Journal of clinical monitoring and computing
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J Clin Monit Comput · Apr 2023
Device for remote and realtime monitoring of neonatal vital signs in neonatal intensive care unit using internet of things: proof-of-concept study.
Realtime and remote monitoring of neonatal vital signs is a crucial part of providing appropriate care in neonatal intensive care units (NICU) to reduce mortality and morbidity of newborns. In this study, a new approach, a device for remote and real-time monitoring of neonatal vital signs (DRRMNVS) in the neonatal intensive care unit using the internet of things (IoT), was proposed. The system integrates four vital signs: oxygen saturation, pulse rate, body temperature and respiration rate for continuous monitoring using the Blynk app and ThingSpeak IoT platforms. ⋯ The developed DRRMNVS device was cheap and had acceptable measurement accuracy of vital signs in a controlled environment. The system has the potential to advance healthcare service delivery for neonates with further development from this proof-of-concept level.
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J Clin Monit Comput · Apr 2023
Reliability of submaximal stimulation for the train-of-four test using acceleromyography and electromyography with individualized stimulation currents.
The supramaximal stimulation (SMS) of the TOF test causes uncomfortable sensations in patients. We aimed to determine whether the submaximal stimulation would be reliable in TOF tests with reduced painful sensation. ⋯ The TOF test with submaximal stimulation is still reliable and can reduce stimulation pain. Considering the importance of the TOF results in determining extubation, the authors suggest the minimal current for the TOF test as 70% SMS.
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J Clin Monit Comput · Apr 2023
Agreement between cardiac output estimation by multi-beat analysis of arterial blood pressure waveforms and continuous thermodilution in post cardiac surgery intensive care unit patients.
We sought to assess agreement of cardiac output estimation between continuous pulmonary artery catheter (PAC) guided thermodilution (CO-CTD) and a novel pulse wave analysis (PWA) method that performs an analysis of multiple beats of the arterial blood pressure waveform (CO-MBA) in post-operative cardiac surgery patients. PAC obtained CO-CTD measurements were compared with CO-MBA measurements from the Argos monitor (Retia Medical; Valhalla, NY, USA), in prospectively enrolled adult cardiac surgical intensive care unit patients. Agreement was assessed via Bland-Altman analysis. ⋯ In the arrhythmia subgroup, mean of differences was 0.14 ± 0.90 L/min with an error of 35.4%. In the low CO subgroup, mean of differences was 0.26 ± 0.89 L/min with an error of 40.4%. In adult patients after cardiac surgery, including those with low cardiac output and arrhythmia CO-MBA is not interchangeable with the continuous thermodilution method via a PAC, when using a 30% error threshold.
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J Clin Monit Comput · Apr 2023
Non-invasive over-distension measurements: data driven vs model-based.
Clinical measurements offer bedside monitoring aiming to minimise unintended over-distension, but have limitations and cannot be predicted for changes in mechanical ventilation (MV) settings and are only available in certain MV modes. This study introduces a non-invasive, real-time over-distension measurement, which is robust, predictable, and more intuitive than current methods. The proposed over-distension measurement, denoted as OD, is compared with the clinically proven stress index (SI). ⋯ OD eliminates the limitations of SI in MV mode and its less intuitive lung status value. Finally, OD can be accurately predicted for new ventilator settings via its foundation in a validated predictive personalized lung mechanics model. Therefore, OD offers potential clinical value over current clinical methods.
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J Clin Monit Comput · Apr 2023
A machine learning approach to predicting early and late postoperative reintubation.
Accurate estimation of surgical risks is important for informing the process of shared decision making and informed consent. Postoperative reintubation (POR) is a severe complication that is associated with postoperative morbidity. Previous studies have divided POR into early POR (within 72 h of surgery) and late POR (within 30 days of surgery). ⋯ The scoring systems developed from the logistic regression models demonstrated strong performance in terms of both accuracy and discrimination across the different POR outcomes (Average Brier score, 0.172; Average c-statistic, 0.852). These results were only marginally worse than prediction using the full set of risk variables (Average Brier score, 0.145; Average c-statistic, 0.870). While more work needs to be done to identify clinically relevant differences between the early and late POR outcomes, the scoring systems provided here can be used by surgeons and patients to improve the quality of care overall.