INTRODUCTION:Measurement of alloantibody titer to a red cell antigen (ABO titers) is an integral part of management of ABO incompatible kidney transplants (ABOiKT).MATERIAL AND METHODS:There are different methods of titer estimation. Alloantibody detection by tube titration and Gel agglutination columns are accepted methodologies. It is essential to find the difference in titers between the two methods so as to set the 'cut-off' titer accordingly, depending upon the method used.RESULTS:We did a prospective observational study to compare and correlate the ABO titers using these two different techniques – conventional tube technique (CTT) and the newer column agglutination technique (CAT). A total of 67 samples were processed in parallel for anti-A/B antibodies by both tube dilution and column agglutination methods. The mean titer by conventional tube method was 38.5 + 96.6 and by the column agglutination test was 96.4 + 225. The samples correlated well with Spearman rho correlation coefficient of 0.94 (P = 0.01).CONCLUSION:The column agglutination method for anti A/B titer estimation in an ABO incompatible kidney transplant is more sensitive, with the column agglutination results being approximately two and half fold higher (one more dilution) than that of tube method.
Streamline analysis coupled with finite-difference simulation provides a novel effective approach for an integrated reservoir management. The output from the existing compositional reservoir model was processed to generate streamlines from the finite-difference simulation. Reservoir management data, historical well performance data, calculations from streamline bundles, and novel performance diagnostics are integrated to optimize the field management and maximize oil recovery. Simulation and field data are combined to give an integrated understanding of the reservoir leading to smart reservoir management. Powerful streamline analysis is being used to help optimize injection and increase recovery efficiency. Real field data and model data are being analyzed to identify the areas of upswept oil and opportunities to improve the reservoir performance. This new methodology workflow is implemented in a user-friendly and intuitive way, giving more time for analysis and integration then data management.
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