Influence of diabetes on autonomic function in children: analysis through the geometr ic indices

Autores

  • Thais Roque Giacon Programa de Pós Graduação em Fisioterapia. Faculdade de Ciências e Tecnologia (FCT/UNESP) - Presidente Prudente (SP), Brazil
  • Franciele Marques Vanderlei Professor Doutor do Departamento de Fisioterapia. Faculdade de Ciências e Tecnologia (FCT/UNESPS) - Presidente Prudente (SP), Brazil.
  • Anne Kastelianne França da Silva Programa de Pós Graduação em Fisioterapia. Faculdade de Ciências e Tecnologia (FCT/UNESP) - Presidente Prudente (SP), Brazil
  • Natália Turri da Silva Programa de Pós Graduação em Fisioterapia. Faculdade de Ciências e Tecnologia (FCT/UNESP) - Presidente Prudente (SP), Brazil
  • Vitor Engrácia Valenti Professor Doutor do Departamento de Fonoaudiologia. Faculdade de Filosofi a e Ciências (FFC/UNESP) - Marília (SP), Brazil.
  • Luiz Carlos Marques Vanderlei Professor Doutor do Departamento de Fisioterapia. Faculdade de Ciências e Tecnologia (FCT/UNESPS) - Presidente Prudente (SP), Brazil.

DOI:

https://doi.org/10.7322/jhgd.113728

Palavras-chave:

Diabetes Mellitus Type 1. Child. Autonomic Nervous System.

Resumo

Introduction: Diabetes mellitus type 1 has been established as one of the most common noncommunicable diseases among children, diabetic autonomic dysfunction presenting as one of its most frequent complications, however, few studies have evaluated autonomic modulation through heart rate variability in diabetic children. Objective: To analyze the autonomic modulation in children with diabetes mellitus type 1. Methods: Data from 36 children of both sexes were analyzed, who were divided into two groups: Diabetes mellitus type 1, n = 13 (11.62 ± 2.18) with a diagnosis of Diabetes mellitus type 1 and control, n = 23 (11.04 ± 1.02) without the disease. Initially personal data, weight, height, heart rate and blood pressure were collected. Subsequently, for the analysis of autonomic modulation, the heart rate beatto-beat was captured using a heart rate monitor in the supine position for 30 minutes. The geometric indices (RRtri, TINN, Poincaré plot) were calculated to analyze autonomic modulation. The Student t test for parametric data or the Mann-Whitney test for nonparametric data, with a 5% signifi cance level, were used for comparison between groups. Results: The results demonstrated a reduction in RRtri, TINN, SD1 and SD2 in diabetic children. The SD1/SD2 ratio was similar between groups. In the qualitative analysis of the Poincaré plot, the children with Diabetes mellitus type 1 presented a fi gure with less dispersion of the points when compared to the control children. Conclusion: Children with diabetes mellitus type 1 have reduced overall variability and parasympathetic modulation.

Referências

Sociedade Brasileira de Diabetes (SBD). Diretrizes da Sociedade Brasileira de Diabetes: 2013-2014. São Paulo: Grupo Editorial Nacional; 2014.

Patterson C, Guariguata L, Dahlquist G, Soltész G, Ogle G, Silink M. Diabetes in the young – a global view and worldwide estimates of numbers of children with type 1 diabetes. Diabetes Res Clin Pract. 2014;103(2):161-75. DOI: http://dx.doi.org/10.1016/j.diabres.2013.11.005

Britto TB, Sadala MLA. Diabetes mellitus juvenil: a experiência de familiares de adolescentes e pré-adolescentes. Ciênc Saude Coletiva. 2009;14(3):947-60. DOI: http://dx.doi.org/10.1590/S1413-81232009000300031

Alves RL, Freitas FM, Fernandes ASN, Ferraz SC, Silva E, Côrrea CL, et al. Modulação autonômica e capacidade funcional em indivíduos portadores de diabetes. J Hum Growth Dev. 2012;22(3):321-7. DOI: http://dx.doi. org/10.7322/jhgd.46396

