The effects of mechanical ventilation on heart rate variability and complexity in mice


Pubblicato: Jan 18, 2024
Aggiornato: 2024-01-18
H Kazdağli
HF Ozel
MA Özbek
Abstract

In a variety of diseases, altered respiratory modulation is often an early sign of autonomic dysfunction. Therefore, understanding and evaluating the effects of artificial ventilation on the autonomic nervous system is vital. The effects of artificial ventilation on autonomic balance have been assessed by heart rate variability using frequency domain and non-linear analysis including fractal complexity and entropy analysis in anesthetized mice. BALB/c mice (n=48) were divided into two groups: Spontaneous breathing and artificial ventilation. The electrocardiograms were recorded. Four different analyses were used: i. frequency domain analysis, ii. Poincaré plots, iii. DFA and iv. Entropy analysis. An unpaired t-test was used for statistical analysis. In a ventilated group, VLF and LF parameters were not changed, whereas the HF parameter was decreased compared to spontaneous breathing mice. DFAα1 was significantly increased due to artificial ventilation but DFAα2 was unchanged. SD2/SD1 ratio was increased, however, SD1 and SD2 were not significantly affected. Also, ApEn and SampEn remained unchanged. HF parameter, DFAα1, and SD2/SD1 were affected by artificial ventilation. Decreased HF and increased DFAα1, further support the notion that HRV is dominated by respiratory sinus arrhythmia at high frequencies, this may be due to decreased vagal tone caused by artificial ventilation.

Article Details
  • Sezione
  • Research Articles
Downloads
I dati di download non sono ancora disponibili.
Riferimenti bibliografici
Alluri, R. et al. (2017) ‘Open tracheostomy gastric acid aspiration murine
model of acute lung injury results in maximal acute nonlethal lung
injury’, Journal of Visualized Experiments [Preprint]. Available at:
Ambrosino, N. and Vitacca, M. (2018) ‘The patient needing prolonged
mechanical ventilation: a narrative review.’, Multidisciplinary respiratory medicine, 13, p. 6. Available at: https://doi.org/10.1186/
s40248-018-0118-7.
Bartlett, D. and St. John, W.M. (1988) ‘Influence of lung volume on phrenic, hypoglossal and mylohyoid nerve activities’, Respiration Physiology, 73 (1), pp. 97-109. Available at: https://doi.org/10.1016/0034-
(88)90130-2.
Bernardi, L. et al. (2001) ‘Modulatory effects of respiration’, in Autonomic Neuroscience: Basic and Clinical. Available at: https://doi.
org/10.1016/S1566-0702 (01)00267-3.
Bloomfield, D.M. et al. (2001) ‘Comparison of spontaneous vs. metronome-guided breathing on assessment of vagal modulation using RR
variability’, American Journal of Physiology - Heart and Circulatory Physiology, 280 (3 49-3). Available at: https://doi.org/10.1152/
ajpheart.2001.280.3.h1145.
Borghi-Silva, A. et al. (2008) ‘Noninvasive ventilation acutely modifies heart rate variability in chronic obstructive pulmonary disease
patients.’, Respiratory medicine, 102 (8), pp. 1117-23. Available at:
Brennan, M., Palaniswami, M. and Kamen, P. (2001) ‘Do existing measures of Poincareé plot geometry reflect nonlinear features of heart
rate variability?’, IEEE Transactions on Biomedical Engineering, 48
(11), pp. 1342-1347. Available at: https://doi.org/10.1109/10.959330.
Brennan, M., Palaniswami, M. and Kamen, P. (2002) ‘Poincaré plot interpretation using a physiological model of HRV based on a network
of oscillators’, American Journal of Physiology - Heart and Circulatory Physiology, 283 (5 52-5). Available at: https://doi.org/10.1152/
ajpheart.00405.2000.
Corne, S. and Bshouty, Z. (2005) ‘Basic principles of control of breathing’, Respiratory Care Clinics of North America. W.B. Saunders, pp.
Dabas, P.K. and Shaw, D. (2010) ‘Reliability of frequency domain HRV
analysis’, in IFMBE Proceedings, pp. 1615-1618. Available at:
Delignières, D. and Marmelat, V. (2012) ‘Fractal fluctuations and complexity: Current debates and future challenges’, Critical Reviews in
Biomedical Engineering, 40 (6), pp. 485-500. Available at: https://
doi.org/10.1615/CritRevBiomedEng.2013006727.
Denver, J.W., Reed, S.F. and Porges, S.W. (2007) ‘Methodological issues in the quantification of respiratory sinus arrhythmia’, Biological
Psychology [Preprint]. Available at: https://doi.org/10.1016/j.biopsycho.2005.09.005.
