Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2023
Modeling the impacts of assumptions and nonpulmonary factors on the performance and reliability of indices of oxygenation.
Assessment of oxygenation is fundamental to the care of patients. Numerous indices of oxygenation have been developed that entail variable degrees of invasiveness, complexity and physiologic underpinning. The clinical reliability of these indices has been questioned. ⋯ These effects manifested as calculated indices either over or under-estimating actual shunt by FShunt, or wide unpredictable variability (scatter) when correlating A-a [Formula: see text] gradient and Pa:Fi ratio to actual shunt. Cardiac output and oxygen extraction have noticeable impacts on all calculated indices. The results support the clinical observations that the performance of indices of oxygenation can vary with fraction of inspired oxygen and various nonpulmonary physiological factors that underly heterogeneity present in the clinical population.
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J Clin Monit Comput · Oct 2023
Deep learning classification of capnography waveforms: secondary analysis of the PRODIGY study.
Capnography monitors trigger high priority 'no breath' alarms when CO2 measurements do not exceed a given threshold over a specified time-period. False alarms occur when the underlying breathing pattern is stable, but the alarm is triggered when the CO2 value reduces even slightly below the threshold. True 'no breath' events can be falsely classified as breathing if waveform artifact causes an aberrant spike in CO2 values above the threshold. ⋯ The neural network's accuracy was 0.97, precision was 0.97 and recall was 0.96. Performance was consistent across hospitals in internal-external validation. The neural network could reduce false capnography alarms. Further research is needed to compare the frequency of alarms derived from the neural network with the standard approach.
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J Clin Monit Comput · Oct 2023
Changes in EEG frequency characteristics during sevoflurane general anesthesia: feature extraction by variational mode decomposition.
Mode decomposition is a method for extracting the characteristic intrinsic mode function (IMF) from various multidimensional time-series signals. Variational mode decomposition (VMD) searches for IMFs by optimizing the bandwidth to a narrow band with the [Formula: see text] norm while preserving the online estimated central frequency. In this study, we applied VMD to the analysis of electroencephalogram (EEG) recorded during general anesthesia. ⋯ IMF-2, IMF-3, IMF-4, IMF-5, and IMF-6 increased significantly from 1.4 (1.2-1.6) Hz to 7.5 (1.5-9.3) Hz, 6.7 (4.1-7.6) Hz to 19.4 (6.9-20.0) Hz, 10.9 (8.8-11.4) Hz to 26.4 (24.2-27.2) Hz, 13.4 (11.3-16.6) Hz to 35.6 (34.9-36.1) Hz, and 12.4 (9.7-18.1) Hz to 43.2 (42.9-43.4) Hz, respectively. The characteristic frequency component changes in specific IMFs during emergence from general anesthesia were visually captured by IMFs derived using VMD. EEG analysis by VMD is useful for extracting distinct changes during general anesthesia.
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J Clin Monit Comput · Oct 2023
Single-FiO2 lung modelling with machine learning: a computer simulation incorporating volumetric capnography.
We investigated whether machine learning (ML) analysis of ICU monitoring data incorporating volumetric capnography measurements of mean alveolar PCO2 can partition venous admixture (VenAd) into its shunt and low V/Q components without manipulating the inspired oxygen fraction (FiO2). From a 21-compartment ventilation / perfusion (V/Q) model of pulmonary blood flow we generated blood gas and mean alveolar PCO2 data in simulated scenarios with shunt values from 7.3% to 36.5% and a range of FiO2 settings, indirect calorimetry and cardiac output measurements and acid- base and hemoglobin oxygen affinity conditions. A 'deep learning' ML application, trained and validated solely on single FiO2 bedside monitoring data from 14,736 scenarios, then recovered shunt values in 500 test scenarios with true shunt values 'held back'. ⋯ With corresponding VenAd values calculated from the same bedside data, low V/Q flow can be reported as VenAd-shunt. ML analysis of blood gas, indirect calorimetry, volumetric capnography and cardiac output measurements can quantify pulmonary oxygenation deficits as percentage shunt flow (V/Q = 0) versus percentage low V/Q flow (V/Q > 0). High fidelity reports are possible from analysis of data collected solely at the operating FiO2.
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J Clin Monit Comput · Oct 2023
Evaluation of temperature-dependent fluctuations in skin microcirculation flow using a light-emitting diode based photoacoustic imaging device.
Skin microvessels maintain temperature homeostasis by contracting and dilating upon exposure to changes in temperature. Under general anesthesia, surgical invasiveness, including incisions and coagulation, and the effects of anesthetics may cause variations in the threshold temperature, leading to the constriction and dilation of cutaneous blood vessels. Therefore, studies on skin microvascular circulation are necessary to develop appropriate interventions for complications during surgery. ⋯ These findings suggest that the LED-PAI device could be an option for evaluating microcirculation in association with changes in temperature.