Pulse Rate and Transit Time Analysis to Predict Hypotension Events After Spinal Anesthesia During Programmed Cesarean Labor
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.
KeywordsHeart rate variability Nonlinear analysis Pulse rate Pulse transit time Hypotension Cesarean section
This work was funded under Projects TEC2013-42140-R, TIN2013-41998-R and TIN2014-53567-R by MINECO (Spain) and by BSICOS Group (T96) from Government of Aragón and European Social Fund (EU), and by ISCIII, Spain, through Project PI10/02851(FIS). CIBER is a center of the Instituto de Salud Carlos III in assistance from the European Regional Development Fund. The computation was performed by the ICTS “NANBIOSIS”, more specifically by the High Performance Computing Unit of the CIBER in Bioengineering, Biomaterials & Nanomedicine (CIBER-BBN) at the University of Zaragoza.
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