title: Assessment of vascular aging and atherosclerosis in hypertensive subjects: second derivative of photoplethysmogram versus pulse wave velocity.
abstract: The pulse wave velocity (PWV) and the photoplethysmogram (PTG) are noninvasive methods for evaluating the pulse wave. The PWV has been associated with age and arterial hypertension, and an index of the second derivative of PTG (SDPTG) is correlated with age and other risk factors for atherosclerosis. The aim of this study was to compare SDPTG and PWV concerning the influencing factors of vascular compliance, including age and atherosclerosis, in a large hypertensive population. We studied consecutively 524 essential hypertensives, 140 with atherosclerotic alterations (AA), defined on the basis of clinical events including coronary heart disease, peripheral vascular disease, stroke, and abdominal aorta aneurysm. The PWV carotid-femoral was measured by a Complior device and the SDPTG was recorded by Fukuda FCP-3166. The augmentation index (AUI) of PTG was defined as the ratio of the late systolic peak to that of the early systolic peak in the pulse. The SDPTG consists of an a,b,c, and d wave in systole and an e wave in diastole; an SDPTG aging index (AI) was calculated as (b-c-d-e)/a. The patients with AA presented a higher PWV (14.9 +/- 4 m/sec v 12.4 +/- 2 m/sec, P < .001), PTG AUI (0.322 +/- 0.16 v 0.252 +/-0.09, P < .001), and SDPTG AI (-0.093 +/- 0.03 v -0.271 +/- 0.018, P < .001). However, in patients 60 years of age, only PWV remained higher in those with AA, whereas in patients >60 yr, both PWV and SDPTG AI remained higher in those with AA. The PWV was independently influenced by age, systolic blood pressure, glucose, AA, and plasma creatinine, whereas the PTG AUI was influenced by age and systolic pressure and the SDPTG AI by age and AA. In a logistic regression model for the presence of AA, including age, plasma creatinine, smoking, and diastolic BP, PWV was a significant independent determinant of AA, whereas SDPTG-AI weakly entered into the model. This study provides evidence that the aortic PWV reflects better than the SDPTG the modifications of the arterial compliance related to age, blood pressure, and atherosclerosis. However, the SDPTG AI may be useful for evaluation of vascular aging in hypertensives.
authors.affiliation: Department of Internal Medicine and Inserm U 337, Broussais Hospital, Paris, France.
authors.forename: L A
authors.initials: LA
authors.lastname: Bortolotto
authors.forename: J
authors.initials: J
authors.lastname: Blacher
authors.forename: T
authors.initials: T
authors.lastname: Kondo
authors.forename: K
authors.initials: K
authors.lastname: Takazawa
authors.forename: M E
authors.initials: ME
authors.lastname: Safar
mesh_terms: D000368:Aged; D000375:Aging / Q000502:physiology*; D001161:Arteriosclerosis / Q000097:blood / Q000209:etiology / Q000503:physiopathology*; D015415:Biomarkers / Q000097:blood; D001783:Blood Flow Velocity; D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure / Q000502:physiology*; D002339:Carotid Arteries / Q000503:physiopathology*; D003404:Creatinine / Q000097:blood; D005260:Female; D005263:Femoral Artery / Q000503:physiopathology*; D006339:Heart Rate; D006801:Humans; D006973:Hypertension / Q000097:blood / Q000150:complications / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D017156:Photoplethysmography / Q000379:methods; D011379:Prognosis; D011674:Pulse / Q000379:methods; D012307:Risk Factors
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D003404:Creatinine