Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2022
Indirect measurement of absolute cardiac output during exercise in simulated altered gravity is highly dependent on the method.
Altered gravity environments introduce cardiovascular changes that may require continuous hemodynamic monitoring in both spaceflight and terrestrial analogs. Conditions in such environments are often prohibitive to direct/invasive methods and therefore, indirect measurement techniques must be used. This study compares two common cardiac measurement techniques used in the human spaceflight domain, pulse contour analysis (PCA-Nexfin) and inert gas rebreathing (IGR-Innocor), in subjects completing ergometer exercise under altered gravity conditions simulated using a tilt paradigm. ⋯ There is a poor agreement in absolute stroke volume and cardiac output values between measurement via PCA (Nexfin) and IGR (Innocor) in subjects who are exercising in simulated altered gravity environments. These results suggest that the chosen measurement method and device greatly impacts absolute measurements of cardiac output. However, there is a good level of agreement between the two devices when measuring relative changes. Either of these devices seem adequate to capture cardiac changes, but should not be solely relied upon for accurate measurement of absolute cardiac output.
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J Clin Monit Comput · Oct 2022
Measurement of capillary refill time with a handheld prototype device: a comparative validation study in healthy volunteers.
Validity and reproducibility of clinical capillary refill time (CRT) measurement depend on many factors in daily routine practice. We conducted a prospective validation study of an automatized handheld prototype device providing standardized CRT assessment (DiCART™) in 20 healthy volunteers. Three different methods of CRT measurement were compared before and during dynamic circulatory changes induced by venous and arterial occlusion tests at both upper and lower limb levels: CRTCLIN corresponding to basic clinical assessment and considered as the reference method; CRTVIDEO corresponding to off-line videos reviewed by investigators recorded by DiCART™; and CRTDiCART corresponding to on-line videos analysed by a built-in proprietary mathematical algorithm included in DiCART™. ⋯ However, the perfectible precision, the poor agreement with clinical assessment and numerous device dysfunctions give leads to the development of a further version of the prototype before promoting its use in clinical practice. Trial registration clinicaltrial.gov. Identifier: NCT04538612.
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J Clin Monit Comput · Oct 2022
Randomized Controlled TrialThe effect of different flow levels and concentrations of sevoflurane during the wash-in phase on volatile agent consumption: a randomized controlled trial.
The standard procedure for low-flow anesthesia usually incorporates a high fresh gas flow (FGF) of 4-6 L/minute during the wash-in phase. However, the administration of a high FGF (4-6 L/min) increases the inhaled anesthetic agent consumption. This study was designed to compare the sevoflurane consumption at 2 rates of flow and vaporizer concentration during the wash-in period. ⋯ The anesthetic agent consumption during the wash-in phase was approximately 3 times lower with the administration of sevoflurane at 1 L/minute FGF than the use of 4 L/minute FGF.
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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
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.