Jun Sugawara1, Koichiro Hayashi2, Hirofumi Tanaka3. 1. Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan. 2. Department of Health and Physical Education, Kokugakuin University, Kanagawa, Japan. 3. Cardiovascular Aging Research Laboratory, Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, Texas, USA.
Abstract
BACKGROUND: Carotid-femoral pulse wave velocity (cfPWV) is the most established measure of central arterial stiffness and is calculated by dividing the distance travelled by the pulse wave by the pulse transit time. However, there is no universally accepted standardized measurement of pulse travel distance for cfPWV. This study sought to assess validity and convertibility of 2 most frequently used travel distance estimations, and create the simple and useful conversion equation to unify cfPWV values obtained with different methodologies for pulse travel distance. METHODS: In a total of 227 adults, cfPWV was calculated using 2 different pulse travel distances: suprasternum-femoral distance minus suprasternum-carotid distance (the subtraction method) and carotid-femoral straight distance × 0.8 (the 80% method). They were compared against 3D arterial tracing via magnetic resonance imaging (MRI). RESULTS: The subtraction method underestimated travel distance and cfPWV by 8.7% although correlations with the MRI reference values were significant. The 80% method provided more reliable cfPWV, showing a stronger linearity (r = 0.96, P < 0.0001) and a better agreement with the MRI-based reference value (+0.02±0.54 m/s). Values of cfPWV were influenced primarily by pulse transit time, explaining ~80% of the variation in cfPWV, and the contribution of pulse travel distance was relatively small irrespective of how the travel distance was measured. After the application of the conversion factor (the 80% method = the subtraction method × 1.1), cfPWV values obtained with both methods were strongly correlated and estimation errors were comparable (+0.03±0.75 m/s). CONCLUSION: Our findings indicate that the subtraction method and the 80% method can provide equivalent cfPWV values by the application of a simple conversion factor.
BACKGROUND: Carotid-femoral pulse wave velocity (cfPWV) is the most established measure of central arterial stiffness and is calculated by dividing the distance travelled by the pulse wave by the pulse transit time. However, there is no universally accepted standardized measurement of pulse travel distance for cfPWV. This study sought to assess validity and convertibility of 2 most frequently used travel distance estimations, and create the simple and useful conversion equation to unify cfPWV values obtained with different methodologies for pulse travel distance. METHODS: In a total of 227 adults, cfPWV was calculated using 2 different pulse travel distances: suprasternum-femoral distance minus suprasternum-carotid distance (the subtraction method) and carotid-femoral straight distance × 0.8 (the 80% method). They were compared against 3D arterial tracing via magnetic resonance imaging (MRI). RESULTS: The subtraction method underestimated travel distance and cfPWV by 8.7% although correlations with the MRI reference values were significant. The 80% method provided more reliable cfPWV, showing a stronger linearity (r = 0.96, P < 0.0001) and a better agreement with the MRI-based reference value (+0.02±0.54 m/s). Values of cfPWV were influenced primarily by pulse transit time, explaining ~80% of the variation in cfPWV, and the contribution of pulse travel distance was relatively small irrespective of how the travel distance was measured. After the application of the conversion factor (the 80% method = the subtraction method × 1.1), cfPWV values obtained with both methods were strongly correlated and estimation errors were comparable (+0.03±0.75 m/s). CONCLUSION: Our findings indicate that the subtraction method and the 80% method can provide equivalent cfPWV values by the application of a simple conversion factor.
Authors: Federica Cuomo; Sara Roccabianca; Desmond Dillon-Murphy; Nan Xiao; Jay D Humphrey; C Alberto Figueroa Journal: PLoS One Date: 2017-03-02 Impact factor: 3.240
Authors: Brandon G Fico; Kathleen B Miller; Leonardo A Rivera-Rivera; Adam T Corkery; Andrew G Pearson; Nicole A Eisenmann; Anna J Howery; Howard A Rowley; Kevin M Johnson; Sterling C Johnson; Oliver Wieben; Jill N Barnes Journal: Front Cardiovasc Med Date: 2022-02-09