Paula F Martinez1, Marina P Okoshi2. 1. Faculdade de Fisioterapia, Universidade Federal de Mato Grosso do Sul, Campo Grande - Brazil. 2. Departamento de Clínica Médica - Faculdade de Medicina de Botucatu, Universidade Estadual de São Paulo (UNESP), Botucatu, SP - Brazil.
The autonomic nervous system regulates heart rate through sympathetic and parasympathetic
response to different stimuli. The resultant fluctuation between intervals of
consecutive heart beats, called heart rate variability (HRV), is a valuable tool to
assess autonomic nervous system activity.[1] A decrease in HRV is a marker of reduced parasympathetic and
increased sympathetic tone and has long been considered to negatively impact the
prognosis in cardiovascular disease.[2]In 1996, the European Society of Cardiology and the North American Society of Pacing and
Electrophysiology suggested standards for evaluation, physiological interpretation, and
clinical use for time- and frequency-domain HRV analysis in short- and long-term
recordings.[3] Some nonlinear
measures have been suggested to work better than traditional measures in predicting
future adverse events in several patient groups. More recently, newer computational
tools have been derived from nonlinear dynamics and complex systems.[4] Although the physiological background of
nonlinear measures of HRV is less understood than the conventional measures, it is
speculated that nonlinear dynamics could provide better understanding on nonlinear
behavior commonly occurring within human systems due to their complex dynamic
nature.[5,6] In accordance, a good agreement between some non-linear
HRV measures and the Framingham cardiovascular risk score was observed, suggesting that
they could be used for screening cardiovascular risk.[7] In 2015, the e-Cardiology Working Group of the European Society
of Cardiology and the European Heart Rhythm Association launched a critical review of
new methodologies for analyzing HRV, including entropy rate, fractal scaling and
Poincaré plot, and their application in different
physiological and clinical studies.[8]Alterations in HRV time and frequency domain indices have been frequently observed in
chronic diseases, such as diabetes and hypertension, and associated with cardiac
autonomic dysfunction.[9,10] Since co-existence of diabetes mellitus and systemic
arterial hypertension is very common, some studies have compared HRV between type 2
diabeticpatients with and without hypertension, and found contradictory results using
time-and frequency-domain HRV analysis.[11-13] However, non-linear
dynamics for HRV analysis in type 2 diabetes and hypertension co-existence is still to
be explored.In this issue of the Arquivos Brasileiros de Cardiologia, Bassi et
al.[14] published a study
evaluating the influence of systemic arterial hypertension on cardiac autonomic
modulation and cardiopulmonary capacity in type 2 diabeticpatients. Diabetes subjects
were assigned to a normotensive (n = 32, age = 51 ± 7.5 years) or a hypertensive
group (n = 28, age = 51 ± 6.9 years). Both groups had a poor glycemic control
(normotensive group: glycated hemoglobin = 8.00 ± 2.14%; hypertensive group:
glycated hemoglobin = 8.70 ± 1.60%; p = 0.39) and the hypertensive group had a
higher insulin resistance (normotensive group: insulin resistance index (HOMA-IR) =
diabetes 4.0 ± 4.0; hypertensive group: HOMA-IR = 8.0 ± 6.6; p = 0.02).
The authors found that hypertensive and diabetic subjects had lower SD1 (derived from
Poincaré plot) and Shannon entropy, both non-linear measures
of HRV, in comparison to non-hypertensivediabeticpatients. In addition, SD2 (derived
from Poincaré plot) and approximate entropy correlated
negatively with exercise capacity variables.Although a healthy control group was not evaluated, the results suggest that systemic
arterial hypertension further impairs HRV in diabeticpatients. These data reinforce
epidemiological findings showing that the combination of diabetes mellitus and
hypertension induces greater cardiac remodeling than either condition alone.[15] Furthermore, heart failure is more
prevalent in patients with both diseases. Additional studies are needed to establish the
role of autonomic nerve dysfunction as a predictor of poor prognosis in patients with
co-existing diabetes and hypertension.
Authors: Chadi P Anaruma; Maycon Ferreira; Carlos H G Sponton; Maria A Delbin; Angelina Zanesco Journal: Diabetes Res Clin Pract Date: 2015-11-26 Impact factor: 5.602
Authors: Luke C Wilson; Karen C Peebles; Neil A Hoye; Patrick Manning; Catherine Sheat; Michael J A Williams; Gerard T Wilkins; Genevieve A Wilson; James C Baldi Journal: Physiol Rep Date: 2017-04