Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Coronary Artery Disease I: Introduction01:30

Coronary Artery Disease I: Introduction

1.8K
Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
1.8K
Assessment of the Cardiovascular System I: Subjective Data01:23

Assessment of the Cardiovascular System I: Subjective Data

1.0K
A thorough health history and physical assessment are essential for identifying cardiovascular disease (CVD) symptoms and distinguishing them from other health issues.
Initial Enquiry
Ask the patient about their primary concern and thoroughly explore all reported symptoms.
Medical History
Investigate past illnesses affecting the cardiovascular system, such as angina, anemia, rheumatic fever, congenital heart disease, stroke, thrombophlebitis, dysrhythmias, varicosities
Inquire about symptoms...
1.0K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

627
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
627
Coronary Artery Disease IV: Preventive Measures01:26

Coronary Artery Disease IV: Preventive Measures

888
Effective preventive measures for coronary artery disease (CAD) focus on controlling modifiable risk factors, including cholesterol abnormalities and lifestyle changes.Cholesterol ManagementFirst, the Mediterranean diet and the American Heart Association advocate for maintaining low-density lipoprotein (LDL) cholesterol levels below 100 mg/dL, with a more stringent recommendation of below 70 mg/dL for individuals at high risk. LDL cholesterol, often termed "bad cholesterol," can lead to the...
888
Type II Diabetes I: Introduction01:26

Type II Diabetes I: Introduction

13
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance, in which target tissues such as the liver, muscle, and adipose tissue respond poorly to insulin. It is also associated with inadequate compensatory insulin secretion, where pancreatic β-cells fail to produce sufficient insulin. Together, these abnormalities lead to persistent hyperglycemia.EtiologyT2DM develops through a complex interaction of genetic predisposition and environmental or...
13
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

965
Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
965

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Lack of association between APOE genotypes and COVID-19 in a black South African cohort.

Scientific reports·2026
Same author

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart Association.

Circulation·2026
Same author

A federated learning framework for ethical dynamic treatment allocation across heterogeneous hospitals.

Journal of biomedical informatics·2026
Same author

Effectiveness of a Participatory Voice Intervention on Psychological Well-Being Among Warehouse Workers: Results From the Fulfillment Center Intervention Study, United States, 2021‒2023.

American journal of public health·2026
Same author

FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport.

Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society·2025
Same author

Work Unit Conditions and Emotional Exhaustion: A Multilevel Study of Healthcare Workers.

Journal of occupational and environmental medicine·2025

Related Experiment Video

Updated: Apr 27, 2026

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
06:04

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome

Published on: September 27, 2024

1.7K

Quantifying cardiometabolic risk using modifiable non-self-reported risk factors.

Miguel Marino1, Yi Li2, Michael J Pencina3

  • 1Department of Family Medicine, Department of Public Health and Preventive Medicine, Division of Biostatistics, Oregon Health Science University, Portland, Oregon.

American Journal of Preventive Medicine
|June 22, 2014
PubMed
Summary

A new cardiometabolic risk score accurately predicts cardiovascular disease (CVD) risk using modifiable factors like HbA1c and BMI. This tool aids in early prevention and health maintenance for individuals.

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K
Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
07:51

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Published on: September 26, 2018

7.1K

Related Experiment Videos

Last Updated: Apr 27, 2026

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
06:04

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome

Published on: September 27, 2024

1.7K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.3K
Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
07:51

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Published on: September 26, 2018

7.1K

Area of Science:

  • Cardiology
  • Preventive Medicine
  • Risk Assessment

Background:

  • Effective tools for assessing cardiometabolic risk factors are crucial for primary prevention.
  • Current assessment methods may not detect subtle changes in modifiable risk factors.

Purpose of the Study:

  • To develop and validate a cumulative cardiometabolic risk score.
  • The score focuses on non-self-reported, modifiable risk factors including glycosylated hemoglobin (HbA1c) and body mass index (BMI).
  • The aim is to detect small changes across multiple risk factors that may not individually reach clinical thresholds.

Main Methods:

  • Prospective follow-up of 2,359 cardiovascular disease-free subjects from the Framingham offspring cohort over 14 years.
  • Utilized baseline measurements of HbA1c and cholesterol.
  • Employed gender-specific Cox proportional hazards models to assess the impact of modifiable risk factors (blood pressure, cholesterol, smoking, BMI, HbA1c) on CVD risk.
  • Developed and evaluated a 10-year general cardiometabolic risk score function.

Main Results:

  • Glycosylated hemoglobin (HbA1c) showed a significant association with general cardiovascular disease (CVD) risk.
  • The developed cardiometabolic risk score demonstrated strong predictive performance.
  • Cross-validated discrimination showed C-indices of 0.703 for men and 0.762 for women.
  • The model exhibited good calibration in both genders.

Conclusions:

  • A novel risk factor algorithm effectively quantifies cardiometabolic risk using modifiable factors.
  • This tool offers a practical method for motivating individuals towards preventive health behaviors.
  • The risk score enhances understanding and management of cardiometabolic health.