OBJECTIVES: Pulse waveform characteristics (Augmentation Index--AIx and pulse wave transit time) are measures of the timing and extent of arterial wave reflections. Although previous studies reported an independent association with cardiovascular morbidity, it remains to be established that waveform characteristics, derived from noninvasive pulse waveform analysis, predict cardiovascular outcomes independent of and additional to brachial blood pressure. METHODS: We prospectively assessed AIx, heart-rate corrected AIx, and pulse wave transit time, using radial applanation tonometry and a validated transfer function to generate the aortic pressure curve, in 520 male patients undergoing coronary angiography. Primary endpoint was a composite of all-cause mortality, myocardial infarction, stroke, cardiac, cerebrovascular, and peripheral revascularization. RESULTS: During a follow-up of 49 months, 170 patients reached the primary endpoint. On the basis of Cox proportional hazards regression models, all pressure waveform characteristics predicted the primary endpoint. A 10% increase of AIx and heart-rate corrected AIx was associated with a 20.5% (95% confidence interval 6.5-36.4, P = 0.003) and 31.4% (95% confidence interval 13.2-52.6, P = 0.0004) increased risk of the primary endpoint, respectively. A 10-ms increase of pulse wave transit time was associated with a 20.8% (95% confidence interval 10.8-29.6, P = 0.0001) lower risk of the primary endpoint. In multiple adjusted models, AIx, heart-rate corrected AIx, and pulse wave transit time were independently associated with the combined endpoint even after adjustments for brachial blood pressure, age, extent of coronary artery disease, clinical characteristics, and medications. CONCLUSION: The study provides evidence that pulse waveform characteristics consistently and independently predict cardiovascular events in coronary patients.
OBJECTIVES: Pulse waveform characteristics (Augmentation Index--AIx and pulse wave transit time) are measures of the timing and extent of arterial wave reflections. Although previous studies reported an independent association with cardiovascular morbidity, it remains to be established that waveform characteristics, derived from noninvasive pulse waveform analysis, predict cardiovascular outcomes independent of and additional to brachial blood pressure. METHODS: We prospectively assessed AIx, heart-rate corrected AIx, and pulse wave transit time, using radial applanation tonometry and a validated transfer function to generate the aortic pressure curve, in 520 male patients undergoing coronary angiography. Primary endpoint was a composite of all-cause mortality, myocardial infarction, stroke, cardiac, cerebrovascular, and peripheral revascularization. RESULTS: During a follow-up of 49 months, 170 patients reached the primary endpoint. On the basis of Cox proportional hazards regression models, all pressure waveform characteristics predicted the primary endpoint. A 10% increase of AIx and heart-rate corrected AIx was associated with a 20.5% (95% confidence interval 6.5-36.4, P = 0.003) and 31.4% (95% confidence interval 13.2-52.6, P = 0.0004) increased risk of the primary endpoint, respectively. A 10-ms increase of pulse wave transit time was associated with a 20.8% (95% confidence interval 10.8-29.6, P = 0.0001) lower risk of the primary endpoint. In multiple adjusted models, AIx, heart-rate corrected AIx, and pulse wave transit time were independently associated with the combined endpoint even after adjustments for brachial blood pressure, age, extent of coronary artery disease, clinical characteristics, and medications. CONCLUSION: The study provides evidence that pulse waveform characteristics consistently and independently predict cardiovascular events in coronary patients.
Authors: Kevin S Heffernan; Eshan A Patvardhan; Navin K Kapur; Richard H Karas; Jeffrey T Kuvin Journal: Eur J Appl Physiol Date: 2011-12-03 Impact factor: 3.078
Authors: Joel L Ramirez; Kimberly A Spaulding; Greg J Zahner; Sukaynah A Khetani; Melinda S Schaller; Warren J Gasper; Nancy K Hills; S Marlene Grenon Journal: J Surg Res Date: 2018-11-01 Impact factor: 2.192
Authors: D Vrachatis; T G Papaioannou; A Konstantopoulou; E G Nasothimiou; S Millasseau; J Blacher; M E Safar; P P Sfikakis; G S Stergiou; A D Protogerou Journal: J Hum Hypertens Date: 2013-10-24 Impact factor: 3.012
Authors: James Faulkner; Louis Martinelli; Kirsty Cook; Lee Stoner; Helen Ryan-Stewart; Eloise Paine; Helen Hobbs; Danielle Lambrick Journal: J Spinal Cord Med Date: 2019-09-16 Impact factor: 1.985