scholarly journals Reliability of the mean flow index (Mx) for assessing cerebral autoregulation in healthy volunteers

2021 ◽  
Vol 9 (12) ◽  
Author(s):  
Markus H. Olsen ◽  
Christian G. Riberholt ◽  
Ronni R. Plovsing ◽  
Kirsten Møller ◽  
Ronan M. G. Berg
Keyword(s):  
Healthy Volunteers ◽  
Cerebral Autoregulation ◽  
Flow Index ◽  
Mean Flow ◽  
The Mean

Reliability and validity of the mean flow index (Mx) for assessing cerebral autoregulation in humans: A systematic review of the methodology

2021 ◽  
pp. 0271678X2110525
Author(s):  
Markus Harboe Olsen ◽  
Christian Gunge Riberholt ◽  
Jesper Mehlsen ◽  
Ronan MG Berg ◽  
Kirsten Møller
Keyword(s):  
Systematic Review ◽  
Cerebral Autoregulation ◽  
Reliability And Validity ◽  
Flow Index ◽  
Mean Flow ◽  
Optimal Method ◽  
Discriminatory Ability ◽  
Wide Range ◽  
Repeatability And Reproducibility ◽  
The Mean

Cerebral autoregulation is a complex mechanism that serves to keep cerebral blood flow relatively constant within a wide range of cerebral perfusion pressures. The mean flow index (Mx) is one of several methods to assess dynamic cerebral autoregulation, but its reliability and validity have never been assessed systematically. The purpose of the present systematic review was to evaluate the methodology, reliability and validity of Mx. Based on 128 studies, we found inconsistency in the pre-processing of the recordings and the methods for calculation of Mx. The reliability in terms of repeatability and reproducibility ranged from poor to excellent, with optimal repeatability when comparing overlapping recordings. The discriminatory ability varied depending on the patient populations; in general, those with acute brain injury exhibited a higher Mx than healthy volunteers. The prognostic ability in terms of functional outcome and mortality ranged from chance result to moderate accuracy. Since the methodology was inconsistent between studies, resulting in varying reliability and validity estimates, the results were difficult to compare. The optimal method for deriving Mx is currently unknown.

scholarly journals Flow and Thermal Properties of Stevia Powder

2018 ◽  
Vol 21 (2) ◽  
pp. 51-55 ◽  
Author(s):  
Ajit K. Mahapatra ◽  
Agnes J. Kapsoiyo ◽  
Sierra C. Birmingham ◽  
Daniel Ekefre ◽  
Bipul K. Biswas
Keyword(s):  
Thermal Properties ◽  
Internal Friction ◽  
Polynomial Regression ◽  
Stevia Rebaudiana ◽  
Calorific Value ◽  
Flow Index ◽  
Published Data ◽  
Mean Flow ◽  
Angle Of Internal Friction ◽  
The Mean

Abstract Stevia (Stevia rebaudiana Bertoni) has recently received a lot of attention as a sweetener due to its taste and low calorific value. Flow and thermal properties of foods play a significant role in the quantitative analysis of unit operations in the food industry. However, there are no published data available on flow and thermal properties of stevia powder. Powder Flow Tester and KD2 Pro Thermal Properties Analyzer were used to determine the flow and thermal properties of stevia powder, respectively, at different moisture contents (4.96%, 9.68%, 13.99%, 20.08%, and 25.79%, w.b.). Mean angle of internal friction of stevia powder ranged from 41.13° to 46.3°. The mean effective angle of internal friction ranged from 47.8° to 52.5° and the mean flow index ranged from 0.27 to 0.48. Mean thermal conductivity of stevia powder ranged from 0.091 W·m-2·K-1 to 0.115 W·m-2·K-1. Mean thermal diffusivity ranged from 0.103 mm2·s-1 to 0.121 mm2·s-1 and mean volumetric specific heat ranged from 0.865 MJ·m-3·K-1 to 1.019 MJ·m-3·K-1. Polynomial regression models were developed to predict flow and thermal properties of stevia powder using moisture content of stevia powder.

