| Summary: | Purpose: Aortic stiffness is predictive of cardiovascular morbidity and mortality. However, the gold standard method for assessing aortic stiffness, carotid-femoral pulse wave velocity, is time-consuming and requires a trained operator. An alternative approach could be to derive an arterial stiffness index (ASI) from the easily measured finger photoplethysmogram (PPG). Our aim was to investigate the performance of PPG-derived ASIs for assessing aortic stiffness.
Methods: An insilico dataset of arterial pulse waves (PWs) was generated using a model of pulse wave propagation (1). PWs were generated for virtual healthy subjects aged 25 to 75. Several simulations were run for each age decade to mimic population-level variation in cardiac and vascular properties. PPG PWs were simulated from blood pressure PWs (2). The dataset was used to design an algorithm to calculate over 30 ASIs described in the literature from the finger PPG. In vivo testing was performed using 6,506 subjects from the Airwave dataset (3) who had triplicate PPG and reference PWV measurements.
Results: In silico and in vivo performances of ASIs, including the stiffness index (SI) and reflection index, varied greatly. The SI performed well in vivo, showing strong correlation with reference PWVs. However, in silico assessment demonstrated that the SI and other ASIs were affected by other cardiac and vascular properties as well as aortic stiffness.
Conclusions: This study identified the best-performing ASIs in both in silico and in vivo datasets. In the future multiple ASIs should be combined to improve performance, since different ASIs have different physiological determinants.
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