Identification of patients prone to hypotension during hemodialysis based on the analysis of cardiovascular signals.
(2015) In Medical Engineering & Physics 37(12). p.1156-1161- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8243579
- author
- Hernando, D ; Sörnmo, Leif LU ; Sandberg, Frida LU ; Laguna, P ; Llamedo, M and Bailón, R
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Medical Engineering & Physics
- volume
- 37
- issue
- 12
- pages
- 1156 - 1161
- publisher
- Elsevier
- external identifiers
-
- pmid:26525780
- wos:000366772100006
- scopus:84949559960
- pmid:26525780
- ISSN
- 1873-4030
- DOI
- 10.1016/j.medengphy.2015.10.003
- language
- English
- LU publication?
- yes
- id
- fd94d06a-0a4e-4158-abdf-f39d0a7073f3 (old id 8243579)
- date added to LUP
- 2016-04-01 10:27:29
- date last changed
- 2022-04-12 06:28:10
@article{fd94d06a-0a4e-4158-abdf-f39d0a7073f3, 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.}}, author = {{Hernando, D and Sörnmo, Leif and Sandberg, Frida and Laguna, P and Llamedo, M and Bailón, R}}, issn = {{1873-4030}}, language = {{eng}}, number = {{12}}, pages = {{1156--1161}}, publisher = {{Elsevier}}, series = {{Medical Engineering & Physics}}, title = {{Identification of patients prone to hypotension during hemodialysis based on the analysis of cardiovascular signals.}}, url = {{http://dx.doi.org/10.1016/j.medengphy.2015.10.003}}, doi = {{10.1016/j.medengphy.2015.10.003}}, volume = {{37}}, year = {{2015}}, }