Caffeine consumption does not have an effect on digital microvascular perfusion assessed by laser doppler imaging on healthy volunteers: a pilot study

2014 ◽  
Vol 40 (4) ◽  
pp. 412-415 ◽  
Author(s):  
R. Knight ◽  
J. Pagkalos ◽  
C. Timmons ◽  
R. Jose
Keyword(s):  
Blood Flow ◽  
Healthy Volunteers ◽  
Microvascular Perfusion ◽  
Laser Doppler ◽  
Mean Flow ◽  
Caffeine Consumption ◽  
Flow Monitoring ◽  
Digital Blood Flow ◽  
The Mean ◽  
Pharmacologically Active

Caffeine is one of the most commonly consumed pharmacologically active ingredients in the Western world. It is postulated to cause peripheral vasoconstriction and decreased digital blood flow. As a result, many hand surgeons forbid caffeine consumption post-operatively by patients undergoing replantation surgery for fear of compromising healing. We hypothesized that caffeine has no effect on digital microvascular perfusion. Healthy volunteers were recruited and digital microperfusion was assessed using laser Doppler probes attached to the finger pulp, both before and after ingestion of 100 mg of caffeine. A total of 34 patients were included in the final study. The mean flow before the consumption of caffeine was 226.15 PU. The mean flow following the consumption of caffeine was 197.7 PU. This decrease was not statistically significant. This study revealed no decrease in digital blood flow following the ingestion of 100 mg of caffeine by healthy volunteers, as measured by laser Doppler flow monitoring. Level of Evidence: 3

scholarly journals Comparison of Frequency and Time Domain Methods of Assessment of Cerebral Autoregulation in Traumatic Brain Injury

2014 ◽  
Vol 35 (2) ◽  
pp. 248-256 ◽  
Author(s):  
Xiuyun Liu ◽  
Marek Czosnyka ◽  
Joseph Donnelly ◽  
Karol P Budohoski ◽  
Georgios V Varsos ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Transfer Function ◽  
Cerebral Autoregulation ◽  
Low Frequency ◽  
Flow Index ◽  
Mean Flow ◽  
Arterial Blood ◽  
Welch Method ◽  
Autoregulation Index

The impulse response (IR)-based autoregulation index (ARI) allows for continuous monitoring of cerebral autoregulation using spontaneous fluctuations of arterial blood pressure (ABP) and cerebral flow velocity (FV). We compared three methods of autoregulation assessment in 288 traumatic brain injury (TBI) patients managed in the Neurocritical Care Unit: (1) IR-based ARI; (2) transfer function (TF) phase, gain, and coherence; and (3) mean flow index (Mx). Autoregulation index was calculated using the TF estimation (Welch method) and classified according to the original Tiecks’ model. Mx was calculated as a correlation coefficient between 10-second averages of ABP and FV using a moving 300-second data window. Transfer function phase, gain, and coherence were extracted in the very low frequency (VLF, 0 to 0.05 Hz) and low frequency (LF, 0.05 to 0.15 Hz) bandwidths. We studied the relationship between these parameters and also compared them with patients’ Glasgow outcome score. The calculations were performed using both cerebral perfusion pressure (CPP; suffix ‘c’) as input and ABP (suffix ‘a’). The result showed a significant relationship between ARI and Mx when using either ABP ( r=−0.38, P<0.001) or CPP ( r=−0.404, P<0.001) as input. Transfer function phase and coherence_a were significantly correlated with ARI_a and ARI_c ( P<0.05). Only ARI_a, ARI_c, Mx_a, Mx_c, and phase_c were significantly correlated with patients’ outcome, with Mx_c showing the strongest association.

Simple explicit model of liquid mean flow in region above axial impeller

1985 ◽  
Vol 50 (11) ◽  
pp. 2396-2410
Author(s):  
Miloslav Hošťálek ◽  
Ivan Fořt
Keyword(s):  
Vortex Flow ◽  
Flow Model ◽  
Quantitative Agreement ◽  
Mean Flow ◽  
Flat Bottom ◽  
Proposed Model ◽  
Minimum Number ◽  
The Mean ◽  
Model Equations ◽  
Radial Circulation

