Modyflow - A Modular Dynamic Flow Testing Device for Research and TAVI Evaluation

2016 ◽  
Vol 64 (S 01) ◽  
Author(s):  
F. König ◽  
C. Hagl ◽  
N. Thierfelder
Keyword(s):  
Testing Device ◽  
Dynamic Flow

Evaluation of a non invasive hemoglobin testing device, the Hemo Hue® card, in obstetrics

2009 ◽  
Vol 213 (S 01) ◽  
Author(s):  
D Dünner ◽  
C Breymann
Keyword(s):  
Testing Device ◽  
Non Invasive

Determination of the International Sensitivity Index of a New Near-Patient Testing Device to Monitor Oral Anticoagulant Therapy

1997 ◽  
Vol 78 (02) ◽  
pp. 855-858 ◽  
Author(s):  
Armando Tripodi ◽  
Veena Chantarangkul ◽  
Marigrazia Clerici ◽  
Barbara Negri ◽  
Pier Mannuccio Mannucci
Keyword(s):  
Linear Relationship ◽  
Whole Blood ◽  
Oral Anticoagulant ◽  
Oral Anticoagulant Therapy ◽  
Oral Anticoagulants ◽  
Calibration Model ◽  
Testing Device ◽  
Data Points ◽  
Near Patient Testing

SummaryA key issue for the reliable use of new devices for the laboratory control of oral anticoagulant therapy with the INR is their conformity to the calibration model. In the past, their adequacy has mostly been assessed empirically without reference to the calibration model and the use of International Reference Preparations (IRP) for thromboplastin. In this study we reviewed the requirements to be fulfilled and applied them to the calibration of a new near-patient testing device (TAS, Cardiovascular Diagnostics) which uses thromboplastin-containing test cards for determination of the INR. On each of 10 working days citrat- ed whole blood and plasma samples were obtained from 2 healthy subjects and 6 patients on oral anticoagulants. PT testing on whole blood and plasma was done with the TAS and parallel testing for plasma by the manual technique with the IRP CRM 149S. Conformity to the calibration model was judged satisfactory if the following requirements were met: (i) there was a linear relationship between paired log-PTs (TAS vs CRM 149S); (ii) the regression line drawn through patients data points, passed through those of normals; (iii) the precision of the calibration expressed as the CV of the slope was <3%. A good linear relationship was observed for calibration plots for plasma and whole blood (r = 0.98). Regression lines drawn through patients data points, passed through those of normals. The CVs of the slope were in both cases 2.2% and the ISIs were 0.965 and 1.000 for whole blood and plasma. In conclusion, our study shows that near-patient testing devices can be considered reliable tools to measure INR in patients on oral anticoagulants and provides guidelines for their evaluation.

Platelet Activation and Cytosolic Free Potassium Kinetics: A Dynamic Flow Cytometric Monitoring

2019 ◽  
Author(s):  
A. Aliotta ◽  
D. Bertaggia ◽  
L. Alberio
Keyword(s):  
Platelet Activation ◽  
Dynamic Flow ◽  
Flow Cytometric

Dynamic Flow Simulation to Study Flow Assurance Challenges in Water Alternating Gas WAG Wells

2016 ◽  
Author(s):  
Hassan Karimi ◽  
Erni Dharma Putra ◽  
Kapil Kumar Thakur ◽  
Rahel Yusuf ◽  
Azwan Shaharun ◽  
...  
Keyword(s):  
Flow Simulation ◽  
Flow Assurance ◽  
Dynamic Flow ◽  
Water Alternating Gas

Numerical study of fluid dynamic flow within an internal combustion engine cylinder

2017 ◽  
Author(s):  
Ana Marta Souza ◽  
Antônio César Valadares de Oliveira ◽  
Enrico Temporim Ribeiro ◽  
Francisco Souza ◽  
Marcelo Colombo Chiari
Keyword(s):  
Internal Combustion Engine ◽  
Combustion Engine ◽  
Numerical Study ◽  
Fluid Dynamic ◽  
Internal Combustion ◽  
Dynamic Flow ◽  
Engine Cylinder

A dynamic-flow carbon-cycle box model and high-latitude sensitivity

Tellus B ◽  
2006 ◽  
Vol 58 (4) ◽  
Author(s):  
Emily Lane ◽  
Synte Peacock ◽  
Juan M. Restrepo
Keyword(s):  
Carbon Cycle ◽  
High Latitude ◽  
Box Model ◽  
Dynamic Flow

scholarly journals Deep learning for vision‐based fall detection system: Enhanced optical dynamic flow

2020 ◽  
Author(s):  
Sagar Chhetri ◽  
Abeer Alsadoon ◽  
Thair Al‐Dala'in ◽  
P. W. C. Prasad ◽  
Tarik A. Rashid ◽  
...  
Keyword(s):  
Deep Learning ◽  
Detection System ◽  
Fall Detection ◽  
Dynamic Flow
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