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Purpose The multiple inert gas elimination technique (MIGET) is the reference method for evaluating pulmonary gas exchange. MIGET includes a complex experimental method and mathematical model, and has not been used routinely in clinical practice. A simpler mathematical model has been proposed, and was shown previously to fit inert gas data from oleic acid damage. This paper explores the capability of this simple model to describe more complex damage, and to calculate oxygenation data upon changing the inspired oxygen fraction (FIO.sub.2), comparing these results with those obtained using MIGET. Methods The comparison of oxygenation was done at different ventilator settings and at varying values of FIO.sub.2 in order to mimic the clinical conditions that occur in the intensive care unit. Results The simple model describes inert gas data from heterogeneous lung damage within measurement noise. Model simulations performed using the MIGET and the simple model are comparable, the MIGET model simulating partial pressure of oxygen (PaO.sub.2) values on average 0.22 ± 0.59 kPa (±SD) higher than the simple model. Model simulations are also accurate with a difference between model simulated and measured values of PaO.sub.2 of 0.33 ± 1.48 kPa (±SD) for the MIGET model and 0.12 ± 1.33 kPa (±SD) for the simple model. This comparability and accuracy was similar over different ventilator settings. Conclusions The simple model provides a description of lung damage and arterial oxygenation which is comparable to the MIGET, calculating PaO.sub.2 with acceptable accuracy and precision over the clinically relevant range of PaO.sub.2, and for different values of FIO.sub.2, positive end-expiratory pressure (PEEP), and inspiratory-to-expiratory ratio (I:E)., Author(s): Stephen E. Rees [sup.1], S. Kjærgaard [sup.2], S. Andreassen [sup.1], G. Hedenstierna [sup.3] Author Affiliations: (1) grid.5117.2, 000000010742471X, Center for Model-Based Medical Decision Support, Institute for Health Science and [...]

Hyper- or hypoventilation are commonly occurring stress responses to arterial puncture around the time of blood sampling and have been shown to rapidly alter arterial blood acid-base parameters. This study aimed to evaluate a physiology-based mathematical method to transform peripheral venous blood acid-base values into mathematically arterialised equivalents following acute, transient changes in ventilation. Data from thirty patients scheduled for elective surgery were analysed using the physiology-based method. These data described ventilator changes simulating 'hyper-' or 'hypoventilation' at arterial puncture and included acid-base status from simultaneously drawn blood samples from arterial and peripheral venous catheters at baseline and following ventilatory change. Venous blood was used to calculate mathematically arterialised equivalents using the physiology-based method; baseline values were analysed using Bland-Altman plots. When compared to baseline, measured arterial and calculated arterialised values at each time point within limits of pH: ± 0.03 and PCO 2 : ± 0.5 kPa, were considered 'not different from baseline'. Percentage of values considered not different from baseline were calculated at each sampling timepoint following hyper- and hypoventilation. For the physiological method, bias and limits of agreement for pH and PCO 2 were -0.001 (-0.022 to 0.020) and -0.02 (-0.37 to 0.33) kPa at baseline, respectively. 60 s following a change in ventilation, 100% of the mathematically arterialised values of pH and PCO 2 were not different from baseline, compared to less than 40% of the measured arterial values at the same timepoint. In clinical situations where transient breath-holding or hyperventilation may compromise the accuracy of arterial blood samples, arterialised venous blood is a stable representative of steady state arterial blood., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

The automatic lung parameter estimator (ALPE) method was developed in 2002 for bedside estimation of pulmonary gas exchange using step changes in inspired oxygen fraction (FIO₂). Since then a number of studies have been conducted indicating the potential for clinical application and necessitating systems evolution to match clinical application. This paper describes and evaluates the evolution of the ALPE method from a research implementation (ALPE1) to two commercial implementations (ALPE2 and ALPE3). A need for dedicated implementations of the ALPE method was identified: one for spontaneously breathing (non-mechanically ventilated) patients (ALPE2) and one for mechanically ventilated patients (ALPE3). For these two implementations, design issues relating to usability and automation are described including the mixing of gasses to achieve FIO₂ levels, and the automatic selection of FIO₂. For ALPE2, these improvements are evaluated against patients studied using the system. The major result is the evolution of the ALPE method into two dedicated implementations, namely ALPE2 and ALPE3. For ALPE2, the usability and automation of FIO₂ selection has been evaluated in spontaneously breathing patients showing that variability of gas delivery is 0.3 % (standard deviation) in 1,332 breaths from 20 patients. Also for ALPE2, the automated FIO2 selection method was successfully applied in 287 patient cases, taking 7.2 ± 2.4 min and was shown to be safe with only one patient having SpO₂ < 86 % when the clinician disabled the alarms. The ALPE method has evolved into two practical, usable systems targeted at clinical application, namely ALPE2 for spontaneously breathing patients and ALPE3 for mechanically ventilated patients. These systems may promote the exploration of the use of more detailed descriptions of pulmonary gas exchange in clinical practice.

