J Lab Med Qual Assur 2016; 38(4): 225-233
Published online December 31, 2016
https://doi.org/10.15263/jlmqa.2016.38.4.225
Copyright © Korean Association of External Quality Assessment Service.
YeJin Oh, Sun Hoe Koo, and Gye Cheol Kwon
Department of Laboratory Medicine, Chungnam National University Hospital, Chungnam National University School of Medicine, Daejeon, Korea
Correspondence to:Gye Cheol Kwon
Department of Laboratory Medicine, Chungnam National University Hospital, Chungnam National University School of Medicine, 282 Munhwa-ro, Junggu, Daejeon 35015, Korea
Tel: +82-42-280-7799 Fax: +82-42-257-5365 E-mail: kckwon@cnu.ac.kr
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: Point-of-care testing (POCT) is designed to be used near the site where the clinical care is being delivered. The demand for POCT in the medical field is expanding significantly, given that rapid results can eventually lead to early diagnosis and immediate clinical management of diseases. Therefore, the aim of this study was to evaluate the performance of the i-STAT POC analyser (Abbott Diagnostics, USA) for testing 8 chemical analytes (viz., sodium, potassium, chloride, total carbon dioxide, blood urea nitrogen, creatinine, glucose, and ionised calcium) and 2 hematological analytes (hematocrit [HCT], hemoglobin [Hb]).
Methods: The precision and linearity of the 10 analytes were measured according to Clinical and Laboratory Standards Institute (CLSI) EP15-A3 and EP6-A guidelines. Comparisons with a central laboratory hematology analyser, Coulter LH 780 (Beckman Coulter Inc., USA), and a chemical analyser, UniCel DxC 880i (Beckman Coulter Inc.), were performed using 85 patient samples according to CLSI EP9-A3.
Results: The coefficient of variation values for the within-run precision and total precision at 3 levels of all analytes were within 5%, except those for low level creatinine. In the aspect of linearity, the correlation coefficient values of all analytes were over 0.975 in the clinically important concentration range. A very high correlation was observed in glucose, blood urea nitrogen and creatinine (R>0.975), high correlation was observed in sodium, potassium, Hct and Hb (R>0.9), and relatively good correlation was observed in chloride and total carbon dioxide (R>0.7) compared to the central laboratory analysers.
Conclusions: i-STAT showed relatively high precision and linearity, and comparable data to that of routine hematology and chemistry analysers. This device was concluded to have potential for providing faster results and relatively acceptable values to clinicians in need of immediate results.
Keywords: Point-of-care systems, i-STAT, Evaluation studies
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