Journal of clinical monitoring and computing
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J Clin Monit Comput · Dec 2020
Observational StudyAccuracy of the non-invasive Tcore™ temperature monitoring system to measure body core temperature in abdominal surgery.
An accurate determination of body core temperature is crucial during surgery in order to avoid and treat hypothermia, which is associated with poor outcome. In a prospective observational study, we evaluated the suitability of the Tcore™ device (Drägerwerk AG & Co. KGaA, Lübeck, Germany)-a non-invasive thermometer-to accurately determine core body temperature. ⋯ In a repeated-measurements version of the Bland and Altman test, a bias of - 0.02 °C and 95% limits of agreement of - 0.48 to 0.44 °C were calculated. In a population analysis, a median absolute error of 0 [- 0.1; + 0.1] °C, a bias of 0 [- 0.276; 0.271] % and an inaccuracy of 0.276 [0.274; 0.354] % was determined. Although the Tcore™ sensor was attached to the frontal skin, it provided an accurate measurement of core body temperature in the investigated intraoperative setting.
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J Clin Monit Comput · Dec 2020
Performance of a capnodynamic method estimating cardiac output during respiratory failure - before and after lung recruitment.
Respiratory failure may cause hemodynamic instability with strain on the right ventricle. The capnodynamic method continuously calculates cardiac output (CO) based on effective pulmonary blood flow (COEPBF) and could provide CO monitoring complementary to mechanical ventilation during surgery and intensive care. The aim of the current study was to evaluate the ability of a revised capnodynamic method, based on short expiratory holds (COEPBFexp), to estimate CO during acute respiratory failure (LI) with high shunt fractions before and after compliance-based lung recruitment. ⋯ Bias (levels of agreement) and percentage error between COEPBFexp and COTS changed from 0.5 (- 0.5 to 1.5) L/min and 30% at HLP5 to - 0.6 (- 2.3 to 1.1) L/min and 39% during LIP5 and finally 1.1 (- 0.3 to 2.5) L/min and 38% at LIPadj. Concordance during CO changes improved from 87 to 100% after lung recruitment and PEEP adjustment. COEPBFexp could possibly be used for continuous CO monitoring and trending in hemodynamically unstable patients with increased shunt and after recruitment manoeuvre.
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J Clin Monit Comput · Dec 2020
Randomized Controlled TrialHierarchical Poincaré analysis for anaesthesia monitoring.
Although the degree of dispersion in Poincaré plots of electroencephalograms (EEG), termed the Poincaré-index, detects the depth of anaesthesia, the Poincaré-index becomes estranged from the bispectral index (BIS) at lighter anaesthesia levels. The present study introduces Poincaré-index20-30 Hz, targeting the 20- to 30-Hz frequency, as the frequency range reported to contain large electromyogram (EMG) portions in frontal EEG. We combined Poincaré-index20-30 Hz with the conventional Poincaré-index0.5-47 Hz using a deep learning technique to adjust to BIS values, and examined whether this layered Poincaré analysis can provide an index of anaesthesia level like BIS. ⋯ We then evaluated the trained MLPNN model using the test dataset, by comparing the measured BIS (mBIS) with BIS predicted from the model (PredBIS). The relationship between mBIS and PredBIS using the two Poincaré-indices showed a tight linear regression equation: mBIS = 1.00 × PredBIS + 0.15, R = 0.87, p < 0.0001, root mean square error (RMSE) = 7.09, while the relationship between mBIS and PredBIS simply using the original Poincaré-index0.5-47 Hz was weaker (R = 0.82, p < 0.0001, RMSE = 7.32). This suggests the 20- to 30-Hz hierarchical Poincaré analysis has potential to improve on anaesthesia depth monitoring constructed by simple Poincaré analysis.