Eckberg, D.L. (1983) ‘Human sinus arrhythmia as an index of vagal cardiac outflow’, Journal of Applied Physiology Respiratory Environmental and Exercise Physiology. Available at: https://doi.org/10.1152/
jappl.1983.54.4.961.
Ewald, A.J., Werb, Z. and Egeblad, M. (2011) ‘Monitoring of vital signs
for long-term survival of mice under anesthesia’, Cold Spring Harbor Protocols [Preprint]. Available at: https://doi.org/10.1101/pdb.
prot5563.
Frazier, S.K., Moser, D.K. and Stone, K.S. (2001) ‘Heart rate variability
and hemodynamic alterations in canines with normal cardiac function
during exposure to pressure support, continuous positive airway pressure, and a combination of pressure support and continuous positive
airway pressure’, Biological research for nursing, 2 (3), pp. 167-174.
Goldberger, A.L. et al. (2002) ‘Fractal dynamics in physiology: Alterations with disease and aging’, Proceedings of the National Academy
of Sciences of the United States of America [Preprint]. Available at:
Gonçalves, H. et al. (2008) ‘Linear and nonlinear heart-rate analysis in
a rat model of acute anoxia’, Physiological Measurement [Preprint].
Gonçalves, H. et al. (2013) ‘Comparison of different methods of heart
rate entropy analysis during acute anoxia superimposed on a chronic rat model of pulmonary hypertension’, Medical Engineering and
Physics [Preprint]. Available at: https://doi.org/10.1016/j.medengphy.2012.06.020.
Grossman, P. and Taylor, E.W. (2007) ‘Toward understanding respiratory sinus arrhythmia: Relations to cardiac vagal tone, evolution and
biobehavioral functions’, Biological Psychology [Preprint]. Available
Guzik, P. et al. (2005) ‘The influence of changing respiratory rate on HRV
is portrayed by descriptors of Poincaré plot analysis’, 11th Congress
of the International Society for Holter and Noninvasive Electrocardiology [Preprint].
Guzik, P. et al. (2007) ‘Correlations between the Poincaré plot and conventional heart rate variability parameters assessed during paced
breathing’, Journal of Physiological Sciences, 57 (1), pp. 63-71.
Haddadian, Z. et al. (2013) ‘Effect of endotoxin on heart rate dynamics in
rats with cirrhosis’, Autonomic Neuroscience: Basic and Clinical, pp.
Iyengar, K. et al. (2020) ‘Challenges and solutions in meeting up the urgent requirement of ventilators for COVID-19 patients’, Diabetes &
metabolic syndrome. 2020/05/05 edn, 14 (4), pp. 499-501. Available
Kitney, R.I. (1980) ‘An analysis of the thermoregulatory influences on
heart-rate variability’, The study of heart rate variability, pp. 81-113.
Lin, T.T. et al. (2016) ‘Proarrhythmic risk and determinants of cardiac
autonomic dysfunction in collagen-induced arthritis rats’, BMC Musculoskeletal Disorders, pp. 1-8. Available at: https://doi.org/10.1186/
s12891-016-1347-6.
Magrans, R. et al. (2013) ‘Complexity of the autonomic heart rate control in coronary artery occlusion in patients with and without prior myocardial infarction, Medical Engineering and Physics, 35 (8),
Malik, M. et al. (1996) ‘Heart rate variability. Standards of measurement,
physiological interpretation, and clinical use. Task Force of the European Society of Cardiology and the North American Society of
Pacing and Electrophysiology.’, European heart journal, 17 (3), pp.
-81.
Malliani, A. et al. (1991) ‘Cardiovascular neural regulation explored in
the frequency domain’, Circulation, 84 (2), pp. 482-492. Available at:
Mandelbrot, B.B. and Aizenman, M. (1979) ‘Fractals: form, chance, and
dimension’, PhT, 32 (5), p. 65.
Melo, H.M. et al. (2018) ‘Ultra-short heart rate variability recording reliability: The effect of controlled paced breathing’, Annals of Noninvasive Electrocardiology [Preprint]. Available at: https://doi.
org/10.1111/anec.12565.
Ozbek, M. (2002) ‘Valve with A Cylinder and A Piston, for A Respirator’.
Pagani, M. et al. (1984) ‘Power spectral density of heart rate variability
as an index of sympatho-vagal interaction in normal and hypertensive
subjects.’, Journal of hypertension. Supplement: official journal of
the International Society of Hypertension, 2 (3), pp. S383-5.
Peng, C.K. et al. (1995) ‘Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series’, Chaos [Preprint]. Available at: https://doi.org/10.1063/1.166141.
