Pulse rate and transit time analysis to predict hypotension events after spinal anesthesia during programmed cesarean labor

Bolea, Juan (Universidad de Zaragoza) ; Lázaro, Jesús (Universidad de Zaragoza) ; Gil, Eduardo (Universidad de Zaragoza) ; Rovira, Eva ; Remartínez, José M. (Universidad de Zaragoza) ; Laguna, Pablo (Universidad de Zaragoza) ; Pueyo, Esther (Universidad de Zaragoza) ; Navarro, Augusto ; Bailón, Raquel (Universidad de Zaragoza)
Pulse rate and transit time analysis to predict hypotension events after spinal anesthesia during programmed cesarean labor
Resumen: Prophylactic 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.
Idioma: Inglés
DOI: 10.1007/s10439-017-1864-y
Año: 2017
Publicado en: ANNALS OF BIOMEDICAL ENGINEERING 45, 9 (2017), 2253–2263
ISSN: 0090-6964

Factor impacto JCR: 3.405 (2017)
Categ. JCR: ENGINEERING, BIOMEDICAL rank: 16 / 78 = 0.205 (2017) - Q1 - T1
Factor impacto SCIMAGO: 1.042 - Biomedical Engineering (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T96
Financiación: info:eu-repo/grantAgreement/ES/ISCIII/FIS/PI10-02851
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TEC2013-42140-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2013-41998-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2014-5356-R
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)
Área (Departamento): Área Fisiología (Dpto. Farmacología y Fisiolog.)
Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)

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