Development and validation of an arterial blood gas analysis interpretation algorithm for application in clinical laboratory services

Author:

Park Sang Hyuk1,An Dongheui1,Chang You Jin2,Kim Hyun Jung3,Kim Kyung Min3,Koo Tai Yeon3,Kim Sollip1,Lee Woochang1,Yang Won Seok3,Hong Sang-Bum4,Chun Sail1,Min Won-Ki1

Affiliation:

1. Department of Laboratory Medicine

2. Department of Internal Medicine

3. Division of Nephrology of Internal Medicine

4. Division of Pulmonary and Critical Care Medicine, University of Ulsan College of Medicine and Asan Medical Center, Seoul, Republic of Korea

Abstract

Background Arterial blood gas analysis (ABGA) is a useful test that estimates the acid–base status of patients. However, numerically reported test results make rapid interpretation difficult. To overcome this problem, we have developed an algorithm that automatically interprets ABGA results, and assessed the validity of this algorithm for applications in clinical laboratory services. Methods The algorithm was developed based on well-established guidelines using three test results (pH, PaCO2 and [HCO3]) as variables. Ninety-nine ABGA test results were analysed by the algorithm. The algorithm's interpretations and the interpretations of two representative web-based ABGA interpretation programs were compared with those of two experienced clinicians. Results The concordance rates between the interpretations of each of the two clinicians and the algorithm were 91.9% and 97.0%, respectively. The web-based programs could not issue definitive interpretations in 15.2% and 25.3% of cases, respectively, but the algorithm issued definitive interpretations in all cases. Of the 10 cases that invoked disagreement among interpretations by the algorithm and the two clinicians, half were interpreted as compensated acid–base disorders by the algorithm but were assessed as normal by at least one of the two clinicians. In no case did the algorithm indicate a normal condition that the clinicians assessed as an abnormal condition. Conclusions The interpretations of the algorithm showed a higher concordance rate with those of experienced clinicians than did two web-based programs. The algorithm sensitively detected acid–base disorders. The algorithm may be adopted by the clinical laboratory services to provide rapid and definitive interpretations of test results.

Publisher

SAGE Publications

Subject

Clinical Biochemistry,General Medicine

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