Literature DB >> 30110047

Heart Rate Variability in Coexisting Diabetes and Hypertension.

Paula F Martinez1, Marina P Okoshi2.   

Abstract

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Year:  2018        PMID: 30110047      PMCID: PMC6078364          DOI: 10.5935/abc.20180118

Source DB:  PubMed          Journal:  Arq Bras Cardiol        ISSN: 0066-782X            Impact factor:   2.000


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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 diabetic patients 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 diabetic patients. 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-hypertensive diabetic patients. 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 diabetic patients. 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.
  13 in total

1.  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.

Authors: 
Journal:  Eur Heart J       Date:  1996-03       Impact factor: 29.983

Review 2.  Heart rate variability today.

Authors:  Borejda Xhyheri; Olivia Manfrini; Massimiliano Mazzolini; Carmine Pizzi; Raffaele Bugiardini
Journal:  Prog Cardiovasc Dis       Date:  2012 Nov-Dec       Impact factor: 8.194

Review 3.  Heart rate variability in risk stratification of cardiac patients.

Authors:  Heikki V Huikuri; Phyllis K Stein
Journal:  Prog Cardiovasc Dis       Date:  2013-08-12       Impact factor: 8.194

4.  Heart rate variability and plasma biomarkers in patients with type 1 diabetes mellitus: Effect of a bout of aerobic exercise.

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

Review 5.  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.

Authors:  Roberto Sassi; Sergio Cerutti; Federico Lombardi; Marek Malik; Heikki V Huikuri; Chung-Kang Peng; Georg Schmidt; Yoshiharu Yamamoto
Journal:  Europace       Date:  2015-07-14       Impact factor: 5.214

6.  Heart rate variability and non-linear dynamics in risk stratification.

Authors:  Juha S Perkiömäki
Journal:  Front Physiol       Date:  2011-11-09       Impact factor: 4.566

Review 7.  Nonlinear systems in medicine.

Authors:  John P Higgins
Journal:  Yale J Biol Med       Date:  2002 Sep-Dec

8.  Resting heart rate variability and exercise capacity in Type 1 diabetes.

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

9.  Comparative study of cardiac autonomic status by heart rate variability between under-treatment normotensive and hypertensive known type 2 diabetics.

Authors:  Jayesh D Solanki; Sanket D Basida; Hemant B Mehta; Sunil J Panjwani; Bhakti P Gadhavi
Journal:  Indian Heart J       Date:  2016-08-02

10.  Association of cardiovascular risk using non-linear heart rate variability measures with the framingham risk score in a rural population.

Authors:  Herbert F Jelinek; Hasan Md Imam; Hayder Al-Aubaidy; Ahsan H Khandoker
Journal:  Front Physiol       Date:  2013-07-26       Impact factor: 4.566

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  2 in total

1.  Inter and Intra-Rater Reliability of Short-Term Measurement of Heart Rate Variability on Rest in Diabetic Type 2 Patients.

Authors:  Daniela Bassi; Aldair Darlan Santos-de-Araújo; Patrícia Faria Camargo; Almir Vieira Dibai-Filho; Moyrane Abreu da Fonseca; Renata Gonçalves Mendes; Audrey Borghi-Silva
Journal:  J Med Syst       Date:  2018-10-16       Impact factor: 4.460

2.  Hypertension attenuates the link of osteoprotegerin to reduced baroreflex sensitivity in type 2 diabetes mellitus patients on oral antidiabetic and antihypertensive therapy - a cross sectional study.

Authors:  A Naga Sailaja; Nivedita Nanda; B S Suryanarayana; G K Pal
Journal:  BMC Endocr Disord       Date:  2022-09-09       Impact factor: 3.263

  2 in total

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