OBJECTIVE: This study aims to analyze how much heart rate variability (HRV) indices discriminatively respond to age and severity of sleep apnea in the obstructive sleep apnea syndrome (OSAS). METHODS: 176 male OSAS patients were classified into four groups according to their age and apnea-hypopnea index (AHI). The HRV indices were compared via analysis of covariance (ANCOVA). In particular, the partial correlation method was performed to identify the most statistically significant HRV indices in the time and frequency domains. Stepwise multiple linear regressions were further executed to examine the effects of age, AHI, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and sleep parameters on the significant HRV indices. RESULTS: The partial correlation analysis yielded the NN50 count (defined as the number of adjacent R-wave to R-wave intervals differing by more than 50 ms) and low frequency/high frequency (LF/HF) ratio to be two most statistically significant HRV indices in both time and frequency domains. The two indices showed significant differences between the groups. The NN50 count was affected by age (p<0.001) and DBP (p=0.039), while the LF/HF ratio was affected by AHI (p<0.001), the amount of Stage 2 sleep (p=0.005), and age (p=0.021) in the order named in the regression analysis. CONCLUSION: The NN50 count more sensitively responded to age than to AHI, suggesting that the index is mainly associated with an age-related parasympathetic system. On the contrary, the LF/HF ratio responded to AHI more sensitively than to age, suggesting that it is mainly associated with a sympathetic tone likely reflecting the severity of sleep apnea.
OBJECTIVE: This study aims to analyze how much heart rate variability (HRV) indices discriminatively respond to age and severity of sleep apnea in the obstructive sleep apnea syndrome (OSAS). METHODS: 176 male OSAS patients were classified into four groups according to their age and apnea-hypopnea index (AHI). The HRV indices were compared via analysis of covariance (ANCOVA). In particular, the partial correlation method was performed to identify the most statistically significant HRV indices in the time and frequency domains. Stepwise multiple linear regressions were further executed to examine the effects of age, AHI, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and sleep parameters on the significant HRV indices. RESULTS: The partial correlation analysis yielded the NN50 count (defined as the number of adjacent R-wave to R-wave intervals differing by more than 50 ms) and low frequency/high frequency (LF/HF) ratio to be two most statistically significant HRV indices in both time and frequency domains. The two indices showed significant differences between the groups. The NN50 count was affected by age (p<0.001) and DBP (p=0.039), while the LF/HF ratio was affected by AHI (p<0.001), the amount of Stage 2 sleep (p=0.005), and age (p=0.021) in the order named in the regression analysis. CONCLUSION: The NN50 count more sensitively responded to age than to AHI, suggesting that the index is mainly associated with an age-related parasympathetic system. On the contrary, the LF/HF ratio responded to AHI more sensitively than to age, suggesting that it is mainly associated with a sympathetic tone likely reflecting the severity of sleep apnea.
Authors: F L Martinho; R P Tangerina; S M G T Moura; L C Gregório; S Tufik; L R A Bittencourt Journal: Braz J Med Biol Res Date: 2008-12 Impact factor: 2.590
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Authors: R Trimer; R G Mendes; F S M Costa; L M M Sampaio; A Delfino; R Arena; F Aletti; M Ferrario; A Borghi-Silva Journal: Sleep Breath Date: 2013-10-31 Impact factor: 2.816
Authors: Julian P Saboisky; Daniel W Stashuk; Andrew Hamilton-Wright; John Trinder; Sanjeev Nandedkar; Atul Malhotra Journal: PLoS One Date: 2014-08-11 Impact factor: 3.240