictors of adverse clinical events.

Methods: We performed a two-stage retrospective study. Stage 1 analyzed 2018-2024 hospitalization data by sex. Stage 2 examined electronic records of 1,866 AMI patients from a tertiary cardiology center. Demographics, clinical parameters, and outcomes were collected. Statistical analysis included group comparisons and uni-/multivariable logistic regression using SPSS.

Results: From 2018 to 2024, clinical improvement exceeded 90% annually except in 2021-2022, while mortality declined to 4.7%. Female were consistently presented at older ages than males and had less favorable baseline profiles, including lower hemoglobin levels and reduced renal function, whereas males had slightly higher creatinine levels and longer hospital stays. Hospital length of stay showed moderate variability with a post-pandemic increase, and hospitalization costs rose steadily for both sexes. Among 1,866 patients, hypertension was highly prevalent and 6.4% died. Deceased patients were older and showed worse hemodynamic, renal, metabolic, and inflammatory profiles with lower ejection fraction. In multivariable analysis, sex was not an independent predictor, while age, glucose, non-ST-elevation myocardial infarction (NSTEMI) status, systolic blood pressure, hemoglobin, glomerular filtration rate, and ejection fraction remained significant.

Conclusion: Advanced age, metabolic and renal dysfunction, hemodynamic instability, and impaired cardiac function were the strongest predictors of adverse outcomes, while NSTEMI presentation and better physiological status were associated with lower mortality. Females presented at older ages with less favorable risk profiles; although sex was not an independent predictor after adjustment, these differences underscore the need for tailored, risk-stratified care for high-risk patients.

Background: This post-hoc subanalysis of the VEIN STEP study assessed the effectiveness of conservative treatment, particularly venoactive drugs (VAD), in reducing chronic venous disease (CVD) signs and symptoms and improving quality of life (QoL) for patients with type 2 diabetes (T2D) in a real-life setting.

Methods: VEIN STEP was an observational, prospective study conducted in adult outpatients who consulted for symptomatic CVD (NCT04574375). CVD symptoms (10-cm Visual Analog Scale and Patient Global Impression of Change), disease severity (Venous Clinical Severity Score), and QoL (Chronic Venous Insufficiency Questionnaire [CIVIQ-14]) were assessed.

Results: Overall, 6084 patients were analyzed, of whom 702 (11.5%) had T2D. These patients were more likely to be older, present with a more advanced CEAP class, have a higher body mass index, greater symptom severity and reduced QoL scores than those without T2D (p<0.001 for all). Almost all patients with T2D (97.3%) received VAD-based treatment, mainly micronized purified flavonoid fraction (MPFF, 72.2%) or diosmin (24.6%). After 4 weeks, conservative therapy was associated with significant improvements in CVD symptoms and QoL (p<0.001). Physicians also noted a significant improvement in disease severity (p<0.001). The decrease in global symptom intensity was significantly greater among patients treated with MPFF than in those treated with diosmin (mean -2.7±1.8 vs -2.0±1.8, p=0.004). Greater reductions in symptom intensity were also observed in patients treated with MPFF for pain (p=0.011), leg heaviness (p=0.006), and swelling (p=0.014), with a tendency for greater improvement of cramps. QoL improved for patients receiving MPFF and those receiving diosmin, with changes in CIVIQ-14 global index score of -21.3±15.8 and -15.5±14.6, respectively.

Conclusion: These findings indicate that patients with concomitant CVD and T2D are more likely to have greater symptom severity and disease burden. In such patients, VAD-based conservative therapy, particularly MPFF, was associated with significant improvements in CVD-related symptoms and QoL.

Background: Cardiovascular diseases remain the leading cause of death and economic burden worldwide. Increasing evidence indicates that sleep disturbance and circadian rhythm disruption are major risk drivers for hypertension, coronary artery disease, heart failure, and arrhythmia. Although the classical transcription-translation feedback loop (TTFL) model explains the basic mechanism of rhythm generation, increasing evidence suggests that the heart-an organ with high metabolic demand-maintains circadian stability through coordinated transcriptional, translational, and post-translational regulation.

