Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2023
Effects of tidal volume challenge on the reliability of plethysmography variability index in hepatobiliary and pancreatic surgeries: a prospective interventional study.
The plethysmography variability index (PVI) is a non-invasive, real-time, and automated parameter for evaluating fluid responsiveness, but it does not reliably predict fluid responsiveness during low tidal volume (VT) ventilation. We hypothesized that in a 'tidal volume challenge' with a transient increase in tidal volume from 6 to 8 ml Kg- 1, the changes in PVI could predict fluid responsiveness reliably. ⋯ In hepatobiliary and pancreatic surgeries, tidal volume challenge improves the reliability of PVI for predicting fluid responsiveness and changes in PVI values obtained after tidal volume challenge are comparable to the changes in SVI.
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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
Observational StudyEvaluation of the accuracy of oscillometric non-invasive blood pressure measurement at the ankle in children during general anesthesia.
This study aimed to evaluate the accuracy of oscillometric blood pressure measurement at the ankle in children using invasive blood pressure as reference standard. This prospective observational study included children undergoing noncardiac surgery. Paired radial invasive and ankle non-invasive blood pressure measurements were obtained. ⋯ The concordance rate of ankle blood pressure was 72%, 71%, and 77% for delta SBP, DBP and MAP, respectively. The AUC (95% confidence interval) for ankle MAP ability to detect hypotension was 0.91 (0.89-0.93) with negative predictive value of 100% at cut-off value ≤ 70 mmHg, We concluded that in pediatric population undergoing noncardiac surgery, ankle blood pressure was not interchangeable with the corresponding invasive readings with the ankle MAP having the least bias compared to SBP and DBP. An ankle MAP > 70 mmHg can exclude hypotension with negative predictive value of 100%.
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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
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.