Carotid-Femoral Pulse Transit Time Variability Predicted Mortality and Improved Risk Stratification in the Elderly

The carotid-to-femoral pulse wave velocity, determined by pulse transit time (PTT) and distance, is a well-established measure of arterial stiffness and predicts adverse outcomes. However, its predictive value decreases with aging. To explore new risk indicator in the elderly, we investigated if the variation of carotid-to-femoral pulse wave velocity, registered as beat-to-beat variability of carotid-to-femoral PTT (cf-PTT), could predict outcome. Totally 3015 (median age, 72.4 years; 39.6% men) and 1181 (75.6 years; 42.2% men) subjects from communities of Malmo, Sweden, and Shanghai, China, were analyzed, respectively. Continuous pulse waves for 10 seconds were recorded sequentially at carotid and femoral arterial sites with applanation tonometry (SphygmoCor, Atcor, Australia). During a median of 6.6 and 10.2 years, 389 and 427 deaths occurred in the Malmo and Shanghai cohorts, respectively. Each one-SD increase in the log-transformed coefficient of variation of cf-PTT was associated with 24% (95% CI, 13%-37%) and 21% (10%-33%) increased risk for all-cause mortality in the Malmo and Shanghai subjects, and 60% (33%-91%) for cardiovascular mortality in the Malmo subjects. Adding the coefficient of variation of cf-PTT to the models including conventional risk factors and carotid-to-femoral pulse wave velocity significantly (P<0.05) improved prediction for all-cause mortality in both cohorts (integrated discrimination improvement, 0.005-0.008) and cardiovascular mortality in the Malmo cohort (net reclassification improvement, 0.206). In both cohorts, a coefficient of variation of cf-PTT <6% was not associated with increased mortality risk. In conclusion, the beat-to-beat variability of cf-PTT predicted mortality and improved risk stratification, which might be a novel risk indicator for elderly people.

Automated summary

The beat-to-beat variability of carotid-to-femoral pulse wave velocity (cf-PTT) was found to predict mortality and improve risk stratification in elderly individuals, particularly in terms of all-cause mortality and cardiovascular mortality. This could potentially serve as a novel risk indicator for elderly populations.