Journal of clinical monitoring and computing
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J Clin Monit Comput · Jun 2022
Changes in arterial blood pressure characteristics following an extrasystolic beat or a fast 50 ml fluid challenge do not predict fluid responsiveness during cardiac surgery.
Prediction of fluid responsiveness is essential in perioperative goal directed therapy, but dynamic tests of fluid responsiveness are not applicable during open-chest surgery. We hypothesised that two methods could predict fluid responsiveness during cardiac surgery based on their ability to alter preload and thereby induce changes in arterial blood pressure characteristics: (1) the change caused by extrasystolic beats and (2) the change caused by a fast infusion of 50 ml crystalloid (micro-fluid challenge). Arterial blood pressure and electrocardiogram waveforms were collected during surgical preparation of the left internal mammary artery in patients undergoing coronary artery bypass surgery. ⋯ Extrasystoles did not predict fluid responsiveness with convincing accuracy in patients undergoing cardiac surgery and changes in arterial waveform indices following a micro-fluid challenge could not predict fluid responsiveness. Given a low number of fluid responders and inherently reduced statistical power, our data does not support firm conclusions about the utility of the extrasystolic method. CLINICAL TRIAL REGISTRATION: Unique identifier: NCT02903316. https://clinicaltrials.gov/ct2/show/NCT02903316?cond=NCT02903316&rank=1 .
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J Clin Monit Comput · Jun 2022
Observational StudyBioreactance-derived haemodynamic parameters in the transitional phase in preterm neonates: a longitudinal study.
Bioreactance (BR) is a novel, non-invasive technology that is able to provide minute-to-minute monitoring of cardiac output and additional haemodynamic variables. This study aimed to determine the values for BR-derived haemodynamic variables in stable preterm neonates during the transitional period. A prospective observational study was performed in a group of stable preterm (< 37 weeks) infants in the neonatal service of Tygerberg Children's Hospital, Cape Town, South Africa. ⋯ To our knowledge, this is the first paper to present longitudinal BR-derived haemodynamic variable data in a cohort of stable preterm infants, not requiring invasive ventilation or inotropic support, during the first 72 h of life. Bioreactance-derived haemodynamic monitoring is non-invasive and offers the ability to simultaneously monitor numerous haemodynamic parameters of global systemic blood flow. Moreover, it may provide insight into transitional physiology and its pathophysiology.
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J Clin Monit Comput · Jun 2022
Perfusion index as an objective measure of postoperative pain in children undergoing adenotonsillectomy: a cohort study.
Postoperative pain in children is usually undertreated because of their inability to complain. While several pain assessment scales have been developed, they have shortcomings such as subjectivity and being observer-dependent. This study aimed to assess the validity of the perfusion index as an objective measure of postoperative pain in children undergoing adenotonsillectomy. ⋯ The ΔPI-pre was an excellent predictor of postoperative pain (AUROC 0.83 with 71% sensitivity, 83% specificity, and a cut-off value of ≥ 0.26). The perfusion index is a good objective measure for predicting the presence of postoperative pain in children undergoing adenotonsillectomy under general anesthesia. Trial registration: ClinicalTrials.gov; ID: (NCT03854604) registered on February 2019.
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J Clin Monit Comput · Jun 2022
Predicting the mortality risk of acute respiratory distress syndrome: radial basis function artificial neural network model versus logistic regression model.
To predict the mortality of acute respiratory distress syndrome (ARDS) by using a radial basis function (RBF) artificial neural network (ANN) model. This study included 217 patients who were admitted between June 2013 and November 2019. The RBF ANN model and logistic regression (LR) model were based on twelve factors related to ARDS. ⋯ LDH, organ failure, SP-D and PaO2/FiO2 were the most important independent variables. The RBF ANN model was more likely to predict the mortality of ARDS than the LR model. In addition, it can extract informative risk factors for ARDS.