Abstract
Body mass index (BMI) is seen as a predictor of cardiovascular disease (CVD) in lipedema patients. A valid predictor of CVD is increased aortic stiffness (IAS), and previous research described IAS in lipedema. However, it is not known if this applies to all patients. In this cross-sectional single-center cohort study, peripheral pulse wave velocity (PWV) as a non-invasive indicator of aortic stiffness was measured in 41 patients with lipedema, irrespective of stage and without pre-existing cardiovascular conditions or a history of smoking and a maximum body mass index (BMI) of 35 kg/m 2. Automatically electrocardiogram-triggered oscillometric sensor technology by the Gesenius-Keller method was used. Regardless of the stage of lipedema disease, there was no significant difference in PWV compared to published standard values adjusted to age and blood pressure. BMI alone is not a predictor of cardiovascular risk in lipedema patients. Measuring other anthropometric factors, such as the waist-hip ratio or waist-height ratio, should be included, and the existing cardiovascular risk factors, comorbidities, and adipose tissue distribution for accurate risk stratification should be taken into account. Automated sensor technology recording the PWV represents a valid and reliable method for health monitoring and early detection of cardiovascular risks.
| Original language | English |
|---|---|
| Article number | 1673 |
| Pages (from-to) | 1-11 |
| Number of pages | 11 |
| Journal | Sensors |
| Volume | 24 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 5 Mar 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Field
- Medical Signal Analysis
Keywords
- oscillometric measurement;
- peripheral vascular stiffness
- lipedema
- Humans
- Vascular Stiffness/physiology
- Pulse Wave Analysis
- Cohort Studies
- Cross-Sectional Studies
- Lipedema/complications
- Cardiovascular Diseases/diagnosis
- Electrocardiography
- Risk Factors
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