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by Keyword: Hypoxia rat model

Romero, D, Jané, R, (2021). Global and Transient Effects of Intermittent Hypoxia on Heart Rate Variability Markers: Evaluation using an Obstructive Sleep Apnea Model Ieee Access 9, 19043-19052

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