Publications

CCBY Intermittent hypoxia (IH) produces autonomic dysfunction that promotes the development of arrhythmia and hypertension in patients with obstructive sleep apnea (OSA). This paper investigated different heart rate variability (HRV) indices in the context of IH using a rat model for OSA. Linear and non-linear HRV parameters were assessed from ultra-short (15-s segments) and short-term (5 min) analyses of heartbeat time-series. Transient changes observed from pre-apnea segments to hypoxia episodes were evaluated, besides the relative and global impact of IH, as a function of its severity. Results showed an overall increase in ultra-short HRV markers as immediate response to hypoxia: standard deviation of normal RR intervals, SDNN=1.2 ms (IQR: 1.1-2.1) vs 1.4 ms (IQR: 1.2-2.2), p=0.015; root mean square of the successive differences, RMSSD=1.7 ms (IQR: 1.5-2.2) vs 1.9 ms (IQR: 1.6-2.4), p=0.031. The power in the very low frequency (VLF) band also showed a significant increase: 0.09 ms2 (IQR: 0.05-0.20) vs 0.16 ms2 (IQR: 0.12-0.23), p=0.016, probably associated with the potentiation of the carotid body chemo-sensory response to hypoxia. Moreover, a clear link between severity of IH and short-term HRV measures was found in VLF and LF power, besides their progressive increase seen throughout the experiment after each apnea sequence. However, only those markers quantifying fragmentation levels in RR series were significantly affected when the experiment ended, as compared to baseline measures: percentage of inflection points, PIP=49% (IQR: 45-51) vs 53% (IQR: 47-53), p=0.031; percentage of short (≥3 RR intervals) accelerated/decelerated segments, PSS=75% (IQR: 51-81) vs 87% (IQR: 51-90), p=0.046. These findings suggest a significant deterioration of cardiac rhythm with a more erratic behavior beyond the normal sinus arrhythmia, that may lead to a future cardiac condition.

JTD Keywords: artificial intelligence, atmospheric modeling, electrocardiography, heart rate variability, hypoxia rat model, intermittent hypoxia, obstructive apneas, protocols, radio access technologies, Artificial intelligence, Atmospheric modeling, Electrocardiography, Heart rate variability, Hypoxia rat model, Intermittent hypoxia, Obstructive apneas, Protocols, Radio access technologies, Rats

In this paper, a non-linear HRV analysis was performed to assess fragmentation signatures observed in heartbeat time series after intermittent hypoxia (IH). Three markers quantifying short-term fragmentation levels, PIP, IALS and PSS, were evaluated on R-R interval series obtained in a rat model of recurrent apnea. Through airway obstructions, apnea episodes were periodically simulated in six anesthetized Sprague-Dawley rats. The number of apnea events per hour (AHI index) was varied during the first half of the experiment while apnea episodes lasted 15 s. For the second part, apnea episodes lasted 5, 10 or 15 s, but the AHI index was fixed. Recurrent apnea was repeated for 15-min time intervals in all cases, alternating with basal periods of the same duration. The fragmentation markers were evaluated in segments of 5 minutes, selected at the beginning and end of the experiment. The impact of the heart and breathing rates (HR and BR, respectively) on the parameter estimates was also investigated. The results obtained show a significant increase (from 5 to 10%, p <; 0.05) in fragmentation measures of heartbeat time series after IH, indicating a clear deterioration of the initial conditions. Moreover, there was a strong linear relationship (r > 0.9) between these markers and BR, as well as with the ratio given by HR/BR. Although fragmentation may be impacted by IH, we found that it is highly dependent on HR and BR values and thus, they should be considered during its calculation or used to normalize the fragmentation estimates.

JTD Keywords: Rats, Time series analysis, Radio access technologies, Protocols, Heart beat