A Novel Approach to Hematology Testing at the Point of Care.

Bransky A, Larsson A, Aardal E, Ben-Yosef Y, Christenson RH

J Appl Lab Med - (-) - [2020-12-04; online 2020-12-04]

The need for rapid point-of-care (POC) diagnostics is now becoming more evident due to the increasing need for timely results and improvement in healthcare service. With the recent COVID-19 pandemic outbreak, POC has become critical in managing the spread of disease. Applicable diagnostics should be readily deployable, easy to use, portable, and accurate so that they fit mobile laboratories, pop-up treatment centers, field hospitals, secluded wards within hospitals, or remote regions, and can be operated by staff with minimal training. Complete blood count (CBC), however, has not been available at the POC in a simple-to-use device until recently. The HemoScreen, which was recently cleared by the FDA for POC use, is a miniature, easy-to-use instrument that uses disposable cartridges and may fill this gap. The HemoScreen's analysis method, in contrast to standard laboratory analyzers, is based on machine vision (image-based analysis) and artificial intelligence (AI). We discuss the different methods currently used and compare their results to the vision-based one. The HemoScreen is found to correlate well to laser and impedance-based methods while emphasis is given to mean cell volume (MCV), mean cell hemoglobin (MCH), and platelets (PLT) that demonstrate better correlation when the vision-based method is compared to itself due to the essential differences between the underlying technologies. The HemoScreen analyzer demonstrates lab equivalent performance, tested at different clinical settings and sample characteristics, and might outperform standard techniques in the presence of certain interferences. This new approach to hematology testing has great potential to improve quality of care in a variety of settings.

Category: Other

Type: Journal article

PubMed 33274357

DOI 10.1093/jalm/jfaa186

Crossref 10.1093/jalm/jfaa186

pii: 6020101


Publications 7.1.2