Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2022
Continuous vital sign monitoring using a wearable patch sensor in obese patients: a validation study in a clinical setting.
Our aim was to determine the agreement of heart rate (HR) and respiratory rate (RR) measurements by the Philips Biosensor with a reference monitor (General Electric Carescape B650) in severely obese patients during and after bariatric surgery. Additionally, sensor reliability was assessed. Ninety-four severely obese patients were monitored with both the Biosensor and reference monitor during and after bariatric surgery. ⋯ No clear causes for data loss were found. The Biosensor is suitable for remote monitoring of HR, but not RR in morbidly obese patients. Future research should focus on improving RR measurements, the interpretation of continuous data, and development of smart alarm systems.
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J Clin Monit Comput · Oct 2022
How early warning with the Oxygen Reserve Index (ORi™) can improve the detection of desaturation during induction of general anesthesia?
The Oxygen Reserve Index (ORi™) is a dimensionless parameter with a value between 0 and 1. It is related to the real-time oxygenation status in the moderate hyperoxic range. The purpose of this study is to investigate the added warning time provided by different ORi alarm triggers and the continuous trends of ORi, SpO2, and PaO2. ⋯ The ORi enables the clinicians to monitor the patients' oxygen status during induction of general anesthesia and can improve the detection of impending desaturation. However, further studies are needed to assess its clinical potential in the high hyperoxic range. The protocol was retrospectively registered at ClinicalTrials.gov on July 21, 2021 (NCT04976504).
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J Clin Monit Comput · Oct 2022
Opal: an implementation science tool for machine learning clinical decision support in anesthesia.
Opal is the first published example of a full-stack platform infrastructure for an implementation science designed for ML in anesthesia that solves the problem of leveraging ML for clinical decision support. Users interact with a secure online Opal web application to select a desired operating room (OR) case cohort for data extraction, visualize datasets with built-in graphing techniques, and run in-client ML or extract data for external use. Opal was used to obtain data from 29,004 unique OR cases from a single academic institution for pre-operative prediction of post-operative acute kidney injury (AKI) based on creatinine KDIGO criteria using predictors which included pre-operative demographic, past medical history, medications, and flowsheet information. ⋯ At the default probability decision threshold of 0.5, the model sensitivity was 0.9 and the specificity was 0.8. K-means clustering was performed to partition the cases into two clusters and for hypothesis generation of potential groups of outcomes related to intraoperative vitals. Opal's design has created streamlined ML functionality for researchers and clinicians in the perioperative setting and opens the door for many future clinical applications, including data mining, clinical simulation, high-frequency prediction, and quality improvement.
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J Clin Monit Comput · Oct 2022
High-flow nasal cannula therapy, factors affecting effective inspired oxygen fraction: an experimental adult bench model.
Oxygenation through High Flow Delivery Systems (HFO) is described as capable of delivering accurate FiO2. Meanwhile, peak inspiratory flow [Formula: see text] ) of patients with acute hypoxemic respiratory failure can reach up to 120 L/min, largely exceeding HFO flow. Currently, very few data on the reliability of HFO devices at these high [Formula: see text] are available. ⋯ The present bench study did expose a weakness of HFO devices in reliability of delivering accurate FIO2 at high [Formula: see text] as well as, to a lesser extent, at [Formula: see text] below equivalent set HFO Flows. Moreover, set HFO flow and set FIO2 did influence the variability of effective inspired oxygen fraction. The adjunction of a dead space in the experimental set-up significantly amended this variability and should thus be further studied in order to improve success rate of HFO therapy.
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J Clin Monit Comput · Oct 2022
A comparison of endotracheal tube compensation techniques for the measurement of respiratory mechanical impedance at low frequencies.
Measurement of respiratory impedance ([Formula: see text]) in intubated patients requires accurate compensation for pressure losses across the endotracheal tube (ETT). In this study, we compared time-domain (TD), frequency-domain (FD) and combined time-/frequency-domain (FT) methods for ETT compensation. We measured total impedance ([Formula: see text]) of a test lung in series with three different ETT sizes, as well as in three intubated porcine subjects. ⋯ The FD and TF compensations yielded estimates of [Formula: see text] with similar accuracies. For the porcine subjects, no significant differences were observed in [Formula: see text] across compensation methods. FD and TF compensation of the ETT may allow for accurate oscillometric estimates of [Formula: see text] in intubated subjects, while avoiding the difficulties associated with direct tracheal pressure measurement.