Methods: We developed an integrative, time-resolved, multilayer in silico framework to systematically analyze cardiac circadian regulation by combining mouse heart time-series RNA-seq (GSE54650), proteomics (PXD002870), phosphoproteomics (PXD036824), BMAL1 and Rev-erbα ChIP-seq, and enhancer RNA (eRNA) datasets. Rhythmicity was assessed using MetaCycle, with cross-layer comparisons evaluating concordance and divergence between transcriptomic and proteomic rhythms, and translation efficiency (TE) estimated from protein-to-mRNA ratios. Enhancer-gene coupling, transcription factor binding, and phosphorylation motif analyses were integrated to investigate multilayer regulatory coordination.

Results: We identified 2552 rhythmic transcripts and 139 rhythmic proteins, with only 31 genes rhythmic at both layers, indicating substantial RNA-protein phase decoupling in the heart. Temporal stability of TE correlated positively with protein amplitude, suggesting that stable translation supports robust protein rhythmicity. Phosphoproteomic analyses revealed enrichment of SP motifs mediated by proline-directed kinases in rhythmic proteins. BMAL1 binding was associated with enhanced transcriptional amplitude, whereas REV-ERBα binding was associated with delayed target gene expression, forming complementary enhancer-level regulatory dynamics.

Conclusion: This study supports a multilayered integrative model of cardiac circadian regulation in which rhythmic gene expression is jointly shaped by transcriptional activation, translational precision, and post-translational modification. By extending the classical "clock-transcription-protein" paradigm, our findings highlight enhancer-level control mediated by BMAL1 and Rev-erbα as an important mechanism contributing to the stabilization of cardiac circadian timing.

Introduction: The incidence of coronary heart disease (CHD) is rising globally. Despite the high burden of CHD in Africa, little is known about appropriate risk stratification systems that can be used to predict outcomes in patients with acute coronary syndromes (ACS) in this region.

Methodology: This was a single-center retrospective cohort study conducted at the Aga Khan University hospital. Data was explored descriptively by summarizing categorical variables using frequencies/percentages and continuous variables using medians and interquartile ranges. Risk groups and mortality were compared using Fisher's exact test or the chi-square test. The area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity were obtained from a binary logistic regression model with mortality as the outcome of interest. The model fit was assessed using Hosmer-Lemeshow statistics. Analysis was performed using R version 4.3.2 (2023-10-31 ucrt) and p-value < 0.05 set as statistical significance.

Results: 378 participants were enrolled. NSTEMI was diagnosed in 48.4% of participants and STEMI in 51.6%. ACS in-hospital mortality was 2.11% and 6-months mortality was 12.70%. NSTEMI in-hospital mortality was 0.55% (p = 0.45) and 15.92% (p = 0.028) at 6-months. STEMI in-hospital mortality was 3.72% (p < 0.001) and 18.23% (p < 0.001) at 6-months. The AUROC curve for in-hospital mortality was 0.87 and 0.66 for 6-month mortality, demonstrating acceptable discriminatory capacity. Calibration of the score using the Hosmer-Lemeshow model fit was appropriate (p = 0.999).

Conclusion: The GRACE 2 score demonstrated good discriminative power and an acceptable goodness-of-fit for in-hospital outcomes in our setting, but was insufficiently accurate for reliably predicting 6-month post-discharge mortality.

Purpose: Grouping comorbidities can better reflect the intrinsic relationships among complications. We aimed to explore the relationships between comorbidity groups and dynamic changes in health-related quality of life (HRQoL) in patients with chronic heart failure (CHF).

Patients and methods: A total of 1533 patients with CHF were included. Demographic and clinical variables were recorded during hospitalization. HRQoL was assessed using the Kansas City Cardiomyopathy Questionnaire (KCCQ) at baseline and at 3 and 12 months. Latent class analysis was used to identify comorbidity groups among patients with CHF. This method identifies latent subgroups by analyzing patterns in their comorbidities. Repeated-measures analysis of variance (ANOVA) was used to assess the relationships between comorbidity groups and dynamic changes in KCCQ scores.

