Baroreflex sensitivity with different lags and random forests for staging cardiovascular autonomic neuropathy in subjects with diabetes

• Published in: Computers in biology and medicine Vol. 127; p. 104098
• Main Authors: Petry, Daiana, Mirian de Godoy Marques, Claudia, Brum Marques, Jefferson Luiz
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.12.2020; Elsevier Limited
• Subjects: Autonomic nervous system; Baroreceptors; Baroreflex sensitivity; Biomarkers; Blood pressure; Cardiovascular autonomic neuropathy; Classification; Diabetes; Diabetes mellitus; Diabetic neuropathy; Electrocardiography; Heart rate; Heart rate variability; Indexing; Insulin; Internal Medicine; Machine learning; Negative feedback; Nervous system; Other; Patients; Principal components analysis; Quality of life; Random forest; Reflexes; Respiration; Sensitivity; Software; Subclinical CAN; Time lag; Variables; Variance analysis; Cardiovascular autonomic neuropathy; Diabetes mellitus; Machine learning; Baroreflex sensitivity; Subclinical CAN; Random forest; Heart rate variability; baroreflex sensitivity; subclinical CAN; heart rate variability; diabetes mellitus; random forest; machine learning; cardiovascular autonomic neuropathy

Impaired baroreflex sensitivity (BRS) may indicate cardiovascular autonomic neuropathy (CAN), which often remains undiagnosed during the initial course of diabetes mellitus. The baroreflex mechanism can be considered negative feedback because of baroreflex delay, the time delay between a change in b...