Vascular Health and Risk Management最新文献

Objective: The aim of this study was to investigate the early and late outcomes of Open Surgical Conversion (OSC) following the failure of Endovascular Aneurysm Sealing (EVAS) endografts, regarding surgical technique, morbidity and mortality.

Method and material: A single center retrospective observational cohort of 46 patients undergoing OSC after EVAS failure. Primary endpoints were primary technical procedural success and 30-day mortality. Secondary endpoints were complications and primary prosthesis patency.

Results: Primary technical procedural success was 97.8% (45/46). Elective 30-day mortality for OSC was 10.9% (5/42) and 75% (3/4) for acute OSC procedures. Median survival after OSC was 4.2 years (IQR 1.0, 4.9 years). Four peri-operative and 17 post-operative complications were registered. Major complications included bleeding, myocardial infraction, acute renal failure and splenectomy. Primary prosthesis patency was 82.6% (38/46) at 30-days. At median follow-up of 4.7 years (IQR 3.9, 5.3 years) 69.6% (32/46) of the patients are still alive with patent vascular prostheses.

Conclusion: Open surgical conversion achieved acceptable technical success rate for failed EVAS, with better outcomes in elective versus emergency procedures. Enhanced surveillance with timely interventions before rupture and careful patient selection through multidisciplinary evaluation are essential for optimizing surgical outcomes.

Background: Despite significant advancements in early reperfusion therapy and pharmacological treatment, which have reduced mortality rates after myocardial infarction in recent decades, the in-hospital mortality rate remains high due to factors such as rapid disease progression, comorbid conditions, and potential complications. We aimed to develop and validate a predictive model for in-hospital mortality in myocardial infarction patients.

Methods: LASSO regression analysis, univariate analysis, and multivariate logistic analysis were used to construct the nomogram in the training set, followed by model comparison, internal validation, and sensitivity analysis.

Results: The analysis comprised 4688 patients in total. The population of patients was randomly assigned to the training set (n = 3512) and validation set (n = 1176). According to the results of LASSO regression analysis and other results, our nomogram contained a total of 10 independent variables related to patient death, including age, respiratory rate, blood glucose, lactate, PTT, BUN, cerebrovascular disease, chronic lung disease, mild liver disease, and metastatic solid cancer. Moreover, the web calculator and nomogram performed exceptionally well at predicting in-hospital death in myocardial infarction patients. The AUC for the training and validation sets' respective prediction models was 0.869 (95% CI: 0.849-0.889) and 0.846 (95% CI: 0.807-0.875) (p<0.01). Compared to the Sequential Organ Failure Assessment (SOFA), the nomogram showed greater discrimination in the training and validation sets, and the calibration plots demonstrated an adequate fit for the nomogram in predicting the risk of in-hospital mortality in both groups. The decision curve analysis (DCA) of the nomogram demonstrated a higher net benefit in the training and validation sets and in terms of clinical usefulness than the SOFA.

Conclusion: We developed a useful nomogram model and developed a nomogram-based web calculator to predict in-hospital mortality in myocardial infarction patients, which will support doctors in patient counseling and logical diagnosis and therapy.

Background: Higher level of carotid-femoral pulse wave velocity (CF-PWV) is indicating higher level of arterial stiffness. China has a population of 1.4 billion, with 1.2 billion population in Han ethnicity, 9.4 million population in Miao ethnicity, 700 thousand population in She ethnicity. We chose these three ethnic groups for analysis, to find some similarities or differences in CF-PWV.

Methods: We launched early vascular lesion detection technology promotion involving several regions such as the Han (Beijing), Miao (Guizhou Province), and She (Fujian Province) ethnicity. We conducted population testing in different regions and based on the inclusion and exclusion criteria, 1481 individuals were ultimately included. There were 942 han subjects, 186 Miao subjects and 353 She subjects. The CF-PWV was measured using a Complior device.

Results: The CF-PWV was significantly higher in Han population than in Miao and She population. Levels of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were significantly lower in Han ethnicity than in Miao and She ethnicity. The composition of male, smoking, hypertension and diabetes mellitus were significantly higher in Han ethnicity than in Miao and She ethnicity. Multiple linear regression analysis showed that age, body mass index (BMI), diabetes mellitus, creatinine, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), SBP, and ethnicity were independent associated with the CF-PWV in all subjects. And compared with the Han ethnicity, CF-PWV was significantly lower in Miao and She ethnicity (β= -0.295, β= -0.241, both p<0.001).

Conclusion: CF-PWV was significantly higher in Han ethnicity than in Miao and She ethnicity. The factors associated with the CF-PWV differed among different ethnicity indicated that different prevention and control strategies needed to be adopted for different ethnic groups and risk factors in different regions to reduce the progression of arteriosclerosis in the local population.

Background: Follistatin-like 1 (FSTL1) is recently becoming a novel cardiokine essential in cardiac angiogenesis. This cardiokine has shown a potential to promote angiogenesis and improve cardiac function, particularly in myocardial injury and ischemia. Despite the increasing relevance, there is no information on the mechanisms of FSTL1 in cardiac angiogenesis.

