Journal of clinical monitoring and computing
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J Clin Monit Comput · May 2021
LetterConductive heating mattress leads to ECG changes that mimic pacemaker spikes.
Hypothermia is a common perioperative complication. To prevent perioperative hypothermia amongst other things electrical heating mattresses are used. ⋯ In this case the ECG monitoring suddenly showed spikes that looked like spikes from an implanted pacemaker. When turning off the heating mattress the spikes disappeared and returned after turning on the heating mattress again.
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J Clin Monit Comput · Apr 2021
Randomized Controlled TrialPhotoplethysmography-derived approximate entropy and sample entropy as measures of analgesia depth during propofol-remifentanil anesthesia.
The ability to monitor the physiological effect of the analgesic agent is of interest in clinical practice. Nonstationary changes would appear in photoplethysmography (PPG) during the analgesics-driven transition to analgesia. The present work studied the properties of nonlinear methods including approximate entropy (ApEn) and sample entropy (SampEn) derived from PPG responding to a nociceptive stimulus under various opioid concentrations. ⋯ The result showed that low Ceremi (0 and 1 ng·ml-1) could be differentiated from high Ceremi (3 and 5 ng·ml-1) by ApEn and SampEn. Depending on the coefficient employed in algorithm: ApEn with k = 0.15 yielded the largest PK value (0.875) whereas SampEn gained its largest PK of 0.867 with k = 0.2. Thus, PPG-based ApEn and SampEn with appropriate k values have the potential to offer good quantification of analgesia depth under general anesthesia.
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Oxygen gas flowmeters (OGF) are used to regulate the oxygen flow in acute and chronic care. In hospitals, Thorpe tubes (TT) are the classical systems most used for delivering oxygen. In recent years, the oxygen flow restrictor (OFR) has appeared. ⋯ With the increasing flow, some data fell outside the limits of agreement, and the trend increased with the elevated oxygen flow. TTs were less accurate compared to OFRs due to the increased flow variability. However, for TTs and OFRs, as the required flow is elevated, the dispersion of values increases on both sides of the actual flow.
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J Clin Monit Comput · Apr 2021
Observational StudyUltrasonography for predicting a difficult laryngoscopy. Getting closer.
Our objective was to evaluate the usefulness of five ultrasound measurements to predict a difficult laryngoscopy (DL). Prospective observational study. 50 patients underwent scheduled surgery under general anesthesia with orotracheal intubation with classical laryngoscopy at the University Hospital of Jaén (Spain). Sociodemographic variables, classic preintubation screening tests and ultrasound measurements of the neck soft tissue from skin to hyoid (DSH), epiglottis (DSE) and glottis (DSG) were obtained, as well as two measurements derived from the above: DSH + DSE and DSE - DSG. ⋯ It was established that DSE ≥ 3 cm, could predict a DL with a positive predictive value (PPV) of 69.23% [95%CI 40.3-98.2], and DSE - DSG ≥ 1.9 cm would do so with a PPV of 78.57% [95%CI 53.31-100%]. The multivariate analysis endorsed that DSE and DSE - DSG combined with classic tests (the Modified Mallampati score, the thyromental distance and the upper lip bite test) improved the preoperative detection of a DL. The inclusion of DSE and DSE - DSG in a multivariate model with classic parameters may offer the anesthesiologist better information for detecting a DL preoperatively.
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J Clin Monit Comput · Apr 2021
An effective pressure-flow characterization of respiratory asynchronies in mechanical ventilation.
Ineffective effort during expiration (IEE) occurs when there is a mismatch between the demand of a mechanically ventilated patient and the support delivered by a Mechanical ventilator during the expiration. This work presents a pressure-flow characterization for respiratory asynchronies and validates a machine-learning method, based on the presented characterization, to identify IEEs. 1500 breaths produced by 8 mechanically-ventilated patients were considered: 500 of them were included into the training set and the remaining 1000 into the test set. Each of them was evaluated by 3 experts and classified as either normal, artefact, or containing inspiratory, expiratory, or cycling-off asynchronies. ⋯ The software classified IEEs with sensitivity 0.904, specificity 0.995, accuracy 0.983, positive and negative predictive value 0.963 and 0.986, respectively. The Cohen's kappa is 0.983 (with 95% confidence interval (CI): [0.884, 0.962]). The pressure-flow characterization of respiratory cycles and the monitoring technique proposed in this work automatically identified IEEs in real-time in close agreement with the experts.