Is the algorithm used to process heart rate variability data clinically relevant? Analysis in male adolescents

Area of Science:

• Cardiology
• Biomedical Engineering
• Adolescent Health

Background:

• Heart rate variability (HRV) analysis is crucial for assessing cardiovascular risk.
• Different algorithms, such as fast Fourier transform (FFT) and autoregressive (AR) methods, are used for HRV assessment.
• Understanding algorithmic influence on HRV parameters is vital for consistent clinical interpretation in adolescents.

Purpose of the Study:

• To investigate whether the choice of algorithm (FFT vs. AR) impacts the association between HRV parameters and cardiovascular risk factors in male adolescents.
• To compare the influence of FFT and AR methods on the relationship between HRV and anthropometric/hemodynamic measures.

Main Methods:

• A cross-sectional study involving 1,152 male adolescents aged 14-19 years.
• HRV parameters (LF, HF, LF/HF ratio, Total Power) were measured using both FFT and AR methods during supine rest.
• Associations with waist circumference, systolic blood pressure, and body mass index were analyzed.

Main Results:

• Significant differences (p<0.05) were observed in HRV parameters between FFT and AR methods, but with a low effect size (<0.1).
• High intra-class correlation (0.96-0.99) and acceptable variation coefficients (7.4-14.8%) indicate good agreement between methods.
• Both methods showed consistent associations: waist circumference, systolic blood pressure, and BMI were significantly linked to HRV parameters indicative of autonomic balance.

Conclusions:

• While FFT and AR methods produce statistically different HRV values in male adolescents, these differences lack clinical significance.
• Both algorithms demonstrate consistent associations with key cardiovascular risk factors, suggesting interchangeability for this population.
• The findings support the use of either FFT or AR methods for HRV assessment in male adolescents when evaluating cardiovascular risk factors.