Objective: This systematic review aimed to consolidate recent results on the role of FSTL1 in molecular pathways of cardiac angiogenesis.

Methods: A comprehensive search was conducted using various databases, including PubMed, Scopus, SpringerLink, and ScienceDirect. Inclusion criteria were primary studies that investigated the role of FSTL1 in promoting cardiac angiogenesis with in vivo models. The risk of bias was assessed using SYRCLE risk of bias tool, and data were synthesized to evaluate the impact of FSTL1 on cardiac angiogenesis.

Results: A total of 5 animal studies were included during the analysis. The results showed the role of FSTL1 as a novel cardiokine in inducing cardiac angiogenesis as assessed by protein examination and histologic analysis. In pathological conditions, the effects of ischemia on the heart increased the expression of FSTL1 as a form of protection for the heart through angiogenesis and as a marker of the disease severity. Furthermore, the molecular mechanisms of FSTL-induced angiogenesis had different signaling pathways, including activation of AMPK, TGFβ-Smad2/3, Akt/mTOR, Erk1/2, and DIP2A-PI3K. Studies showed increased capillary density and improved blood flow in cardiac tissues where FSTL1 was upregulated, suggesting a possible important role in improving cardiac function.

Conclusion: FSTL1 showed a promising avenue for therapeutic development. Moreover, future studies should explore its role in cardiac angiogenesis in healthy populations.

Objective: This study investigates the relationship between serum γKlotho levels and coronary heart disease (CHD) risk and develops a machine learning model for CHD prediction.

Methods: A total of 1435 subjects were enrolled for analysis and randomized as training (n = 969, 70%) or validation (n = 466, 30%) group. The training group was used for univariate regression. Thereafter, least absolute shrinkage and selection operator (LASSO) regression was conducted for selecting independent risk factors for CHD. Using independent risk factors for CHD, nine machine learning models were developed, the best model was selected by evaluating them, and the model was validated by decision curve analysis (DCA).

Results: The factors independently associated with CHD risk were age, the serum level of γKlotho, LDL-C, sex, diabetes, hypertension, and smoking status. We used these risk factors to construct nine popular machine-learning models. Among all models, the RF model was better appropriate; thus, we visualized and validated this model, which showed promising clinical application.

Conclusion: Serum γKlotho levels are novel biomarker which positively related to CHD risk. Additionally, the RF model can better predict the risk of CHD, and RF model is better appropriate to predicting the CHD risk in clinics.

Background: In recent years, vascular aging has emerged as a hot topic in become an important direction of aging research, but a comprehensive bibliometric analysis has not been conducted.

Methods: The Web of Science database was searched for articles and reviews on vascular aging from January 1, 2014, to August 20, 2024, and the literature was analyzed and knowledge maps were constructed using CiteSpace, VOSviewer, pajek and Scimago Graphica software for econometric analysis and knowledge graph construction of the literature.

Results: A total of 38,910 authors from 7622 institutions in 111 countries published 7277 papers in 1344 academic journals, with a significant increase in publication volume. The United States is the country with the highest productivity and citation rates, and Mayo Clinic is the most active institution. Tarantini S published the most papers, while Csiszar A received the most citations. Retina-The Journal of Retinal and Vitreous Diseases journal published the most papers, and Circulation journal received the most citations. The main research aspects include age-related macular degeneration, arteriosclerosis, and oxidative stress, which are the main keywords in this field. In the last decade, the term c reactive protein has attracted great attention with its strongest citation explosion.

Conclusion: In the past decade, the research focus on vascular aging has been increasing year by year. Age-related macular degeneration, arteriosclerosis, oxidative stress and vascular endothelial cells are the emerging research directions in this field.

Background: Endovenous Laser Ablation (EVLA) is the recommended method for treating varicose veins. It is commonly performed in an inpatient or as day surgery setting under either general or spinal anesthesia. The purpose of this study is to assess the technical efficacy and safety performing outpatient EVLA for varicose veins under local tumescent anesthesia for procedure success, complications, recovery time, and patient satisfaction.

Methods: A retrospective review of 300 consecutive patients who underwent outpatient EVLA under local tumescent anesthesia from October 2014 to June 2019 was undertaken. Patients 25-55 years diagnosed with symptomatic varicose veins and Great Saphenous Vein (GSV) incompetence were enrolled. Patient demographics, clinical characteristics, procedure duration, complications, and follow-up outcomes were recorded.

Results: A total of 331 limbs were treated. The mean procedure time was 36 minutes. Five procedures were aborted for technical reasons, resulting in an overall technical success rate of 98%. They were minor complications of bruising (13%) and phlebitis (5%), that were resolved and did not require further intervention. There were no significant complications, including deep vein thrombosis (DVT) or pulmonary embolism (PE). Patients were discharged and resumed normal activities within approximately seven days and were well satisfied.

Conclusion: EVLA for varicose veins can be performed as an outpatient procedure under local tumescent anesthesia safely and with high technical efficiency. It offers the benefits of shorter recovery times, less risk of complications, and lower health care costs.