Balcioğlu AS, Müderrisoğlu H. Diabetes and cardiac autonomic neuropathy: clinical manifestations, cardiovascular consequences, diagnosis and treatment. Worl J Diabetes. 2015;6(1):80-91. DOI: http://dx.doi.org/10.4239/wjd.v6.i1.80

Pop-Busui R. Cardiac autonomic neuropathy in Diabetes. A clinical perspective. Diabetes Care. 2010;33(2):434-41. DOI: http://dx.doi.org/10.2337/dc09-1294

Abreu LC. Variabilidade da frequência cardíaca como marcador funcional do desenvolvimento. J Hum Growth Dev. 2012;22(3): 279-82. DOI: http://dx.doi.org/10.7322/jhgd.46712

Santana MDR, Souza ACA, Abreu LC, Valenti VE. Association between oral variables and heart rate variability. Int Arch Med. 2013;6(1):49. DOI: http://dx.doi.org/10.1186/1755-7682-6-49

Silva SAF, Guida HL, Antônio AMS, Vanderlei LCM, Ferreira LL, Abreu LC, et al. Auditory stimulation with music infl uences the geometric indices of heart rate variability in men. Int Arch Med. 2014;7:27. DOI: http://dx.doi.org/10.1186/1755-7682-7-27

Rajendra AU, Paul JK, Kannathal N, Lim CM, Suri JS. Heart rate variability: a review. Med Bio Eng Comput. 2006;44(12):1031-51. DOI: http://dx.doi.org/10.1007/s11517-006-0119-0

Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation. 1996;93(5):1043-65. DOI: http://dx.doi.org/10.1161/01.CIR.93.5.1043

Voss A, Baier V, Schuluz S, Bar KJ. Linear and non linear methods for analyses of cardiovascular variability in bipolar disorders. Transl Psychiatry. 2006;8(5 Pt 1):441-52. DOI: http://dx.doi.org/10.1111/j.1399-5618.2006.00364.x

Vanderlei FM, Rossi RC, Souza NM, Sá DA, Gonçalves TM, Pastre CM, et al. Heart rate variability in healthy adolescentes at rest. J Hum Growth Dev. 2012;22(2);173-78.

Vanderlei LCM, Pastre CM, Freitas Júnior IF, Godoy MF. Índices Geométricos de Variabilidade da Frequência Cardíaca em Crianças Obesas e Eutrófi cas. Arq Bras Card. 2010;95(1):35-40. DOI: http://dx.doi.org/10.1590/S0066-782X2010005000082

Guzik P, Piskorski J, Krauze T, Schneider R, Wesseling KH, Wykretowicz A, et al. Correlations between the poincaré plot and conventional heart rate variability parameters assessed during paced breathing. J Physiol Sci. 2007;57(1):63-71. DOI: http://dx.doi.org/10.2170/physiolsci.RP005506

Gardim CB, Oliveira BAP, Bernardo AFB, Gomes RL, Pacagnelli FL, Lorençoni RMR, et al. Variabilidade da frequência cardíaca em crianças com diabetes melito tipo 1. Rev Paul Pediar. 2014;32(2):279-85. DOI: http://dx.doi.org/10.1590/0103-0582201432215513

Chen S, Lee Y, Chiu H. Impact of physical activity on heart rate variability in children with type 1 diabetes. Childs Nerv Syst. 2008;24(6):741-7. DOI: http://dx.doi.org/10.1007/s00381-007-0499-y

Kardelen F, Akçurin G, Ertug H, Akçurin S, Bircan I. Heart rate variability and circadian variations in type 1 diabetes mellitus. Pediatr Diabetes. 2006;7(1):45-50. DOI: http://dx.doi.org/10.1111/j.1399-543X.2006.00141.x

