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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]
Copyright of Medical Engineering & Physics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Identification of patients prone to hypotension during hemodialysis based on the analysis of cardiovascular signals.
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  Data: <searchLink fieldCode="AR" term="%22Hernando%2C+D%2E%22">Hernando, D.</searchLink><relatesTo>1,2</relatesTo><i> dhernand@unizar.es</i><br /><searchLink fieldCode="AR" term="%22Sörnmo%2C+L%2E%22">Sörnmo, L.</searchLink><relatesTo>3</relatesTo><i> leif.sornmo@bme.lth.se</i><br /><searchLink fieldCode="AR" term="%22Sandberg%2C+F%2E%22">Sandberg, F.</searchLink><relatesTo>3</relatesTo><i> frida.sandberg@bme.lth.se</i><br /><searchLink fieldCode="AR" term="%22Laguna%2C+P%2E%22">Laguna, P.</searchLink><relatesTo>1,2</relatesTo><i> laguna@unizar.es</i><br /><searchLink fieldCode="AR" term="%22Llamedo%2C+M%2E%22">Llamedo, M.</searchLink><relatesTo>1,2</relatesTo><i> llamedom@unizar.es</i><br /><searchLink fieldCode="AR" term="%22Bailón%2C+R%2E%22">Bailón, R.</searchLink><relatesTo>1,2</relatesTo><i> rbailon@unizar.es</i>
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  Data: <searchLink fieldCode="JN" term="%22Medical+Engineering+%26+Physics%22">Medical Engineering & Physics</searchLink>. Dec2015, Vol. 37 Issue 12, p1156-1161. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Hypotension%22">Hypotension</searchLink><br /><searchLink fieldCode="DE" term="%22Hemodialysis+complications%22">Hemodialysis complications</searchLink><br /><searchLink fieldCode="DE" term="%22Heart+beat%22">Heart beat</searchLink><br /><searchLink fieldCode="DE" term="%22Baroreflexes%22">Baroreflexes</searchLink><br /><searchLink fieldCode="DE" term="%22Autonomic+nervous+system%22">Autonomic nervous system</searchLink><br /><searchLink fieldCode="DE" term="%22Diabetes%22">Diabetes</searchLink>
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  Data: 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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  Data: <i>Copyright of Medical Engineering & Physics is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.medengphy.2015.10.003
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        Text: English
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        Type: general
      – SubjectFull: Hemodialysis complications
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      – SubjectFull: Heart beat
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      – SubjectFull: Diabetes
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      – TitleFull: Identification of patients prone to hypotension during hemodialysis based on the analysis of cardiovascular signals.
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              Text: Dec2015
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