The prognostic value of central systolic blood pressure has been established recently. At present, its noninvasive assessment is limited by the need of dedicated equipment and trained operators. Moreover, ambulatory and home blood pressure monitoring of central pressures are not feasible. An algorithm enabling conventional automated oscillometric blood pressure monitors to assess central systolic pressure could be of value. We compared central systolic pressure, calculated with a transfer-function like method (ARCSolver algorithm), using waveforms recorded with a regular oscillometric cuff suitable for ambulatory measurements, with simultaneous high-fidelity invasive recordings, and with noninvasive estimations using a validated device, operating with radial tonometry and a generalized transfer function. Both studies revealed a good agreement between the oscillometric cuff-based central systolic pressure and the comparator. In the invasive study, composed of 30 patients, mean difference between oscillometric cuff/ARCSolver-based and invasive central systolic pressures was 3.0 mm Hg (SD: 6.0 mm Hg) with invasive calibration of brachial waveforms and -3.0 mm Hg (SD: 9.5 mm Hg) with noninvasive calibration of brachial waveforms. Results were similar when the reference method (radial tonometry/transfer function) was compared with invasive measurements. In the noninvasive study, composed of 111 patients, mean difference between oscillometric cuff/ARCSolver-derived and radial tonometry/transfer function-derived central systolic pressures was -0.5 mm Hg (SD: 4.7 mm Hg). In conclusion, a novel transfer function-like algorithm, using brachial cuff-based waveform recordings, is suited to provide a realistic estimation of central systolic pressure. (Hypertension. 2011;58:825-832.). Online Data Supplement
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PanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R ChinaPanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Man, Ping-Kwan
Cheung, Kit-Leong
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PanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Chinese Univ Hong Kong, Dept Comp Sci & Engn, Shatin, Hong Kong, Peoples R ChinaPanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Cheung, Kit-Leong
Sangsiri, Nawapon
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PanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Chinese Univ Hong Kong, Dept Comp Sci & Engn, Shatin, Hong Kong, Peoples R ChinaPanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Sangsiri, Nawapon
Shek, Wilfred Jin
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PanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Kings Coll London, Dept Biomed Sci, London WC2R 2LS, EnglandPanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Shek, Wilfred Jin
Wong, Kwan-Long
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PanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Hong Kong Univ Sci & Technol, Dept Chem & Biol Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R ChinaPanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Wong, Kwan-Long
Chin, Jing-Wei
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PanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Hong Kong Univ Sci & Technol, Dept Chem & Biol Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R ChinaPanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Chin, Jing-Wei
Chan, Tsz-Tai
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PanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Hong Kong Univ Sci & Technol, Dept Chem & Biol Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R ChinaPanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Chan, Tsz-Tai
So, Richard Hau-Yue
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PanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China
Hong Kong Univ Sci & Technol, Dept Chem & Biol Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R ChinaPanopticAI, Hong Kong Sci & Technol Pk, Hong Kong, Peoples R China