Lucini D, Zuccotti G, Malacarne M, Scaramuzza A, Riboni S, Palombo C, et al. Early progression of the autonomic dysfunction observed in pediatric type 1 diabetes mellitus. Hypertension. 2009;54(5):987-94. DOI: http://dx.doi.org/10.1161/hypertensionaha.109.140103

Özgür S, Ceylan Ö, Senocak F, Örün UA, Dogan V, Yilmaz O, et al. An evaluation of heart rate variability and its modifying factors in children with type 1 diabetes. Cardiol Young. 2014;24(5):872-9. DOI: http://dx.doi.org/10.1017/S1047951113001224

Vanderlei L, Silva R, Pastre C, Azevedo F, Godoy M. Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains. Braz J Med Biol Res. 2008;41(10):854-59. DOI:http://dx.doi.org/10.1590/S0100-879X2008005000039

Gamelin F, Berthoin S, Bosquet L. Validity of the polar s810 heart rate monitor to measure R-R intervals at rest. Med Sci Sports Exerc. 2006;38(5):887-93. DOI: http://dx.doi.org/10.1249/01.mss.0000218135.79476.9c

Sociedade Brasileira de Cardiologia; Sociedade Brasileira de Hipertensão; Sociedade Brasileira de Nefrologia. VI Diretrizes brasileiras de hipertensão. Arq Bras Cardiol. 2010; 95(1 supl 1):1-3. DOI: http://dx.doi.org/10.1590/S0066-782X2010001700001

Associação Brasileira para o Estudo da Obesidade e da Síndrome Metabólica (Abeso) Diretrizes Brasileiras de Obesidade: 2009/2010. 3ed. São Paulo: AC Farmacêutica; 2009; p.1-83.

Porto LG, Junqueira Jr LF. Comparison of time-domain short-term heart interval variability analysis using a wristworn heart rate monitor and the conventional electrocardiogram. Pacing Clin Electrophysiol. 2009;32(1):43-51. DOI: http://dx.doi.org/10.1111/j.1540-8159.2009.02175.x

Vanderlei FM, Vanderlei LCM, Garner DM. Heart rate dynamics by novel chaotic globals to HRV in obese youths. J Hum Growth Dev. 2015;25(1):82-8. DOI: http://dx.doi.org/10.7322/jhgd.96772

Niskasen JP, Tarvainen MP, Ranta-Aho PO, Karjalainen PA. Software for advanced HRV analysis. Comput Methods Programs Biomed. 2004;76(1):73-81. DOI: http://dx.doi.org/10.1016/j.cmpb.2004.03.004

Tulppo MP, Huikuri HV, Tutungi E, Kimmerly DS, Gelb AW, Hughson RL, et al. Feedback effects of circulating norepinephrine on sympathetic outfl ow in healthy subjects. Am J Physiol Heart Circ Physiol. 2005;288(2):705-10. DOI: http://dx.doi.org/10.1152/ajpheart.00540.2004

Barreto GS, Vanderlei FM, Vanderlei LCM, Garner DM. Risk Appraisal by novel chaotic globals to HRV in subjects with malnutrition. J Hum Growth Dev. 2014;24(3):243-8. DOI: http://dx.doi.org/10.7322/jhdg.88900

Souza ACA, Cisternas JR, Abreu LC, Roque AL, Monteiro CBM, Adami F, et al. Fractal correlation property of heart rate variability in response to the postural change maneuver in healthy women. Int Arch Med. 2014;7:25. DOI: http://dx.doi.org/10.1186/1755-7682-7-25

Ranasinghe DC, Ranasinghe P, Jayawardena R, Matthews DR, Katulanda P. Evaluation of physical activity among adults with diabetes mellitus from Sri Lanka. Int Arch Med. 2014;7:15. DOI: http://dx.doi.org/10.1186/1755-7682-7-15

Publicado

2016-04-28

Edição

Seção

Artigos Originais