Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2021
Letter Meta AnalysisComparison between laryngeal handshake and palpation techniques in the identification of cricothyroid membrane: a meta-analysis.
Because the use of conventional digital palpation technique for the identification of cricothyroid membrane (CTM) has been widely believed to be unreliable, the 'laryngeal handshake' technique (LH) has been introduced for CTM identification in the event of cricothyroidotomy. To provide evidence for clinical practice, this pilot meta-analysis aimed at investigating whether identification of CTM with the LH is superior to that with the palpation technique. Studies that evaluated the accuracy of CTM identification by using LH or palpation techniques (i.e., LH group vs. ⋯ Four studies published from 2018 to 2020 were considered relevant and were read in full. We found no significant difference in success rate of CTM identification [Risk Ratio (RR) 1.09, 95% CI 0.89-1.34, p = 0.41] between the two groups. These preliminary results of the current study demonstrated no significant differences in success rate between the laryngeal handshake and conventional palpation techniques in cricothyroid membrane identification.
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J Clin Monit Comput · Oct 2021
Randomized Controlled TrialPostoperative respiratory state assessment using the Integrated Pulmonary Index (IPI) and resultant nurse interventions in the post-anesthesia care unit: a randomized controlled trial.
Although postoperative adverse respiratory events, defined by a decrease in respiratory rate (RR) and/or a drop in oxygen saturation (SpO2), occur frequently, many of such events are missed. The purpose of the current study was to assess whether continuous monitoring of the integrated pulmonary index (IPI), a composite index of SpO2, RR, end-tidal PCO2 and heart rate, alters our ability to identify and prevent adverse respiratory events in postoperative patients. Eighty postoperative patients were subjected to continuous respiratory monitoring during the first postoperative night using RR and pulse oximetry and the IPI monitor. Patients were randomized to receive intervention based on standard care (observational) or based on the IPI monitor (interventional). ⋯ Compared to the observational group, the use of the IPI monitor led to an increase in the number of interventions performed by nurses to improve the respiratory status of the patient (average 13 versus 39 interventions, p < 0.001). This difference was associated with a significant reduction of the median number of events per patient (2.5 versus 6, p < 0.05) and a shorter median duration of events (62 s versus 75 s, p < 0.001). The use of the IPI monitor in postoperative patients did not result in a reduction of the number of patients experiencing adverse respiratory events, compared to standard clinical care. However, it did lead to an increased number of nurse interventions and a decreased number and duration of respiratory events in patients that experienced postoperative adverse respiratory events.
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J Clin Monit Comput · Oct 2021
Technical considerations when using the EEG export of the SEDLine Root device.
Electroencephalographic (EEG) patient monitoring during general anesthesia can help to assess the real-time neurophysiology of unconscious states. Some monitoring systems like the SEDLine Root allow export of the EEG to be used for retrospective analysis. We show that changes made to the SEDLine display during recording affected the recorded EEG. ⋯ Changing the display settings results in undocumented changes in EEG amplitude, sampling rate, and signal quality. The occult nature of these changes could make the analysis of data sets difficult if not invalid. We strongly suggest researchers adequately define and keep the EEG display settings to export good quality EEG and to ensure comparability among patients.
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J Clin Monit Comput · Oct 2021
Quantitative assessment of consciousness during anesthesia without EEG data.
Assessing the depth of anesthesia (DoA) is a daily challenge for anesthesiologists. The best assessment of the depth of anesthesia is commonly thought to be the one made by the doctor in charge of the patient. This evaluation is based on the integration of several parameters including epidemiological, pharmacological and physiological data. ⋯ This protocol constitutes the very first step on the way towards a multimodal approach of anesthesia. The fact that our first classifier already demonstrated a good predictability is very encouraging for the future. Indeed, this first model was merely a proof of concept to encourage research ways in the field of machine learning and anesthesia.