Computation of the “Gray Zone” Based on Experimental Data and Its Effect on the Trueness in HIV Results in the Blood, Cells and Tissues Banks

Department of Quality Assurance, Portuguese Institute of Blood and Transplantation, Avenida Miguel Bombarda, Portugal.

Corresponding Author: Paulo Pereira, Department of Quality Assurance, Portuguese Institute of Blood and Transplantation, Avenida Miguel Bombarda 6, 1000-208 Lisboa, Portugal, Tel: +351-210063047; E-Mail:[email protected]

Received Date: 22 Dec 2016   
Accepted Date: 02 Mar 2017  
Published Date: 03  Mar 2017

Copyright© 2017 Pereira P

Citation: Pereira P. (2017). Computation of the “gray zone” based on experimental data and its effect on the trueness in HIV results in the blood, cells, and tissues banks. Mathews J HIV AIDS. 2(1): 015

ABSTRACT

Background: The impact of false negative HIV results in the clinical decision is a major concern, principally in the blood, cells, and tissues banks due to the high risk of post-transfusion/post-transplant infection. The use of the “gray zone” in medical laboratory tests is not systematically used. Thus, it is up to the laboratory to decide on its use. This text analyses a model to determine the “gray zone” based on the Guide to the expression of uncertainty in measurement and using experimental data.

Materials and methods: Usually, the selected decision limit relies on a theoretical zone. Nevertheless, an empirical “gray zone” could be computed established on data already available in the medical laboratory offering a more realistic interval. An empirical model conforming to the “Uncertainty Approach” principles using intra-laboratory method is applied using short-term and long-term data.

Results and discussion: The expanded measurement uncertainty of the combination of the within-laboratory uncertainty and the bias uncertainty is 14% and 23% on the short-term and long-term, respectively. The impact of the indeterminate results of true negatives is non-significant (0.04%) to the budget. 

Conclusions: The use of a “gray zone” based on HIV experimental data should be classified as a good laboratory practice, contributing to decreasing the residual risk related to post-transfusion and post-transplant infection.

KEYWORDS

Gray Zone; Gum; HIV; ISO 15189; Measurement Uncertainty; Window Period.