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Related Concept Videos

Assessment of the Cardiovascular System I: Subjective Data01:23

Assessment of the Cardiovascular System I: Subjective Data

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...
Coronary Artery Disease I: Introduction01:30

Coronary Artery Disease I: Introduction

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...
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

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...
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:

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Related Experiment Video

Updated: Jun 19, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Mapping the Evidence on Cardiovascular Disease Risk among Individuals Experiencing Disability: A Scoping Review.

Yan Xu1,2, Elena Koelbener2, Oscar H Franco3

  • 1Swiss Paraplegic Research, Nottwil, Switzerland.

American Journal of Physical Medicine & Rehabilitation
|June 17, 2026
PubMed
Summary
This summary is machine-generated.

Cardiovascular disease risk in complex disabling conditions like TBI and MS is under-researched. Evidence is fragmented, highlighting a need for standardized definitions and broader representation in future studies.

Keywords:
Cardiovascular DiseaseDisabilityRisk FactorsStroke

Related Experiment Videos

Last Updated: Jun 19, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Area of Science:

  • Neurology
  • Cardiology
  • Public Health
  • Disability Studies

Background:

  • Growing interest in cardiovascular disease (CVD) risk among individuals with complex and disabling health conditions.
  • Limited understanding of CVD risk factors and outcomes in populations with traumatic brain injury (TBI), multiple sclerosis (MS), spinal cord injury (SCI), cerebral palsy (CP), spina bifida (SB), and poliomyelitis.

Purpose of the Study:

  • To map existing evidence on CVD risk in individuals with complex disabling health conditions.
  • Identify research gaps to guide future investigations.

Main Methods:

  • Scoping review following an established framework and pre-registered protocol.
  • Searched MEDLINE, Embase, Web of Science, and Google Scholar.
  • Descriptive synthesis of data from 38 observational studies (over 1.6 million individuals).

Main Results:

  • Evidence base is limited, fragmented, and geographically uneven.
  • Most studies compared these populations to the general population, focusing on stroke.
  • Little attention paid to within-group determinants of CVD risk.

Conclusions:

  • Literature shows increasing interest but suffers from methodological heterogeneity and uneven condition representation.
  • Future research requires standardized disability definitions and consistent diagnostic criteria.
  • Improved reporting of patient-level factors and broader representation across impairment groups and regions are crucial.