Peak systolic blood pressure during preparticipation exercise testing in 12,083 athletes: age, sex, and workload-indexed values and predictors - Pesova, Petra; Jiravska Godula, Bogna; Jiravsky, Otakar; Jelinek, Libor; Sovova, Marketa; Moravcova, Katarina; Ozana, Jaromir; Ranic, Ivan; Neuwirth, Radek; Miklik, Roman; Pekar, Matej; Sknouril, Libor; et al. (Frontiers in Physiology, 2024)
AimAssessment of blood pressure during exercise is routine in athletes, but normal values remain equivocal. This study examines the response of systolic blood pressure (SBP) to exercise in a large cohort of athletes and establishes normative values by sex and age.MethodsCompetitive athletes free of cardiovascular disease underwent pre-participation exercise testing on a bicycle ergometer. Resting (SBPrest) and peak blood pressure (SBPpeak), heart rate (HRrest and HRpeak), and power output (WR) were recorded. Workload indexed values were calculated.ResultsThe cohort included 12,083 athletes (median age 15 years, 26.9% female). Median peak exercise SBP was similar between sexes, but WR-indexed measures including SBP/WR ratio and SBP/(WR/kg) slope were higher in females (0.9 vs. 0.7, p < 0.001; 10.94 vs. 9.52, p < 0.001). Univariate analyses revealed significant associations between SBPpeak and several predictors, including sex, age, weight, height, SBPrest, DBPrest, HRrest, HRpeak, and WR (all p < .001). Multivariate analysis showed that SBPrest (beta = 0.353, 95% CI [0.541, 0.609], p < 0.001), height (beta = 0.303, 95% CI [0.360, 0.447], p < 0.001), WR (beta = 0.171, 95% CI [0.029, 0.045], p < 0.001), and age (beta = 0.093, 95% CI [0.162, 0.241], p < 0.001) were the strongest predictors of SBPpeak.ConclusionThis study provides reference values for the interpretation of SBP responses to exercise in athletes. Multivariate analyses highlight the complex interplay of factors influencing peak SBP, including SBPrest, height, WR, age, DBPrest, sex, endurance sport category, and weight. In future studies, these findings may inform the development of personalised training strategies and risk stratification models in athletic populations.