Management of mechanical ventilation in intensive care patients is complicated by conflicting clinical goals. Decision support systems (DSS) may support clinicians in finding the correct balance. The objective of this study was to evaluate a computerized model-based DSS for its advice on inspired oxygen fraction, tidal volume and respiratory frequency. The DSS was retrospectively evaluated in 16 intensive care patient cases, with physiological models fitted to the retrospective data and then used to simulate patient response to changes in therapy. Sensitivity of the DSS's advice to variations in cardiac output (CO) was evaluated. Compared to the baseline ventilator settings set as part of routine clinical care, the system suggested lower tidal volumes and inspired oxygen fraction, but higher frequency, with all suggestions and the model simulated outcome comparing well with the respiratory goals of the Acute Respiratory Distress Syndrome Network from 2000. Changes in advice with CO variation of about 20% were negligible except in cases of high oxygen consumption. Results suggest that the DSS provides clinically relevant and rational advice on therapy in agreement with current 'best practice', and that the advice is robust to variation in CO.

Germ-line mutations in the tumour suppressor genes BRCA1 and BRCA2 predispose to breast and ovarian cancer. Since 1999 we have performed mutational screening of breast and/or ovarian cancer patients in East Denmark. During this period we have identified 40 novel sequence variations in BRCA1 and BRCA2 in high risk breast and/or ovarian cancer families. The mutations were detected via pre-screening using dHPLC or high-resolution melting and direct sequencing. We identified 16 variants in BRCA1, including 9 deleterious frame-shift mutations, 2 intronic variants, 4 missense mutations, and 1 synonymous variant. The remaining 24 variants were identified in BRCA2, including 10 deleterious mutants (6 frame-shift and 4 nonsense), 2 intronic variants, 10 missense mutations and 2 synonymous variants. The frequency of the variants of unknown significance was examined in control individuals. Moreover, the presumed significance of the missense mutations was predicted in silico using the align GVGD algorithm. In conclusion, the mutation screening identified 40 novel variants in the BRCA1 and BRCA2 genes and thereby extends the knowledge of the BRCA1/BRCA2 mutation spectrum. Nineteen of the mutations were interpreted as pathogenic, 3 missense mutations were suggested to be pathogenic based on in silico analysis, 6 mutations were suggested to be benign since they were identified in patients together with a well-known disease-causing BRCA1/BRCA2 mutation, while 12 were variants of unknown significance.

Objective: To present a decision support system for optimising mechanical ventilation in patients residing in the intensive care unit., Methods: Mathematical models of oxygen transport, carbon dioxide transport and lung mechanics are combined with penalty functions describing clinical preference toward the goals and side-effects of mechanical ventilation in a decision theoretic approach. Penalties are quantified for risk of lung barotrauma, acidosis or alkalosis, oxygen toxicity or absorption atelectasis, and hypoxaemia., Results: The system is presented with an example of its use in a post-surgical patient. The mathematical models describe the patient's data, and the system suggests an optimal ventilator strategy in line with clinical practice., Conclusions: The system illustrates how mathematical models combined with decision theory can aid in the difficult compromises necessary when deciding on ventilator settings.

Objective: Clinical measurements of pulmonary gas exchange abnormalities might help prevent hypoxaemia and be useful in monitoring the effects of therapy. In clinical practice single parameters are often used to describe the abnormality e.g., the "effective shunt." A single parameter description is often insufficient, lumping the effects of several abnormalities. A more detailed picture can be obtained from experiments where FiO2 is varied and two parameters estimated. These experiments have previously taken 30-40 minutes to complete, making them inappropriate for routine clinical use. However with automation of data collection and parameter estimation, the experimental time can be reduced to 10-15 minutes., Methods: A system has been built for non-invasive, Automatic, Lung Parameter Estimation (ALPE). This system consists of a ventilator, a gas analyser with pulse oximeter, and a computer. Computer programs control the experimental procedure, collect data from the ventilator and gas analyser, and estimate pulmonary gas exchange parameters. Use of the ALPE system, i.e. in estimating gas exchange parameters and reducing experimental time, has been tested on five normal subjects, two patients before and during diuretic therapy, and on 50 occasions in patients before and after surgical intervention., Results: The ALPE system provides estimation of pulmonary gas exchange parameters from a simple, clinical, non-invasive procedure, automatically and quickly. For normal subjects and in patients receiving diuretic therapy, data collection by clinicians familiar with ALPE took (mean +/- SD) 13 min 40 sec +/- 1 min 23 sec. For studies on patients before and after surgery, data collection by an intensive care nurse took (mean +/- SD) 10 min 47 sec +/- 2 min 14 sec. Parameter estimates were: for normal subjects, shunt = 4.95% +/- 2.64% and fA2 = 0.89 +/- 0.01; for patients with heart failure prior to diuretic therapy, patient 1, shunt = 11.50% fA2 = 0.41, patient 2 shunt = 11.61% fA2 = 0.55; and during therapy: patient 1, shunt = 11.51% fA2 = 0.71, patient 2, shunt = 11.22% fA2 = 0.49., Conclusions: The ALPE system provides quick, non-invasive estimation of pulmonary gas exchange parameters and may have several clinical applications. These include, monitoring pulmonary gas exchange abnormalities in the ICU, assessing post-operative gas exchange abnormalities, and titrating diuretic therapy in patients with heart failure.