Correlation and agreement between the TEG® 5000 and the TEG® 6s during liver transplant surgery

Jacqueline L Robson1, Andrew Dj Watts1, Timothy J McCulloch1,2

  • 11 Department of Anaesthetics, Royal Prince Alfred Hospital, Australia.

The TEG® 5000 and novel TEG® 6s measure the viscoelasticity of whole blood during in vitro clot formation. The two devices measure similar coagulation variables but utilize distinctly different technologies. This study aimed to determine the correlation and agreement between the thrombelastographic parameters obtained by the two devices during liver transplant surgery. We obtained blood samples at six predefined intervals during the surgery of 10 consecutive patients. Two operators proficient in the use of the TEG® 6s and TEG® 5000 systems performed thrombelastographic measurements on each sample: non-citrated TEG® 5000, citrated TEG® 5000 and citrated TEG® 6s. Agreement and correlation were assessed using Bland Altman plots and Lin's concordance correlation. There was considerable inter-device variability for the different parameters measured by the TEG® 5000 and TEG® 6s devices. Acceptable agreement was observed when results were within the normal reference ranges. However, with increasing coagulopathy, agreement was poor and results could not be considered interchangeable. Although each of the three tests appeared reliable for qualitative detection of abnormalities of clot formation during liver transplant surgery, we found their quantitative results were not interchangeable.

Related Concept Videos

Correlations02:20

Correlations

Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
35.8K
Correlation and Causation01:27

Correlation and Causation

Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
42.4K
Correlation01:09

Correlation

In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
15.1K
Correlation and Regression00:53

Correlation and Regression

In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
3.4K
Coefficient of Correlation01:12

Coefficient of Correlation

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
8.6K
Correlation of Experimental Data01:23

Correlation of Experimental Data

Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
481