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July 17, 2014EntropyOpen Access

Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects

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Why the study?

Does short time multi-scale entropy (sMSE) using 600 points preserve sensitivity in differentiating PWV signal complexity among healthy and diabetic subjects compared to conventional MSE?

Population

94 subjects including healthy young and middle-aged without known cardiovascular disease, and middle-aged…

Comparison

Short time multi-scale entropy analysis of pulse… vs Conventional multi-scale entropy analysis using…

Design

Other

Authors

HWHsien–Tsai WuCentral South UniversityHCHong‐Ruei ChenNational Dong Hwa UniversityALAn‐Bang LiuAmyotrophic Lateral Sclerosis Association

Discussion

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Implication

May enable shorter PWV recordings clinically; leaves open validation for routine diabetes stratification.

Structured PICO

Does short time multi-scale entropy (sMSE) using 600 points preserve sensitivity in differentiating PWV signal complexity among healthy and diabetic subjects compared to conventional MSE?

P
Population
94 subjects including healthy young (n=24) and middle-aged (n=30) without known cardiovascular disease, and middle-aged individuals with well-controlled (n=18) and poorly-controlled (n=22) type 2 diabetes mellitus.
I
Intervention
Short time multi-scale entropy (sMSE) analysis of pulse wave velocity (PWV) signals using 600 consecutive points (~10 min data acquisition).
C
Comparator
Conventional multi-scale entropy (MSE) analysis using 1000 points (20 min) and 600 points.
O
Outcome
Sensitivity in differentiating the complexity of PWV signals among the subject groups.surrogate

The sMSE method halves the required data acquisition time for PWV analysis to approximately 10 minutes while maintaining the ability to differentiate between healthy and diabetic patients.

Cite This Study

Wu et al. (2014) studied this question.

synapsesocial.com/papers/6a7f95bf97addb7815406a29https://doi.org/10.3390/e16074032
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