Results: Three comorbidity clusters were identified: the young/valvular heart disease (VHD) group, the elderly/coronary heart disease (CHD) group, and the high-comorbidity burden group. The young group had a relatively lower comorbidity burden and the best HRQoL, followed by the elderly/CHD group, while the high-comorbidity burden group showed the worst HRQoL. The overall summary scores, clinical summary scores, social limitations, physical limitations, and self-efficacy were significantly highest in the high-comorbidity burden group. In addition, at 3 months the symptom scores had decreased in all three groups. Repeated-measures ANOVA showed that the comorbidity groups were significantly associated with dynamic changes in HRQoL through time and group effects.

Conclusion: There were significant differences in the baseline characteristics and dynamic changes of HRQoL among different comorbidity clusters. Patients in the high-comorbidity burden group performed the worst in terms of quality of life, but the improvement was the most significant.

Purpose: Aortic dissection (AD) is a life-threatening aortic emergency that progresses rapidly and carries a high mortality rate. We characterised contemporary patterns and long-term trends in AD mortality in the United States and examined associations between ambient temperature and AD mortality.

Patients and methods: We obtained mortality data for AD from United States CDC WONDER for 1999-2023 and calculated age-adjusted mortality rates (AAMR). Temporal trends were assessed using Joinpoint regression to estimate annual percent change (APC) and average annual percent change (AAPC). Monthly air temperature data for the period 1999-2023 were obtained from the North America Land Data Assimilation System (NLDAS). Associations between temperature and AD mortality were evaluated across census regions using correlation analyses and Poisson regression models. To explore the future burden, subgroup-specific time series models (ARIMA or ETS) were applied to generate 20-year forecasts.

Results: In 2023, there were 4,418 AD deaths (AAMR 1.73 per 100,000; 95% CI 1.68-1.78); rates were highest in the Midwest (1.96), in male (2.19 vs 1.24 in female), in non-Hispanic Black individuals (2.75), and in adults ≥85 years (11.67). From 1999-2023, 86,943 deaths occurred and the overall AAMR declined (AAPC -0.37), but reversed to sustained increases after 2013. Across the four census regions, the monthly AAMR was lowest in summer and highest in winter during 1999-2023 (P < 0.05). A 10°F increase in temperature was associated with lower mortality risk (eg, South RR 0.889).

Conclusion: AD mortality has rebounded since 2013 with marked demographic and regional disparities. Lower temperatures and greater thermal variability are linked to higher mortality, supporting seasonally and region-tailored prevention and health-system preparedness.

Peripheral artery disease (PAD) is rapidly emerging as a global health priority, with projections indicating a dramatic rise in prevalence, mortality, and disability by 2050. Recent forecasts project an approximately 220% increase in PAD prevalence, with more than 360 million individuals affected globally by mid-century, largely driven by metabolic diseases-particularly diabetes and obesity. A recent population-based study forecasting the global burden of PAD provides compelling evidence that metabolic disease is the dominant driver of this alarming trend. This commentary highlights the critical interplay between metabolic risk factors and PAD progression, underscores the disproportionate burden expected in low- and middle-income countries, and calls for urgent, integrated strategies targeting metabolic health. Without decisive action to reduce diabetes, obesity, and related metabolic disorders, the looming global PAD crisis will further strain healthcare systems and deepen health inequities worldwide.

Background: People with diabetes mellitus (DM) remain at high risk of cardiovascular (CV) disease. The use of coronary artery calcium (CAC) has been demonstrated as the most powerful CV risk indicator and surrogate marker for the overall vascular health in the asymptomatic population.

Material and methods: This study aimed to find the severity of CAC in asymptomatic Thai people with DM, evaluate the correlation of the severity CAC risk scoring system with different CV risk scores, and examine the impacts of CAC testing on patient managements. ABC control, defined as the proportion of individuals meeting glycemic, blood pressure, and LDL cholesterol targets together, was assessed at 6 months after the CAC measurement.

