Correlation Analysis between Polysomnography Diagnostic Indices and Heart Rate Variability Parameters among Patients with Obstructive Sleep Apnea Hypopnea Syndrome

Xuehao Gong, Leidan Huang, Xin Liu, Chunyue Li, Xuhua Mao, Weizong Liu, Xian Huang, Haiting Chu, Yumei Wang, Wanqing Wu, Jun Lu, Xuehao Gong, Leidan Huang, Xin Liu, Chunyue Li, Xuhua Mao, Weizong Liu, Xian Huang, Haiting Chu, Yumei Wang, Wanqing Wu, Jun Lu

Abstract

Heart rate variability (HRV) can reflect the changes in the autonomic nervous system (ANS) that are affected by apnea or hypopnea events among patients with obstructive sleep apnea hypopnea syndrome (OSAHS). To evaluate the possibility of using HRV to screen for OSAHS, we investigated the relationship between HRV and polysomnography (PSG) diagnostic indices using electrocardiography (ECG) and PSG data from 25 patients with OSAHS and 27 healthy participants. We evaluated the relationship between various PSG diagnostic indices (including the apnea hypopnea index [AHI], micro-arousal index [MI], oxygen desaturation index [ODI]) and heart rate variability (HRV) parameters using Spearman's correlation analysis. Moreover, we used multiple linear regression analyses to construct linear models for the AHI, MI, and ODI. In our analysis, the AHI was significantly associated with relative powers of very low frequency (VLF [%]) (r = 0.641, P = 0.001), relative powers of high frequency (HF [%]) (r = -0.586, P = 0.002), ratio between low frequency and high frequency powers (LF/HF) (r = 0.545, P = 0.049), normalized powers of low frequency (LF [n.u.]) (r = 0.506, P = 0.004), and normalized powers of high frequency (HF [n.u.]) (r = -0.506, P = 0.010) among patients with OSAHS. The MI was significantly related to standard deviation of RR intervals (SDNN) (r = 0.550, P = 0.031), VLF [%] (r = 0.626, P = 0.001), HF [%] (r = -0.632, P = 0.001), LF/HF (r = 0.591, P = 0.011), LF [n.u.] (r = 0.553, P = 0.004), HF [n.u.] (r = -0.553, P = 0.004), and absolute powers of very low frequency (VLF [abs]) (r = 0.525, P = 0.007) among patients with OSAHS. The ODI was significantly correlated with VLF [%] (r = 0.617, P = 0.001), HF [%] (r = -0.574, P = 0.003), LF [n.u.] (r = 0.510, P = 0.012), and HF [n.u.] (r = -0.510, P = 0.012) among patients with OSAHS. The linear models for the PSG diagnostic indices were AHI = -38.357+1.318VLF [%], MI = -13.389+11.297LF/HF+0.266SDNN, and ODI = -55.588+1.715VLF [%]. However, the PSG diagnostic indices were not related to the HRV parameters among healthy participants. Our analysis suggests that HRV parameters are powerful tools to screen for OSAHS patients in place of PSG monitoring.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. The relationship between the frequency…
Fig 1. The relationship between the frequency domain parameters and the AHI with regard to the OSAHS group.
(A) Scatterplot of VLF [%] with AHI; (B) Scatterplot of HF [%] with AHI; (C) Scatterplot of LF/HF with AHI; (D) Scatterplot of LF [n.u.] with AHI; (E) Scatterplot of HF [n.u.] with AHI.
Fig 2. The relationship between the HRV…
Fig 2. The relationship between the HRV domain parameters and the MI regarding the OSAHS group.
(A) Scatterplot of SDNN with MI; (B) Scatterplot of VLF [%] with MI; (C) Scatterplot of HF [%] with MI; (D) Scatterplot of LF/HF with MI; (E) Scatterplot of LF [n.u.] with MI; (F) Scatterplot of HF [n.u.] with MI; (G) Scatterplot of VLF [abs] with MI.
Fig 3. The relationship between the frequency…
Fig 3. The relationship between the frequency domain parameters and the ODI with regard to the OSAHS group.
(A) Scatterplot of VLF [%] with ODI; (B) Scatterplot of HF [%] with ODI; (C) Scatterplot of LF [n.u.] with ODI; (D) Scatterplot of HF [n.u.] with ODI.

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