Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2022
VACuum INtubation (VACcIN) box restricts the exhaled air dispersion generated by simulated cough: description and simulation-based tests of an innovative aerosolization protective prototype.
The COVID-19 pandemic has caused personal protective equipment shortages worldwide and required healthcare workers to develop novel ways of protecting themselves. Anesthesiologists in particular are exposed to increased risks of contamination when performing interventions such as airway manipulations. We developed and tested an aerosolization protective device which contains aerosols around the patient's airway and helps eliminate particles using negative pressure. ⋯ One minute following simulated cough, the mean number of particles per cubic foot in our box with suction on is around 45% that with the suction off (1,462,373 vs 3,272,080, P < 0.0001) in the negative pressure room, and four times lower than with the suction off (760,380 vs 3,088,700, P < 0.0001) in the positive pressure room. After a simulated cough inside the box, particles can be detected in front of the anesthesiologist's face with a non-airtight device, while none are detected when our box is sealed and its suction turned on. The use of our negative pressure intubation box prevents contamination of surroundings and increases particle elimination, regardless of room pressure.
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J Clin Monit Comput · Oct 2022
Multicenter StudyPredicting hypoglycemia in critically Ill patients using machine learning and electronic health records.
Hypoglycemia is a common occurrence in critically ill patients and is associated with significant mortality and morbidity. We developed a machine learning model to predict hypoglycemia by using a multicenter intensive care unit (ICU) electronic health record dataset. Machine learning algorithms were trained and tested on patient data from the publicly available eICU Collaborative Research Database. ⋯ The best-performing predictive model was the eXtreme gradient boosting model (XGBoost), which achieved an area under the received operating curve (AUROC) of 0.85, a sensitivity of 0.76, and a specificity of 0.76. The machine learning model developed has strong discrimination and calibration for the prediction of hypoglycemia in ICU patients. Prospective trials of these models are required to evaluate their clinical utility in averting hypoglycemia within critically ill patient populations.
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J Clin Monit Comput · Oct 2022
Hypotension Prediction Index with non-invasive continuous arterial pressure waveforms (ClearSight): clinical performance in Gynaecologic Oncologic Surgery.
Intraoperative hypotension (IOH) is common during major surgery and is associated with a poor postoperative outcome. Hypotension Prediction Index (HPI) is an algorithm derived from machine learning that uses the arterial waveform to predict IOH. The aim of this study was to assess the diagnostic ability of HPI working with non-invasive ClearSight system in predicting impending hypotension in patients undergoing major gynaecologic oncologic surgery (GOS). ⋯ Thirty-one patients undergoing GOS were included in the analysis, 28 of which had complete data set. The HPI predicted hypotensive events with a sensitivity of 0.85 [95% confidence interval (CI) 0.73-0.94] and specificity of 0.85 (95% CI 0.74-0.95) 15 min before the event [area under the curve (AUC) 0.95 (95% CI 0.89-0.99)]; with a sensitivity of 0.82 (95% CI 0.71-0.92) and specificity of 0.83 (95% CI 0.71-0.93) 10 min before the event [AUC 0.9 (95% CI 0.83-0.97)]; and with a sensitivity of 0.86 (95% CI 0.78-0.93) and specificity 0.86 (95% CI 0.77-0.94) 5 min before the event [AUC 0.93 (95% CI 0.89-0.97)]. HPI provides accurate and continuous prediction of impending IOH before its occurrence in patients undergoing GOS in general anesthesia.
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J Clin Monit Comput · Oct 2022
Multicenter StudyComparison of a new EMG module, AF-201P, with acceleromyography using the post-tetanic counts during rocuronium-induced deep neuromuscular block: a prospective, multicenter study.
Recent advances in neuromuscular monitors have facilitated the development of a new electromyographic module, AF-201P™. The purpose of this study was to investigate the relationship between post-tetanic counts (PTCs) assessed using the AF-201P™ and the acceleromyographic TOF Watch SX™ during rocuronium-induced deep neuromuscular block. Forty adult patients consented to participate in this study. ⋯ Regression analysis showed no significant difference in PTCs between the two monitors (PTCs measured by the TOF Watch SX™ = 0.78·PTCs measured by AF-201P™ + 0.21, R = 0.56). Bland-Altman analysis also showed acceptable ranges of bias [95% CI] and limits of agreement (0.3 [0.2 to 0.5] and - 4.6 to 5.3) for the PTCs. The new EMG module, AF-201P™, showed reliable PTCs during deep neuromuscular block, as well as the TOF Watch SX™.
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J Clin Monit Comput · Oct 2022
Randomized Controlled Trial Observational StudyThe outcomes of using high oxygen concentration in pediatric patients.
Oxygen reserve index, available as part of Masimo Rainbow SET pulse oximetry, is a noninvasive and continuous variable intended to provide insight into a patient's oxygen status in the moderate hyperoxic range (PaO2 > 100 and ≤ 200 mm Hg), defined as a patient's oxygen "reserve". When used in conjunction with pulse oximetry, ORi extends the knowledge on a patient's oxygen status providing clinically important information helping to prevent hyperoxemia and hypoxemia. There are limited data on patients undergoing craniosynostosis surgery. ⋯ In Group 1, ORi values were significantly higher when compared to group 2 at baseline (0.86 ± 0.21 vs 0.45 ± 0.32, p = 0.001), one minute (0.61 ± 0.24 vs 0.27 ± 0.21, p = 0.001), and 5 min (0.34 ± 0.31 vs 0.10 ± 0.13, p = 0.033). High inspired oxygen concentration during induction of anesthesia in pediatric patients is associated with higher levels of ORi. Therefore, ORi may provide the means to safely reduce the inspired oxygen fraction during inhalational induction in paediatric patients.