Glucose determination: The use of glucometers as a rapid test of analysis

• Main Authors: Gygliola-Ormachea Peggy Brenda, Tarquino-Flores Gabriela, Chambi-Gutierrez Edgar, Averanga-Conde Kattia, Salcedo-Ortiz Lily
• Format: Article
• Language: Spanish
• Published: Selva Andina Research Society 2020-02-01
• Series: Journal of the Selva Andina Research Society
• Subjects: glucose; glucometers; diabetes; erythrocytosis; anemia.
• Online Access: http://www.scielo.org.bo/scielo.php?script=sci_arttext&pid=S2072-92942020000100005&lng=es&nrm=iso&tlng=es
• ISSN: 2072-9294; 2072-9308

The objective of this study was to determine the usefulness of glucometers in relation to the standard laboratory method (MEL) in blood samples: healthy, diabetic, erythrocytic and anemic. The glucometers (GM) evaluated were ACCU CHEK Active in its two procedures (ACCU I and ACCU II), ONE TOUCH Ultra (ONETu) and Easy TRUEread (TRUEf). The ANOVA analysis of variance, p<0.005, was used. Of 54 healthy samples with hematocrit 49±4, ONETu did not show a significant difference with MEL, ACCU I, ACCU II and TRUEf showed significant differences, being TRUEf the one that revealed the greatest difference with over-estimated values in more than 30 mg / dL. Of 60 diabetic samples with hematocrit 48 ± 8, there were no significant differences between GM and MEL, however incongruous results were detected 2 to 3 times overestimated (13%) and 2 to 3 times undervalued (12%) with GM ONETu and TRUEf; ACCU I and ACCU II exposed slight inconsistencies. Of 54 erythrocyte samples with hematocrit 66 ± 6, underestimated values were detected in 20 mg / dL with ONETu and TRUEf (10%), ACCU I (18%); ACCU II reported overestimated values between 15-25 mg / dL (40%) with significant statistical difference. Of 40 anemic samples with hematocrit 29 ± 9, overestimated values were reported, 20% (ONETu), 35% (TRUEf), 45% (ACCU II) and 55% (ACCU I), with a difference greater than 20 mg / dL. The GM evaluated present different degrees of interference by diabetic, anemic and erythrocytic samples, in the case of erythrocytic samples, undervalued values are observed, in anemic samples overvalued values, these data should be considered for a better use of GM.