title: Identification of patients prone to hypotension during hemodialysis based on the analysis of cardiovascular signals.
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.
authors.affiliation: Biomedical Signal Interpretation & Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain. Electronic address: dhernand@unizar.es.
authors.forename: D
authors.initials: D
authors.lastname: Hernando
authors.affiliation: Signal Processing Group, Department of Biomedical Engineering and Center for Integrative Electrocardiology, Lund University, Lund, Sweden. Electronic address: leif.sornmo@bme.lth.se.
authors.forename: L
authors.initials: L
authors.lastname: Sörnmo
authors.affiliation: Signal Processing Group, Department of Biomedical Engineering and Center for Integrative Electrocardiology, Lund University, Lund, Sweden. Electronic address: frida.sandberg@bme.lth.se.
authors.forename: F
authors.initials: F
authors.lastname: Sandberg
authors.affiliation: Biomedical Signal Interpretation & Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain. Electronic address: laguna@unizar.es.
authors.forename: P
authors.initials: P
authors.lastname: Laguna
authors.affiliation: Biomedical Signal Interpretation & Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain. Electronic address: llamedom@unizar.es.
authors.forename: M
authors.initials: M
authors.lastname: Llamedo
authors.affiliation: Biomedical Signal Interpretation & Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain. Electronic address: rbailon@unizar.es.
authors.forename: R
authors.initials: R
authors.lastname: Bailón
mesh_terms: D000368:Aged; D017704:Baroreflex; D001794:Blood Pressure; D060467:Disease Resistance; D004198:Disease Susceptibility; D005260:Female; D006321:Heart / Q000503:physiopathology*; D006339:Heart Rate; D006801:Humans; D007022:Hypotension / Q000209:etiology* / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D006435:Renal Dialysis / Q000009:adverse effects*
keywords: Baroreflex sensitivity; Blood pressure variability; Diabetes; Heart rate variability; Hemodialysis; Intradialytic hypotension; Linear classifier