000071103 001__ 71103
000071103 005__ 20190709135513.0
000071103 0247_ $$2doi$$a10.1007/s10439-017-1864-y
000071103 0248_ $$2sideral$$a99504
000071103 037__ $$aART-2017-99504
000071103 041__ $$aeng
000071103 100__ $$0(orcid)0000-0003-4068-127X$$aBolea, Juan$$uUniversidad de Zaragoza
000071103 245__ $$aPulse rate and transit time analysis to predict hypotension events after spinal anesthesia during programmed cesarean labor
000071103 260__ $$c2017
000071103 5060_ $$aAccess copy available to the general public$$fUnrestricted
000071103 5203_ $$aProphylactic treatment has been proved to reduce hypotension incidence after spinal anesthesia during cesarean labor. However, the use of pharmacological prophylaxis could carry out undesirable side-effects on mother and fetus. Thus, the prediction of hypotension becomes an important challenge. Hypotension events are hypothesized to be related to a malfunctioning of autonomic nervous system (ANS) regulation of blood pressure. In this work, ANS responses to positional changes of 51 pregnant women programmed for a cesarean labor were explored for hypotension prediction. Lateral and supine decubitus, and sitting position were considered while electrocardiographic and pulse photoplethysmographic signals were recorded. Features based on heart rate variability, pulse rate variability (PRV) and pulse transit time (PTT) analysis were used in a logistic regression classifier. The results showed that PRV irregularity changes, assessed by approximate entropy, from supine to lateral decubitus, and standard deviation of PTT in supine decubitus were found as the combination of features that achieved the best classification results sensitivity of 76%, specificity of 70% and accuracy of 72%, being normotensive the positive class. Peripheral regulation and blood pressure changes, measured by PRV and PTT analysis, could help to predict hypotension events reducing prophylactic side-effects in the low-risk population.
000071103 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T96$$9info:eu-repo/grantAgreement/ES/ISCIII/FIS/PI10-02851$$9info:eu-repo/grantAgreement/ES/MINECO/TEC2013-42140-R$$9info:eu-repo/grantAgreement/ES/MINECO/TIN2013-41998-R$$9info:eu-repo/grantAgreement/ES/MINECO/TIN2014-5356-R
000071103 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000071103 590__ $$a3.405$$b2017
000071103 591__ $$aENGINEERING, BIOMEDICAL$$b16 / 78 = 0.205$$c2017$$dQ1$$eT1
000071103 592__ $$a1.042$$b2017
000071103 593__ $$aBiomedical Engineering$$c2017$$dQ1
000071103 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000071103 700__ $$0(orcid)0000-0001-8742-0072$$aLázaro, Jesús$$uUniversidad de Zaragoza
000071103 700__ $$0(orcid)0000-0001-7285-0715$$aGil, Eduardo$$uUniversidad de Zaragoza
000071103 700__ $$aRovira, Eva
000071103 700__ $$aRemartínez, José M.$$uUniversidad de Zaragoza
000071103 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, Pablo$$uUniversidad de Zaragoza
000071103 700__ $$0(orcid)0000-0002-1960-407X$$aPueyo, Esther$$uUniversidad de Zaragoza
000071103 700__ $$0(orcid)0000-0002-6410-0495$$aNavarro, Augusto
000071103 700__ $$0(orcid)0000-0003-1272-0550$$aBailón, Raquel$$uUniversidad de Zaragoza
000071103 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000071103 7102_ $$11005$$2410$$aUniversidad de Zaragoza$$bDpto. Farmacología y Fisiolog.$$cÁrea Fisiología
000071103 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000071103 773__ $$g45, 9 (2017), 2253–2263$$pAnn. biomed. eng.$$tANNALS OF BIOMEDICAL ENGINEERING$$x0090-6964
000071103 8564_ $$s483007$$uhttps://zaguan.unizar.es/record/71103/files/texto_completo.pdf$$yPostprint
000071103 8564_ $$s38781$$uhttps://zaguan.unizar.es/record/71103/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000071103 909CO $$ooai:zaguan.unizar.es:71103$$particulos$$pdriver
000071103 951__ $$a2019-07-09-11:53:35
000071103 980__ $$aARTICLE