Background: The Sarcopenia Index (SI) is a recognized predictor of cardiovascular risk in patients with coronary artery disease (CAD), yet its association with aortic valve sclerosis (AVSc) remains insufficiently studied. This study aimed to examine the relationship between SI and AVSc in CAD patients.

Methods: In this retrospective study, 1056 CAD patients at Shanghai Ruijin Hospital underwent SI assessment and Doppler echocardiography. SI was calculated as [serum creatinine (mg/dL)/cystatin C (mg/L)] × 100. Logistic regression, subgroup analyses, and restricted cubic splines evaluated the SI-AVSc association. ROC curves determined SI's diagnostic value and its addition to traditional AVSc factors. In parallel with clinical observations, aortic valve changes were analyzed in mice via hematoxylin and eosin, AlizarinRed S, and Masson's trichrome to assess valve thickness, fibrosis and calcification.

Results: Patients with the lowest SI levels showed a higher prevalence of AVSc. Multivariate logistic regression revealed that SI was independently associated with AVSc (P<0.001). The C-statistic for SI in identifying AVSc was 0.708 (95% CI: 0.671, 0.744), and it improved risk stratification when SI was added to traditional clinical models (C-statistic increased from 0.840 to 0.866). In the subgroup analysis, the discriminatory power of SI was enhanced among elderly patients. Findings from animal models supported these results, and Spearman correlation analyses revealed negative correlation between SI and peak systolic aortic valve flow velocity (Spearman's rho=-0.578, P=0.006). Histological analysis demonstrated that aortic valve leaflets in the low SI group were thicker and more fibrotic than those in the high SI group, and this complementary approach provided mechanistic insights into how sarcopenia may promote valve degeneration in elder mice.

Conclusion: Lower Sarcopenia Index is associated with the presence of AVSc in CAD patients. SI improves risk stratification and acts as a valuable associated marker for AVSc, emphasizing its potential clinical utility in enhancing patient management.

Background: Functional compression of the internal carotid artery by hyoid bone is a rare but potentially serious condition that can lead to vascular complications, particularly when coexisting with intracranial vascular abnormalities. This case report describes a 48-year-old woman with acute cerebral ischemia due to a combination of functional right internal carotid artery compression by the hyoid bone, low carotid bifurcation, and coexisting Moyamoya syndrome.

Case report: In this article, we describe the clinical case of a 48-year-old woman who presented with sudden-onset weakness in her left arm. Imaging studies demonstrated acute ischemia in the territory supplied by the right middle cerebral artery. Further evaluation with computed tomography angiography revealed compression of the right internal carotid artery by the hyoid bone. However, additional imaging studies, including digital subtraction angiography and carotid Doppler ultrasound, did not reveal any signs of internal carotid artery stenosis. This suggested that the compression was functional, occurring only in specific positions of the head or arms. The patient was also newly diagnosed with Moyamoya syndrome, characterized by progressive stenosis of the intracranial vessels. Prompt recognition of these findings enabled timely management, including the initiation of antiplatelet therapy.

Conclusion: In cases of acute brain ischemia, it is crucial to consider both intracranial and extracranial vascular conditions. This case report underscores the significance of identifying anatomical variations in the relationship between the hyoid bone and the internal carotid artery, as it can lead to arterial compression and potentially trigger acute ischemic strokes, especially in combination with Moyamoya syndrome. Understanding these anatomical nuances is essential for early diagnosis and appropriate management.

Objective: Constructing a predictive model to evaluate the risk of coronary heart disease (CHD) for early identification of patients with CHD risk based on new metabolic indicators.

Methods: A retrospective analysis was conducted based on NHANES databases. Collect general information, cardiovascular comorbidities, new metabolic indicators (BMI, Triglycerides/Glucose, Waist Circumference-to-Height ratio, Cholesterol/HDL, Triglycerides/HDL, Cardiometabolic index, Neutrophil percentage-to-albumin ratio, etc). The least absolute shrinkage and selection operator (LASSO) regression model and multivariate logistic regression were performed to analyze the risk factors of CHD and develop a CHD risk predictive model using R software.

Results: A total of 3741 individuals were included and 160 (4.3%) individuals had CHD. According to the results of the LASSO regression model and multivariate logistic regression, 9 factors were related to CHD such as Hypertension (Yes), Cardiometabolic index (≥0.672), Mean arterial pressure (<70 mmHg), Gender (male), COPD (Yes), Age (>69), Neutrophil percentage-to-albumin ratio (≥1.465), Thyroid problem (Yes) and Stroke (Yes), which were developed a CHD risk prediction nomogram. The nomogram presented good discrimination with a C-index value of 0.869 (95% confidence interval: 0.82196-0.91604), AUC (0.868) and good calibration. Based on the maximum point of the Youden index, the individuals with a score greater than 136.5 are at high risk for CHD.

Conclusion: A risk prediction model for CHD has been developed based on new metabolic indicators in this study and boasts a relatively high accuracy in the early identification of patients with CHD risk. It may help clinicians develop strategies to prevent CHD and improve care quality.