Objectives: This study aims to assess the correlations among coronary artery calcium (CAC), self-reported exercise, and mortality in asymptomatic patients.
Background: The interaction between reported exercise habits and CAC scores for predicting clinical risk is not yet well known.
Methods: We followed 10,690 asymptomatic patients who underwent CAC scanning. Patients were divided into 4 groups based on a single-item self-reported exercise. Mean follow-up was 8.9 ± 3.5 years for the occurrence of all-cause mortality (ACM).
Results: Annualized ACM progressively increased with increasing CAC score (p < 0.001) and decreasing exercise (p < 0.001). Among patients with CAC scores of 0, ACM was low regardless of the amount of exercise. Among patients with CAC scores from 1 to 399, there was a stepwise increase in ACM for each reported decrement in exercise, and this difference was markedly more pronounced among patients with CAC scores ≥400. Compared with highly active patients with a CAC score of 0, highly sedentary patients with CAC scores ≥400 had a 3.1-fold increase (95% confidence interval: 1.35 to 7.11) in adjusted ACM risk. Our single-item physical activity questionnaire was also predictive of risk factors and clinical and lipid profile measurements.
Conclusions: In asymptomatic patients, self-reported exercise is a significant predictor of long-term outcomes. Prognostic value of the reported exercise is additive to the increasing degree of underlying atherosclerosis. Among patients with high CAC scores, exercise may play a protective role, whereas reported minimal or no exercise substantially increases clinical risk. Our results suggest there is clinical utility for the use of a simple single-item exercise questionnaire for such assessments.
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http://dx.doi.org/10.1016/j.jcmg.2016.12.030 | DOI Listing |
Eur Heart J Digit Health
January 2025
Department of Cardiovascular Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
Aims: Aortic stenosis (AS) is a common and progressive disease, which, if left untreated, results in increased morbidity and mortality. Monitoring and follow-up care can be challenging due to significant variability in disease progression. This study aimed to develop machine learning models to predict the risks of disease progression and mortality in patients with mild AS.
View Article and Find Full Text PDFEur Heart J Digit Health
January 2025
Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, USA.
Aims: Accurate prediction of clinical outcomes following percutaneous coronary intervention (PCI) is essential for mitigating risk and peri-procedural planning. Traditional risk models have demonstrated a modest predictive value. Machine learning (ML) models offer an alternative risk stratification that may provide improved predictive accuracy.
View Article and Find Full Text PDFFront Endocrinol (Lausanne)
January 2025
Department of Neurosurgery, Huzhou Central Hospital, Huzhou, China.
Background: Abnormal thyroid hormone levels may occur in critical illness, which may have an interactive relationship with inflammatory reaction. At present, the relationship between triiodothyronine (T3)/thyroxine (T4) ratio and inflammatory indicators and all-cause mortality of stroke survivors is still unclear.
Methods: We obtained the relevant data of the respondents from 2007 to 2012 through the National Health and Nutrition Examination Survey (NHANES) database for statistical analysis.
Front Med (Lausanne)
January 2025
VA Connecticut Healthcare System, West Haven, CT, United States.
[This corrects the article DOI: 10.3389/fmed.2023.
View Article and Find Full Text PDFOptimal dosing of VTE prophylaxis for specific patient populations remains an area of concern as insufficient evidence exists regarding dosing for underweight patients. The purpose of this study is to compare the incidence of major bleeding events in underweight patients given different prophylactic doses of enoxaparin. This is a retrospective analysis performed at multiple hospitals within a single health care system.
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