2016
DOI: 10.1111/anec.12372
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Application of Heart Rate Variability in Diagnosis and Prognosis of Individuals with Diabetes Mellitus: Systematic Review

Abstract: Although there are methodological differences in indices used, in general, this tool demonstrated good sensitivity and specificity and can be used as an additional and/or complementary tool to the conventional autonomic tests, in order to obtain safer and more effective diagnostic, collaborating for better risk stratification conditions of these patients.

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Cited by 29 publications
(9 citation statements)
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“…Secondly, this finding may be considered as another support for a recently proposed hypothesis that trial-to-trial variability of MEP amplitudes may be by itself an informative measurement of the neuronal state ( Conforto et al, 2012 ). Such hypothesis is in agreement with a well-known role of the variability in the biological systems from the widely used heart rate variability ( Chouchou and Desseilles, 2014 ; França da Silva et al, 2016 ) to the firing rate variability serving an important role in action preparation ( Churchland et al, 2010 ; Klein-Flügge et al, 2013 ). A presence of the correlation between central and peripheral variabilities only for ICF condition could be explained by the fact that ICF phenomenon is likely to be based on multiple synaptic connections ( Di Lazzaro and Ziemann, 2013 ; Ziemann et al, 2015 ).…”
Section: Discussionsupporting
confidence: 89%
“…Secondly, this finding may be considered as another support for a recently proposed hypothesis that trial-to-trial variability of MEP amplitudes may be by itself an informative measurement of the neuronal state ( Conforto et al, 2012 ). Such hypothesis is in agreement with a well-known role of the variability in the biological systems from the widely used heart rate variability ( Chouchou and Desseilles, 2014 ; França da Silva et al, 2016 ) to the firing rate variability serving an important role in action preparation ( Churchland et al, 2010 ; Klein-Flügge et al, 2013 ). A presence of the correlation between central and peripheral variabilities only for ICF condition could be explained by the fact that ICF phenomenon is likely to be based on multiple synaptic connections ( Di Lazzaro and Ziemann, 2013 ; Ziemann et al, 2015 ).…”
Section: Discussionsupporting
confidence: 89%
“…Examples of clinical conditions in which HRV is predictive of patient survival include diabetes, ( 33 ) cancer, ( 34 ) heart failure, ( 35 ) acute myocardial infarction, ( 36 ) stroke, ( 37 ) epilepsy, ( 38 ) Parkinson's disease ( 39 ) and kidney failure, ( 40 ) among others.…”
Section: Discussionmentioning
confidence: 99%
“…The autonomic nervous system modulates the cardiovascular system to cope with physical and physiological challenges through the activities of the sympathetic and parasympathetic nervous systems [ 51 ]. Depressed HRV is a strong and independent predictor of a number of health conditions, including diabetes, metabolic syndrome, and cardiovascular diseases, as well as increased risk of cardiovascular event and all-cause mortality in patients with chronic diseases and healthy populations [ 52 , 53 ]. HRV decreases with aging, and it can also provide important information about the cardiac health of older adults, as abnormalities are also strong predictors of death in this population [ 54 ].…”
Section: Monitoring Cardiac Function and Cardiovascular Healthmentioning
confidence: 99%