Journal of clinical monitoring and computing
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J Clin Monit Comput · Feb 2022
Frontal electroencephalogram based drug, sex, and age independent sedation level prediction using non-linear machine learning algorithms.
Brain monitors which track quantitative electroencephalogram (EEG) signatures to monitor sedation levels are drug and patient specific. There is a need for robust sedation level monitoring systems to accurately track sedation levels across all drug classes, sex and age groups. Forty-four quantitative features estimated from a pooled dataset of 204 EEG recordings from 66 healthy adult volunteers who received either propofol, dexmedetomidine, or sevoflurane (all with and without remifentanil) were used in a machine learning based automated system to estimate the depth of sedation. ⋯ Nonlinear machine-learning models using quantitative EEG features can accurately predict sedation levels. The results obtained in this study may provide a useful reference for developing next generation EEG based sedation level prediction systems using advanced machine learning algorithms. Clinical trial registration: NCT02043938 and NCT03143972.
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J Clin Monit Comput · Feb 2022
Safety aspects of the PiCCO thermodilution-cardiac output catheter during magnetic resonance imaging at 3 Tesla.
Thermodilution cardiac output monitoring, using a thermistor-tipped intravascular catheter, is used in critically ill patients to guide hemodynamic therapy. Often, these patients also need magnetic resonance imaging (MRI) for diagnostic or prognostic reasons. As thermodilution catheters contain metal, they are considered MRI-unsafe and advised to be removed prior to investigation. ⋯ No magnetically induced catheter displacements were observed. Under the tested circumstances, no heating or dislocation of the PiCCO™ catheter was observed in a tissue mimicking phantom during 3T-MRI. Leaving the catheter in the critically ill patient during MRI investigation might pose a lower risk of complications than catheter removal and replacement.
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J Clin Monit Comput · Dec 2021
Clinical TrialEEG-derived pain threshold index for prediction of postoperative pain in patients undergoing laparoscopic urological surgery: a comparison with surgical pleth index.
Recently a novel pain recognition indicator derived from electroencephalogram(EEG) signals, pain threshold index(PTI) has been developed. The aim of this study was to determine whether PTI can be used for prediction of postoperative acute pain while surgical pleth index(SPI) applied as control. Eighty patients undergoing laparoscopic urological surgery under general anesthesia were enrolled. ⋯ Further analysis indicated that PTI had a best predictive accuracy reflected by highest area under curve (AUC)(0.772, 95% CI: 0.661-0.860)with sensitivity(62.50%) and specificity(90.91%) and a best positive predictive value(83.3%,95% CI: 68.4-98.2%). PTI obtained at the end of surgery, which have better predictive accuracy for postoperative pain than SPI, could differentiate the patients with moderate-to-severe pain from those with mild pain after they awaken from anesthesia. Clinical trial registration Chinese Clinical Trials Registry: ChiCTR1900024789.
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J Clin Monit Comput · Dec 2021
Feasibility study of a smartphone pupillometer and evaluation of its accuracy.
Measurement of pupillary characteristics, such as pupillary unrest in ambient light, and reflex dilation have been shown to be useful in a variety of clinical situations. Dedicated pupillometers typically capture images in the near-infrared to allow imaging in both light and darkness. However, because a subset of pupillary measurements can be acquired with levels of visible light suitable for conventional cameras, it is theoretically possible to capture data using general purpose cameras and computing devices such as those found on smartphones. ⋯ In 77% of the scans the software was able to successfully identify the pupil and iris. The raw data as well as calculated values of pupillary unrest in ambient light were in clinically acceptable levels of agreement; Bland-Altman analysis of raw pupil measurements yielded a 95% confidence interval of 0.26 mm. In certain situations a smartphone pupillometer may be an appropriate alternative to a commercial pupillometer.
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J Clin Monit Comput · Dec 2021
Clinical TrialComparison of the Conox (qCON) and Sedline (PSI) depth of anaesthesia indices to predict the hypnotic effect during desflurane general anaesthesia with ketamine.
Comparison of two depth of anesthesia indices, qCON (Conox) and PSI (Sedline), during desflurane sedation and their sensitivity to random ketamine boluses in patients undergoing routine surgery. The performance of desflurane and ketamine on both indices was analyzed for 11 patients, and the ketamine sensitivity was compared with another group of 11 patients under sevoflurane and propofol. The MOAA/S was used to determine sedation level and pain. ⋯ However, during desflurane anesthesia the qCON index did not change significantly after ketamine administration, qCON (before = 33 (4), after = 30 (17); Wilcoxon, p = 0.89), while the PSI experienced a significant increase, PSI (before = 31(6), after = 39(16) Wilcoxon, p = 0.013). This study shows that qCON and PSI have similar performance under desflurane with good discrimination between the awake and anesthetized states. While both indices exhibited similar behavior under ketamine boluses under a sevoflurane-propofol anesthesia, the qCON index had a better performance under ketamine during desflurane anesthesia.