Penttilä, J. et al. (2003) ‘Effect of cardiac vagal outflow on complexity
and fractal correlation properties of heart rate dynamics’, Autonomic and Autacoid Pharmacology [Preprint]. Available at: https://doi.
org/10.1046/j.1474-8673.2003.00293.x.
Penzel, T. et al. (2003) ‘Comparison of detrended fluctuation analysis and
spectral analysis for heart rate variability in sleep and sleep apnea’,
IEEE Transactions on biomedical engineering, 50 (10), pp. 1143-1151.
Perakakis, P. et al. (2009) ‘Breathing frequency bias in fractal analysis of
heart rate variability’, Biological Psychology [Preprint]. Available at:
Rothe, C.F. (2011) ‘Venous system: physiology of the capacitance vessels’, Comprehensive Physiology, pp. 397-452.
Roy, S., Goswami, D.P. and Sengupta, A. (2020) ‘Geometry of the Poincaré plot can segregate the two arms of autonomic nervous system - A
hypothesis’, Medical Hypotheses [Preprint]. Available at: https://doi.
org/10.1016/j.mehy.2020.109574.
Sassi, R. et al. (2015) ‘Advances in heart rate variability signal analysis:
joint position statement by the e-Cardiology ESC Working Group and
the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society’, EP Europace, 17 (9), pp. 1341-1353.
Sato, N. et al. (1995) ‘Power Spectral Analysis of Heart Rate Variability
in Healthy Young Women During the Normal Menstrual Cycle’, Psychosomatic Medicine, 57 (4).
Schipke, A.G. (1999) Effect of respiration rate on short-term heart rate
variability, Journal of Clinical and Basic Cardiology.
Schmidt, H. et al. (2005) ‘Autonomic dysfunction predicts mortality in
patients with multiple organ dysfunction syndrome of different age
groups’, Critical care medicine, 33 (9), pp. 1994-2002.
Shaffer, F. and Ginsberg, J.P. (2017) ‘An Overview of Heart Rate Variability Metrics and Norms’, Frontiers in Public Health, 5, p. 258.
da Silva, R.B. et al. (2023) ‘Heart rate variability as a predictor of mechanical ventilation weaning outcomes’, Heart & Lung, 59, pp. 33-
Singh, S. (2010) ‘Pattern analysis of different ECG signal using Pan-Tompkin’s algorithm 1’, International Journal on Computer Science and
Engineering, 02 (07), pp. 2502-2505.
Song, H.S. and Lehrer, P.M. (2003) ‘The effects of specific respiratory
rates on heart rate and heart rate variability’, Applied Psychophysiology Biofeedback, 28 (1), pp. 13-23. Available at: https://doi.
org/10.1023/A:1022312815649.
Tarvainen, M.P. et al. (2014) ‘Kubios HRV - Heart rate variability
analysis software’, Computer Methods and Programs in Biomedicine, 113 (1), pp. 210-220. Available at: https://doi.org/10.1016/j.
cmpb.2013.07.024.
Tayel, M. and AlSaba, E. (2015) ‘Poincaré Plot for Heart Rate Variability’, International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering [Preprint].
Thireau, J. et al. (2008) ‘Heart rate variability in mice: a theoretical and
practical guide’, Experimental Physiology, 93 (1), pp. 83-94. Available at: https://doi.org/10.1113/expphysiol.2007.040733.
Weippert, M. et al. (2015) ‘Effects of breathing patterns and light exercise on linear and nonlinear heart rate variability’, Applied Physiology, Nutrition and Metabolism [Preprint]. Available at: https://doi.
org/10.1139/apnm-2014-0493.
Weiser, T.G. et al. (2008) ‘An estimation of the global volume of surgery: a modelling strategy based on available data’, The Lancet, 372
(9633), pp. 139-144.
Xiuying, M., Abboud, F.M. and Chapleau, M.W. (2002) ‘Analysis of afferent, central, and efferent components of the baroreceptor reflex
in mice’, American Journal of Physiology - Regulatory Integrative
and Comparative Physiology [Preprint]. Available at: https://doi.
org/10.1152/ajpregu.00768.2001.
Yan, B. et al. (2009) ‘Diabetes induces neural degeneration in nucleus ambiguus (NA) and attenuates heart rate control in OVE26 mice’, Experimental Neurology [Preprint]. Available at: https://doi.org/10.1016/j.
expneurol.2009.07.006.
Zerr, C.L. et al. (2015) ‘Does inhalation-to-exhalation ratio matter in heart
rate variability biofeedback?’, in Applied Psychophysiology and Biofeedback. Springer/Plenum Publishers 233 Spring St, New York, NY 10013 USA, p. 135