Effect of site of sample collection and prandial state on blood glucose concentrations measured with a portable blood glucose meter in healthy dogs

2019 ◽  
Vol 80 (11) ◽  
pp. 995-1000 ◽  
Author(s):  
Jose L. Guevara ◽  
Karen M. Tobias ◽  
Jennifer E. Stokes ◽  
Xiaojuan Zhu ◽  
Rebecca A. Smith
2016 ◽  
Vol 19 (4) ◽  
pp. 707-713 ◽  
Author(s):  
A. Mori ◽  
H. Oda ◽  
E. Onozawa ◽  
S. Shono ◽  
T. Takahashi ◽  
...  

Abstract This study evaluated the accuracy and reproducibility of a human portable blood glucose meter (PBGM) for canine and feline whole blood. Reference plasma glucose values (RPGV) were concurrently measured using glucose oxidation methods. Fifteen healthy dogs and 6 healthy cats were used for blood sampling. Blood glucose concentrations and hematocrits were adjusted using pooled blood samples for our targeted values. A positive correlation between the PBGM and RPGV was found for both dogs (y = 0.877, x = −24.38, r = 0.9982, n = 73) and cats (y = 1.048, x = −27.06, r = 0.9984, n = 69). Acceptable results were obtained in error grid analysis between PBGM and RPGV in both dogs and cats; 100% of these results were within zones A and B. Following ISO recommendations, a PBGM is considered accurate if 95% of the measurements are within ± 15 mg/dl of the RPGV when the glucose concentration is <100 mg/dl and within ±15% when it is ≥100 mg/dl; however, small numbers of samples were observed inside the acceptable limits for both dogs (11%, 8 of 73 dogs) and cats (39%, 27 of 69 cats). Blood samples with high hematocrits induced lower whole blood glucose values measured by the PBGM than RPGV under hypoglycemic, normoglycemic, and hyperglycemic conditions in both dogs and cats. Therefore, this device is not clinically useful in dogs and cats. New PBGMs which automatically compensate for the hematocrit should be developed in veterinary practice.


2001 ◽  
Vol 305 (1-2) ◽  
pp. 81-87 ◽  
Author(s):  
David A Vote ◽  
Owen Doar ◽  
Richard E Moon ◽  
John G Toffaletti

2021 ◽  
pp. 1-9
Author(s):  
Haifen Zhang ◽  
Shuhui Lailan ◽  
Shiyu Zhao ◽  
Qian Liu ◽  
Nina Fang ◽  
...  

BACKGROUND: Portable blood glucose meters are the main method for detecting the blood glucose status of clinical patients. OBJECTIVE: To investigate the accuracy of detecting blood glucose in haemodialysis patients by sampling two blood glucose meters through the haemodialysis line. METHODS: Convenient sampling was used to select 80 patients with maintenance haemodialysis. The patients were sampled through the arterial end of the haemodialysis line within three minutes of being put on the machine. One specimen was tested by glycemeter1, which can identify the type of blood in the arteries and veins, and glycemeter2, which can only detect blood glucose in the capillaries for bedside blood glucose testing. The other specimen was sent to the laboratory biochemical analyser for blood glucose testing. RESULTS: When the blood glucose value of the first blood glucose meter (No. 1) was compared with the laboratory biochemical analyser, the correlation coefficient was r = 0.805 (p < 0.05), the out of value of the first blood glucose meter accounted for 4.4%, and the consistency reached 95% (p < 0.05). When the blood glucose value of the second blood glucose meter (No. 2) was compared with the laboratory biochemical analyser, the correlation coefficient was r = 0.800 (p < 0.05), the out of value of the second blood glucose meter accounted for 4.4%, and the consistency reached 95% (p < 0.05). CONCLUSIONS: For patients with maintenance haemodialysis, the blood glucose values detected by the two bedside blood glucose meters using arteriovenous mixed blood in the pipeline do not affect the accuracy and can respond more realistically.


Author(s):  
Juan C. Lavariega ◽  
Gustavo A. Córdova ◽  
Lorena G. Gómez ◽  
Alfonso Avila

This chapter is an updated version of a previous work about the authors' project on monitoring pregnancy progress in rural areas and/or areas with poor support of medical services. The project is based on an information technology solution based on mobile devices and health sensors such as electrocardiogram, stethoscope, pulse-oximeter, and blood-glucose meter to automatically collect relevant health data for monitoring pregnancy. In this chapter, the authors provide a detailed description of the software architecture of the system. They include a description of the test they have been performing and the difficulties they have faced for the complete implementation of their system.


Sign in / Sign up

Export Citation Format

Share Document