Predicting cardiac autonomic neuropathy in type I (insulin-dependent) diabetes mellitus

R. S. Jaffe, T. T. Aoki, P. L. Rohatsch, E. A. Disbrow, D. L. Fung

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


A total of 24 subjects with type I insulin-dependent diabetes mellitus were studied. Cardiac parasympathetic function was measured by supine heart rate variability (HRV) in the respiratory frequency 0.10-0.50 Hz and the sympathetic index was measured as the ratio of HRV between 0.055 and 0.098 Hz to that between 0.004 and 0.5 Hz. Factors assessing diabetic control and complications, and factors unrelated to diabetes but possibly influencing HRV, were recorded. Association with depressed HRV was assessed with correlation, and prediction of depressed HRV was determined with multiple regression. Factors associated with depressed HRV but not independently predictive were renal dysfunction and elevated thyroid stimulating hormone. Elevated glycosylated haemoglobin was not significantly correlated with depressed HRV. Four factors (presence of diabetic retinopathy, male gender, duration of diabetes and increasing age) were significant in the regression and sufficed to predict 81% of the sample variance. The relative weights (β) were -0.65, 0.40, -0.40 and 0.26, respectively. Supine sympathetic index was not sufficient to demonstrate sympathetic dysfunction. It is proposed that the regression model may be used to identify patients likely to have cardiac parasympathetic autonomic dysfunction.

Original languageEnglish (US)
Pages (from-to)155-158
Number of pages4
JournalClinical Autonomic Research
Issue number3
StatePublished - Jun 1995


  • diabetic neuropathies
  • Fourier analysis
  • heart rate
  • parasympathetic nervous system
  • regression analysis
  • sympathetic nervous system

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Neurology


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