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Nonlinear PD2i heart rate complexity algorithm detects autonomic neuropathy in patients with type 1 diabetes mellitus
- Source :
- Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 122(7)
- Publication Year :
- 2010
-
Abstract
- Objective: The aim of this study was to test whether a new heart rate variability (HRV) complexity measure, the Point Correlation Dimension (PD2i), provides diagnostic information regarding early subclinical autonomic dysfunction in diabetes mellitus (DM). We tested the ability of PD2i to detect diabetic autonomic neuropathy (DAN) in asymptomatic young DM patients without overt neuropathy and compared them to age- and gender-matched controls. Methods: HRV in DM type 1 patients (n = 17, 10 female, 7 male) aged 12.9–31.5 years (duration of DM 12.4 ± 1.2 years) was compared to that in a control group of 17 healthy matched probands. The R–R intervals were measured over 1 h using a telemetric ECG system. Results: PD2i was able to detect ANS dysfunction with p = 0.0006, similar to the best discriminating MSE scale, with p = 0.0002. Discussion: The performance of PD2i to detect DAN in asymptomatic DM patients is similar to the best discriminative power of previously published complexity measures. Conclusions: The PD2i algorithm may prove to be an easy to perform and clinically useful tool for the early detection of autonomic neuropathy in DM type 1 patients, especially given its minimal data requirements.
- Subjects :
- Proband
Adult
Male
Adolescent
Entropy
Asymptomatic
Electrocardiography
Young Adult
Diabetic Neuropathies
Heart Rate
Physiology (medical)
Diabetes mellitus
medicine
Heart rate variability
Humans
Child
Subclinical infection
Diabetic Autonomic Neuropathy
Type 1 diabetes
business.industry
medicine.disease
Sensory Systems
Diabetes Mellitus, Type 1
Neurology
Autonomic Nervous System Diseases
Nonlinear Dynamics
Data Interpretation, Statistical
Linear Models
Female
Neurology (clinical)
medicine.symptom
business
Autonomic neuropathy
Algorithm
Algorithms
Subjects
Details
- ISSN :
- 18728952
- Volume :
- 122
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
- Accession number :
- edsair.doi.dedup.....8019eb8be341c09f0a112dc12c298cbc