The study describes a method of modelling axial-radial circulation in a tank with an axial impeller and radial baffles. The proposed model is based on the analytical solution of the equation for vortex transport in the mean flow of turbulent liquid. The obtained vortex flow model is tested by the results of experiments carried out in a tank of diameter 1 m and with the bottom in the shape of truncated cone as well as by the data published for the vessel of diameter 0.29 m with flat bottom. Though the model equations are expressed in a simple form, good qualitative and even quantitative agreement of the model with reality is stated. Apart from its simplicity, the model has other advantages: minimum number of experimental data necessary for the completion of boundary conditions and integral nature of these data.

scholarly journals Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores

2019 ◽  
Vol 23 (10) ◽  
pp. 4323-4331 ◽  
Author(s):  
Wouter J. M. Knoben ◽  
Jim E. Freer ◽  
Ross A. Woods
Keyword(s):  
Time Series ◽  
Coefficient Of Variation ◽  
Ad Hoc ◽  
Model Performance ◽  
Technical Note ◽  
Mean Flow ◽  
Model Adequacy ◽  
Robust Model ◽  
The Mean ◽  
Adequacy Assessment

Abstract. A traditional metric used in hydrology to summarize model performance is the Nash–Sutcliffe efficiency (NSE). Increasingly an alternative metric, the Kling–Gupta efficiency (KGE), is used instead. When NSE is used, NSE = 0 corresponds to using the mean flow as a benchmark predictor. The same reasoning is applied in various studies that use KGE as a metric: negative KGE values are viewed as bad model performance, and only positive values are seen as good model performance. Here we show that using the mean flow as a predictor does not result in KGE = 0, but instead KGE =1-√2≈-0.41. Thus, KGE values greater than −0.41 indicate that a model improves upon the mean flow benchmark – even if the model's KGE value is negative. NSE and KGE values cannot be directly compared, because their relationship is non-unique and depends in part on the coefficient of variation of the observed time series. Therefore, modellers who use the KGE metric should not let their understanding of NSE values guide them in interpreting KGE values and instead develop new understanding based on the constitutive parts of the KGE metric and the explicit use of benchmark values to compare KGE scores against. More generally, a strong case can be made for moving away from ad hoc use of aggregated efficiency metrics and towards a framework based on purpose-dependent evaluation metrics and benchmarks that allows for more robust model adequacy assessment.

scholarly journals Experimental study on the mean flow characteristics of a supersonic multiple jet configuration

2021 ◽  
Vol 108 ◽  
pp. 106377
Author(s):  
Mohammed Faheem ◽  
Aqib Khan ◽  
Rakesh Kumar ◽  
Sher Afghan Khan ◽  
Waqar Asrar ◽  
...  
Keyword(s):  
Experimental Study ◽  
Flow Characteristics ◽  
Mean Flow ◽  
The Mean

scholarly journals Modeling the Excess Velocity of Low-Viscous Taylor Droplets in Square Microchannels

Fluids ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 162 ◽  
Author(s):  
Thorben Helmers ◽  
Philip Kemper ◽  
Jorg Thöming ◽  
Ulrich Mießner
Keyword(s):  
High Speed ◽  
Process Intensification ◽  
Continuous Phase ◽  
Channel Cross Section ◽  
Optimization Approach ◽  
Mean Flow ◽  
Bypass Flow ◽  
Wall Film ◽  
Proposed Model ◽  
The Mean

Microscopic multiphase flows have gained broad interest due to their capability to transfer processes into new operational windows and achieving significant process intensification. However, the hydrodynamic behavior of Taylor droplets is not yet entirely understood. In this work, we introduce a model to determine the excess velocity of Taylor droplets in square microchannels. This velocity difference between the droplet and the total superficial velocity of the flow has a direct influence on the droplet residence time and is linked to the pressure drop. Since the droplet does not occupy the entire channel cross-section, it enables the continuous phase to bypass the droplet through the corners. A consideration of the continuity equation generally relates the excess velocity to the mean flow velocity. We base the quantification of the bypass flow on a correlation for the droplet cap deformation from its static shape. The cap deformation reveals the forces of the flowing liquids exerted onto the interface and allows estimating the local driving pressure gradient for the bypass flow. The characterizing parameters are identified as the bypass length, the wall film thickness, the viscosity ratio between both phases and the C a number. The proposed model is adapted with a stochastic, metaheuristic optimization approach based on genetic algorithms. In addition, our model was successfully verified with high-speed camera measurements and published empirical data.

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