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Identification of patients prone to hypotension during hemodialysis based on the analysis of cardiovascular signals.

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Title: Identification of patients prone to hypotension during hemodialysis based on the analysis of cardiovascular signals.
Authors: Hernando, D.1,2 dhernand@unizar.es, Sörnmo, L.3 leif.sornmo@bme.lth.se, Sandberg, F.3 frida.sandberg@bme.lth.se, Laguna, P.1,2 laguna@unizar.es, Llamedo, M.1,2 llamedom@unizar.es, Bailón, R.1,2 rbailon@unizar.es
Source: Medical Engineering & Physics. Dec2015, Vol. 37 Issue 12, p1156-1161. 6p.
Subjects: Hypotension, Hemodialysis complications, Heart beat, Baroreflexes, Autonomic nervous system, Diabetes
Abstract: Intradialytic hypotension (IDH) is a major complication during hemodialysis treatment, and therefore it is highly desirable to identify, at an early stage during treatment, whether the patient is prone to IDH. Heart rate variability (HRV), blood pressure variability (BPV) and baroreflex sensitivity (BRS) were analyzed during the first 30 min of treatment to assess information on the autonomic nervous system. Using the sequential floating forward selection method and linear classification, the set of features with the best discriminative power was selected, resulting in an accuracy of 92.1%. Using a classifier based on the HRV features only, thereby avoiding that continuous blood pressure has to be recorded, accuracy decreased to 90.2%. The results suggest that an HRV-based classifier is useful for determining whether a patient is prone to IDH at the beginning of the treatment. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Intradialytic hypotension (IDH) is a major complication during hemodialysis treatment, and therefore it is highly desirable to identify, at an early stage during treatment, whether the patient is prone to IDH. Heart rate variability (HRV), blood pressure variability (BPV) and baroreflex sensitivity (BRS) were analyzed during the first 30 min of treatment to assess information on the autonomic nervous system. Using the sequential floating forward selection method and linear classification, the set of features with the best discriminative power was selected, resulting in an accuracy of 92.1%. Using a classifier based on the HRV features only, thereby avoiding that continuous blood pressure has to be recorded, accuracy decreased to 90.2%. The results suggest that an HRV-based classifier is useful for determining whether a patient is prone to IDH at the beginning of the treatment. [ABSTRACT FROM AUTHOR]
ISSN:13504533
DOI:10.1016/j.medengphy.2015.10.003