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Are Complexity Metrics Reliable in Assessing HRV Control in Obese Patients During Sleep?

Cabiddu R, Trimer R, Borghi-Silva A, Migliorini M, Mendes RG, Oliveira AD, Costa FS, Bianchi AM - PLoS ONE (2015)

Bottom Line: Sample entropy, Lempel-Ziv complexity and detrended fluctuation analysis were evaluated and results showed no significant differences among the values calculated over ten-minute signals and longer durations, confirming the reliability of such analysis when performed on short-term signals.Complexity parameters were extracted from ten-minute signal portions selected during wakefulness and different sleep stages on HRV signals obtained from eighteen obese patients and twenty controls.The obese group presented significantly reduced complexity during light and deep sleep, suggesting a deficiency in the control mechanisms integration during these sleep stages.

View Article: PubMed Central - PubMed

Affiliation: DEIB, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.

ABSTRACT
Obesity is associated with cardiovascular mortality. Linear methods, including time domain and frequency domain analysis, are normally applied on the heart rate variability (HRV) signal to investigate autonomic cardiovascular control, whose imbalance might promote cardiovascular disease in these patients. However, given the cardiac activity non-linearities, non-linear methods might provide better insight. HRV complexity was hereby analyzed during wakefulness and different sleep stages in healthy and obese subjects. Given the short duration of each sleep stage, complexity measures, normally extracted from long-period signals, needed be calculated on short-term signals. Sample entropy, Lempel-Ziv complexity and detrended fluctuation analysis were evaluated and results showed no significant differences among the values calculated over ten-minute signals and longer durations, confirming the reliability of such analysis when performed on short-term signals. Complexity parameters were extracted from ten-minute signal portions selected during wakefulness and different sleep stages on HRV signals obtained from eighteen obese patients and twenty controls. The obese group presented significantly reduced complexity during light and deep sleep, suggesting a deficiency in the control mechanisms integration during these sleep stages. To our knowledge, this study reports for the first time on how the HRV complexity changes in obesity during wakefulness and sleep. Further investigation is needed to quantify altered HRV impact on cardiovascular mortality in obesity.

No MeSH data available.


Related in: MedlinePlus

Results of the complexity analysis performed on the control group and on the obese group.a) SE, b) LZC 1, c) LZC 2 and d) DFA mean values (± SD) calculated for the controls (darker bars) and for the obese group (lighter bars) during wakefulness and sleep stages N2, N3 and REM. W denotes significant difference (p-value ≤ 0.05) when compared to wakefulness; N2 denotes significant difference (p-value ≤ 0.05) when compared to N2; N3 denotes significant difference (p-value ≤ 0.05) when compared to N3; the horizontal bar denotes significant difference between the two populations.
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pone.0124458.g003: Results of the complexity analysis performed on the control group and on the obese group.a) SE, b) LZC 1, c) LZC 2 and d) DFA mean values (± SD) calculated for the controls (darker bars) and for the obese group (lighter bars) during wakefulness and sleep stages N2, N3 and REM. W denotes significant difference (p-value ≤ 0.05) when compared to wakefulness; N2 denotes significant difference (p-value ≤ 0.05) when compared to N2; N3 denotes significant difference (p-value ≤ 0.05) when compared to N3; the horizontal bar denotes significant difference between the two populations.

Mentions: A set of non-linear parameters were calculated from the tachogram, for wakefulness and different sleep stages, according to the clinical classification summarized in the hypnogram. The average values of the evaluated HRV non-linear parameters during wakefulness and sleep stages N2, N3 and REM, for the obese and the healthy groups, are shown in Fig 3.


Are Complexity Metrics Reliable in Assessing HRV Control in Obese Patients During Sleep?

Cabiddu R, Trimer R, Borghi-Silva A, Migliorini M, Mendes RG, Oliveira AD, Costa FS, Bianchi AM - PLoS ONE (2015)

Results of the complexity analysis performed on the control group and on the obese group.a) SE, b) LZC 1, c) LZC 2 and d) DFA mean values (± SD) calculated for the controls (darker bars) and for the obese group (lighter bars) during wakefulness and sleep stages N2, N3 and REM. W denotes significant difference (p-value ≤ 0.05) when compared to wakefulness; N2 denotes significant difference (p-value ≤ 0.05) when compared to N2; N3 denotes significant difference (p-value ≤ 0.05) when compared to N3; the horizontal bar denotes significant difference between the two populations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4404104&req=5

pone.0124458.g003: Results of the complexity analysis performed on the control group and on the obese group.a) SE, b) LZC 1, c) LZC 2 and d) DFA mean values (± SD) calculated for the controls (darker bars) and for the obese group (lighter bars) during wakefulness and sleep stages N2, N3 and REM. W denotes significant difference (p-value ≤ 0.05) when compared to wakefulness; N2 denotes significant difference (p-value ≤ 0.05) when compared to N2; N3 denotes significant difference (p-value ≤ 0.05) when compared to N3; the horizontal bar denotes significant difference between the two populations.
Mentions: A set of non-linear parameters were calculated from the tachogram, for wakefulness and different sleep stages, according to the clinical classification summarized in the hypnogram. The average values of the evaluated HRV non-linear parameters during wakefulness and sleep stages N2, N3 and REM, for the obese and the healthy groups, are shown in Fig 3.

Bottom Line: Sample entropy, Lempel-Ziv complexity and detrended fluctuation analysis were evaluated and results showed no significant differences among the values calculated over ten-minute signals and longer durations, confirming the reliability of such analysis when performed on short-term signals.Complexity parameters were extracted from ten-minute signal portions selected during wakefulness and different sleep stages on HRV signals obtained from eighteen obese patients and twenty controls.The obese group presented significantly reduced complexity during light and deep sleep, suggesting a deficiency in the control mechanisms integration during these sleep stages.

View Article: PubMed Central - PubMed

Affiliation: DEIB, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.

ABSTRACT
Obesity is associated with cardiovascular mortality. Linear methods, including time domain and frequency domain analysis, are normally applied on the heart rate variability (HRV) signal to investigate autonomic cardiovascular control, whose imbalance might promote cardiovascular disease in these patients. However, given the cardiac activity non-linearities, non-linear methods might provide better insight. HRV complexity was hereby analyzed during wakefulness and different sleep stages in healthy and obese subjects. Given the short duration of each sleep stage, complexity measures, normally extracted from long-period signals, needed be calculated on short-term signals. Sample entropy, Lempel-Ziv complexity and detrended fluctuation analysis were evaluated and results showed no significant differences among the values calculated over ten-minute signals and longer durations, confirming the reliability of such analysis when performed on short-term signals. Complexity parameters were extracted from ten-minute signal portions selected during wakefulness and different sleep stages on HRV signals obtained from eighteen obese patients and twenty controls. The obese group presented significantly reduced complexity during light and deep sleep, suggesting a deficiency in the control mechanisms integration during these sleep stages. To our knowledge, this study reports for the first time on how the HRV complexity changes in obesity during wakefulness and sleep. Further investigation is needed to quantify altered HRV impact on cardiovascular mortality in obesity.

No MeSH data available.


Related in: MedlinePlus