Purpose: Assessment of cardiovascular (CV) risk with a predictive algorithm is recommended for managing CV disease prevention. The aim of this study was to assess the predictive accuracy of the European Society of Cardiology SCORE among French people.
Methods: Our analysis was based on the Third French MONICA population-based survey (1995-1996) and on a sample of subjects referred (from 1995 to 2000) for a CV checkup in a preventive cardiology unit. Vital status was obtained 10 years after inclusion. The 10-year predicted risk of CV death was calculated using the SCORE equation for low-risk countries and was compared with the 10-year incidence of CV death observed in the cohort.
Results: The sample was composed of 6915 participants aged 35 to 64 years, among whom 56 CV deaths occurred during the followup. The median risk SCORE (0.97%) did not differ from the 10-year incidence of CV death observed in the cohort (1.05%; 95% CI, 0.81-1.37). The median risk SCORE calculated for different categories of sex, age, educational level, family history of premature CV disease, physical activity, impaired fasting glucose, smoking, systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol did not differ from the 10-year incidence of CV death observed in these categories. The C-statistic of the SCORE equation was 79% (73-85). Using a 5% threshold to discriminate people at high risk, 93% of participants were correctly classified (subjects with SCORE ≥5% who died from a CV causes during followup and those with SCORE <5% who did not).
Conclusions: Among middle-aged French people, the SCORE equation adequately predicts CV death.
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http://dx.doi.org/10.1097/HCR.0000000000000148 | DOI Listing |
Cardiovasc Diabetol
January 2025
Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Background: Existing cardiovascular risk prediction models still have room for improvement in patients with type 2 diabetes who represent a high-risk population. This study evaluated whether adding metabolomic biomarkers could enhance the 10-year prediction of major adverse cardiovascular events (MACE) in these patients.
Methods: Data from 10,257 to 1,039 patients with type 2 diabetes from the UK Biobank (UKB) and the German ESTHER cohort, respectively, were used for model derivation, internal and external validation.
Sci Rep
January 2025
Orthopedics Department, The First Affiliated Hospital of Army Medical University, Chongqing, China.
The aim of this study is to elucidate the disparities in survival and risk factors among different subtypes of liposarcoma, through analysis of epidemiological and prognostic data. The study cohort consisted of 12,822 patients diagnosed with liposarcoma in the United States between 2000 and 2021, whose data were retrieved from the Surveillance, Epidemiology, and End Results (SEER) program. The prognosis for different subtypes of liposarcoma and the associated factors such as age, tumor stage, intervention, gender, tumor grade, location, size, chemotherapy and radiotherapy, were retrieved from the database.
View Article and Find Full Text PDFNurs Health Sci
March 2025
College of Nursing, Pusan National University, Yangsan, Republic of Korea.
This study aimed to externally validate two 10-year stroke risk prediction models: one developed in Korea (Model 1) and the other in China (Model 2), using community-based cohort data. Data from 8432 participants in Model 1 and 8915 participants in Model 2 were analyzed. Stroke risk was calculated based on each model's equations, and model performance was assessed using the area under the receiver operating characteristic curve (AUC).
View Article and Find Full Text PDFCMAJ
January 2025
Schools of Health and Wellbeing (Nakada, Pell, Ho), and Cardiovascular and Metabolic Health (Welsh, Celis-Morales), University of Glasgow, Glasgow, UK; Human Performance Laboratory, Education, Physical Activity and Health Research Unit (Celis-Morales), Universidad Católica del Maule, Talca, Chile; Centro de Investigación en Medicina de Altura (CEIMA) (Celis-Morales), Universidad Arturo Prat, Iquique, Chile.
Background: Anxiety and depression are associated with cardiovascular disease (CVD). We aimed to investigate whether adding measures of anxiety and depression to the American Heart Association Predicting Risk of Cardiovascular Disease Events (PREVENT) predictors improves the prediction of CVD risk.
Methods: We developed and internally validated risk prediction models using 60% and 40% of the cohort data from the UK Biobank, respectively.
Objective: To describe demographics, causative pathogens, hospitalization, mortality, and antimicrobial resistance of bacterial bloodstream infections (BSIs) among beneficiaries in the global U.S. Military Health System (MHS), a single-provider healthcare system with 10-year longitudinal follow-up.
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