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'. ML shunt estimates versus true values (n = 500) produced a linear regression model with slope = 0.987, intercept = -0.001 and R2 = 0.999. Kernel density estimate and error plots confirmed close agreement. 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.

Pulmonary gas exchange evaluated by machine learning: a computer simulation.

Using computer simulation we investigated whether machine learning (ML) analysis of selected ICU monitoring data can quantify pulmonary gas exchange in multi-compartment format. A 21 compartment ventilation/perfusion (V/Q) model of pulmonary blood flow processed 34,551 combinations of cardiac output, hemoglobin concentration, standard P50, base excess, VO2 and VCO2 plus three model-defining parameters: shunt, log SD and mean V/Q. From these inputs the model produced paired arterial blood gases, first with the inspired O2 fraction (FiO2) adjusted to arterial saturation (SaO2) = 0.90, and second with FiO2 increased by 0.1. 'Stacked regressor' ML ensembles were trained/validated on 90% of this dataset. The remainder with shunt, log SD, and mean 'held back' formed the test-set. 'Two-Point' ML estimates of shunt, log SD and mean utilized data from both FiO2 settings. 'Single-Point' estimates used only data from SaO2 = 0.90. From 3454 test gas exchange scenarios, two-point shunt, log SD and mean estimates produced linear regression models versus true values with slopes ~ 1.00, intercepts ~ 0.00 and R2 ~ 1.00. Kernel density and Bland-Altman plots confirmed close agreement. Single-point estimates were less accurate: R2 = 0.77-0.89, slope = 0.991-0.993, intercept = 0.009-0.334. ML applications using blood gas, indirect calorimetry, and cardiac output data can quantify pulmonary gas exchange in terms describing a 20 compartment V/Q model of pulmonary blood flow. High fidelity reports require data from two FiO2 settings.

Comparison of the Glidescope®, flexible fibreoptic intubating bronchoscope, iPhone modified bronchoscope, and the Macintosh laryngoscope in normal and difficult airways: a manikin study.

BACKGROUND: Smart phone technology is becoming increasingly integrated into medical care.Our study compared an iPhone modified flexible fibreoptic bronchoscope as an intubation aid and clinical teaching tool with an unmodified bronchoscope, Glidescope® and Macintosh laryngoscope in a simulated normal and difficult airway scenario. METHODS: Sixty three anaesthesia providers, 21 consultant anaesthetists, 21 registrars and 21 anaesthetic nurses attempted to intubate a MegaCode Kelly™ manikin, comparing a normal and difficult airway scenario for each device. Primary endpoints were time to view the vocal cords (TVC), time to successful intubation (TSI) and number of failed intubations with each device. Secondary outcomes included participant rated device usability and preference for each scenario. Advantages and disadvantages of the iPhone modified bronchoscope were also discussed. RESULTS: There was no significant difference in TVC with the iPhone modified bronchoscope compared with the Macintosh blade (P = 1.0) or unmodified bronchoscope (P = 0.155). TVC was significantly shorter with the Glidescope compared with the Macintosh blade (P < 0.001), iPhone (P < 0.001) and unmodified bronchoscope (P = 0.011). The iPhone bronchoscope TSI was significantly longer than all other devices (P < 0.001). There was no difference between anaesthetic consultant or registrar TVC (P = 1.0) or TSI (P = 0.252), with both being less than the nurses (P < 0.001). Consultant anaesthetists and nurses had a higher intubation failure rate with the iPhone modified bronchoscope compared with the registrars. Although more difficult to use, similar proportions of consultants (14/21), registrars (15/21) and nurses (15/21) indicated that they would be prepared to use the iPhone modified bronchoscope in their clinical practice. The Glidescope was rated easiest to use (P < 0.001) and was the preferred device by all participants for the difficult airway scenario. CONCLUSIONS: The iPhone modified bronchoscope, in its current configuration, was found to be more difficult to use compared with the Glidescope® and unmodified bronchoscope; however it offered several advantages for teaching fibreoptic intubation technique when video-assisted bronchoscopy was unavailable.

Copper and anesthesia: clinical relevance and management of copper related disorders.

Recent research has implicated abnormal copper homeostasis in the underlying pathophysiology of several clinically important disorders, some of which may be encountered by the anesthetist in daily clinical practice. The purpose of this narrative review is to summarize the physiology and pharmacology of copper, the clinical implications of abnormal copper metabolism, and the subsequent influence of altered copper homeostasis on anesthetic management.