Results: A total of 157 patients (female 45.2%, T2D 93.0%, mean age 61.7±13.3 years, mean DM duration 12.4±10.6 years, BMI 26.4±4.8 kg/m², A1C 7.4±1.9%, insulin usage 28.7%) were included in the study. Zero calcium score was found in 24.2% and CAC score ≥100 AU was found in 40.3% of all patients. There was a weak to moderate significant positive correlation (correlation coefficients ranged from 0.311 to 0.449) between different CV risk scores with the presence of CAC score ≥100 AU. In those with CAC score ≥ 100 AU, aggressive lipid-lowering therapy, new prescription of SGLT2i or GLP-1 RA, new prescription of antiplatelet as primary prevention was all increased when compared with CAC <100 AU. At 6 months, achieved ABC target increased from 30.4% to 55.7% in patients with CAC ≥100 AU while achieved ABC target increased from 35.9% to 56.4% in patients with CAC < 100 AU.

Conclusion: CAC is an effective tool for CV risk stratification among asymptomatic people with DM and could improve metabolic target attainment rates. Currently available clinical risk assessment models including diabetes-specific risk scores correlated weakly with results from CAC testing among Thai people with DM.

Background: Evidences suggested that gamma-glutamyltransferase (GGT) to high-density lipoprotein cholesterol (HDL-C) ratio (GTHR) was a reliable surrogate indicator for fatty liver disease, diabetes, metabolic syndrome. However, the relationship between GTHR and the presence of arterial stiffness remains unclear in healthy population. In the present study, we aimed to explore the association between GTHR and arterial stiffness (AS) in a health check-up population from Japan.

Methods: This study is a secondary analysis from a health check-up program carried out at Murakami Memorial Hospital, Gifu, Japan between March 2004 and December 2012. A total of 912 individuals were included in this study. Patients were divided into three groups according to the tertiles of LogGTHR. The univariate linear regression model and the multivariate models were performed to explore the association between between LogGTHR and baPWV. Smoothed curve fit analysis was used to explore the linear or the nonlinear relationship between LogGTHR and baPWV. The modification and interaction of subgroup were inspected by the likelihood ration test.

Results: After adjusting for confounders, there is a nonlinear relationship between LogGTHR and baPWV (β=30.08, 95%CI: -33.12 to 93.29, P=0.351). The inflection point was 1.43. When K<1.43 (80.37% of the participants), the relationship was positively correlated (β=165.15, 95%CI: 62.72 to 267.58, P=0.0016), while when ≥1.43, there was a negative association between LogGTHR and baPWV (β= -106.23, 95%CI: -209.25 to -3.21, P=0.0436). Subgroup analysis suggested that LogGTHR was not associated with baPWV in any of these subgroups.

Conclusion: In this cross-sectional study, there was a nonlinear positive association between LogGTHR and AS. LogGTHR was positively related with baPWV when less than 1.43, while this association was negative when LogGTHR was >1.43.

Objective: Compared to stable abdominal aortic aneurysms (AAA), the inflammatory response in perivascular adipose tissue (PVAT) may be exacerbated prior to rupture, leading to functional and structural alterations that manifest as imaging disparities. Radiomics enables the extraction of images features, which can be integrated with machine learning(ML) to construct models for clinical decision support. This study investigated the potential of radiomic features derived from PVAT to predict AAA rupture.

Methods: A retrospective analysis was conducted using aortic Computed Tomography Angiography (CTA) images from two centers, comprising patients with either stable or ruptured AAA who had pre-rupture CTA scans. These images were allocated to a development set and an external validation set. After radiomic feature extraction, statistically significant features between the two groups were subjected to dimensionality reduction. Subsequently, ten common ML models were constructed and validated using both internal and external validation sets.

Results: The development set comprised 37 ruptured patients and 155 non-ruptured patients. The external test set included 6 ruptured patients and 30 non-ruptured patients. A total of 107 radiomic features were extracted per patient, of which 18 exhibited statistically significant differences between groups. After dimensionality reduction, 5 representative features were selected. The constructed models achieved an average accuracy of 0.76 and an average AUC of 0.81 in the internal test set, while the external test set yielded an average accuracy of 0.73 and an average AUC of 0.77.

Conclusion: Significant differences exist in PVAT characteristics between ruptured and non-ruptured AAA patients, supporting the feasibility of using radiomic features for rupture prediction with reasonable accuracy.