Minimal Detectable Change in Resting Blood Pressure and Cardiorespiratory Fitness: A Secondary Analysis of a Study on School-Based High-Intensity Interval Training Intervention.
Jarosław DomaradzkiPublished in: Journal of clinical medicine (2023)
High-intensity interval training (HIIT) effects on resting blood pressure (BP) and cardiorespiratory fitness (CRF) have already been studied. Furthermore, the responses of responders and non-responders to HIIT in terms of these physiological outcomes have also been examined. However, the minimal detectable change (MDC) in BP and CRF has not been addressed yet. Therefore, the current study aimed to compare the MDC 90 of BP (systolic and diastolic) and CRF (fitness index (FI) results) in the context of a school-based HIIT program for adolescents. Participants were adolescents, with an average age of 16.16 years (n = 141; 36.6% males). A preplanned secondary analysis was conducted using pre-post data from the control group to estimate MDC 90 . The MDC 90 of SBP, DBP, and FI were 7.82 mm HG, 12.45 mm HG, and 5.39 points, respectively. However, taking into account the relative values of these changes, MDC 90 required a greater change in DBP (17.27%) than FI (12.15%) and SBP (6.68%). Any training-induced physiological changes in the average values of the outcomes did not exceed MDC 90 . However, a comparison of the participants who exceeded and did not exceed MDC 90 showed statistically significant differences. These findings reveal the huge variability in and insensitivity to the intervention effect for all measurements. This is likely because of the large subgroup of participants with low sensitivity to the physiological stimulus. As such, there is a considerable need to create individually tailored intervention programs.
Keyphrases
- blood pressure
- heart rate
- randomized controlled trial
- high intensity
- young adults
- physical activity
- left ventricular
- hypertensive patients
- heart rate variability
- body composition
- metabolic syndrome
- type diabetes
- electronic health record
- gene expression
- single cell
- adipose tissue
- fluorescent probe
- machine learning
- oxidative stress
- skeletal muscle
- living cells
- ejection fraction
- double blind