Chronic high-dose beetroot juice supplementation improves time trial performance of well-trained cyclists in normoxia and hypoxia, Nitric Oxide (2019), doi:

This study shows that oxygen equilibration relevant for clinical interpretation requires only 10 minutes following an increase and 16 minutes following a decrease in FIO2. over the range studied.

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.

BackgroundEarly diagnosis of shock is a predetermining factor for a good prognosis in intensive care. An elevated central venous to arterial PCO2 difference (∆PCO2) over 0.8 kPa (6 mm Hg) is indicative of low blood flow states. Disturbances around the time of blood sampling could result in inaccurate calculations of ∆PCO2, thereby misrepresenting the patient status. This study aimed to determine the influences of acute changes in ventilation on ∆PCO2 and understand its clinical implications.MethodsTo investigate the isolated effects of changes in ventilation on ∆PCO2, eight pigs were studied in a prospective observational cohort. Arterial and central venous catheters were inserted following anaesthetisation. Baseline ventilator settings were titrated to achieve an EtCO2 of 5±0.5 kPa (VT = 8 mL/kg, Freq = 14 ± 2/min). Blood was sampled simultaneously from both catheters at baseline and 30, 60, 90, 120, 180 and 240 s after a change in ventilation. Pigs were subjected to both hyperventilation and hypoventilation, wherein the respiratory frequency was doubled or halved from baseline. ∆PCO2 changes from baseline were analysed using repeated measures ANOVA with post-hoc analysis using Bonferroni’s correction.Results∆PCO2 at baseline for all pigs was 0.76±0.29 kPa (5.7±2.2 mm Hg). Following hyperventilation, there was a rapid increase in the ∆PCO2, increasing maximally to 1.35±0.29 kPa (10.1±2.2 mm Hg). A corresponding decrease in the ∆PCO2 was seen following hypoventilation, decreasing maximally to 0.23±0.31 kPa (1.7±2.3 mm Hg). These changes were statistically significant from baseline 30 s after the change in ventilation.ConclusionDisturbances around the time of blood sampling can rapidly affect the PCO2, leading to inaccurate calculations of the ∆PCO2, resulting in misinterpretation of patient status. Care should be taken when interpreting blood gases, if there is doubt as to the presence of acute and transient changes in ventilation.

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.