Beyond monitoring: Validation of the StatStrip Glucose Meter
as a diagnostic tool for diabetes mellitus
M. Vučić Lovrenčić, V. Radišić Biljak, S. Božičević, E. Pape-Medvidović1
Institute of Medical Biochemistry and Laboratory Medicine, 1Vuk Vrhovac University Clinic
MERKUR Teaching Hospital - Zagreb, CROATIA
Abstract (lick on the text to edit)
Background
Methods
Despite many potential advantages, the use of POCT
glucose meters for screening and diagnosis of diabetes has
been considered to be unreliable due to insufficient accuracy.
According to the World Health Organization (WHO)
recommendations, diagnostic procedure for diabetes
includes fasting plasma glucose measurement, followed by a
75g oral glucose tolerance test in asymptomatic individuals
with previous history of dysglycaemia and fasting plasma
glucose values below 7.0 mmol/L, and subsequent
classification of glycaemic status using respective diagnostic
criteria.
Aim
The aim of this study was to validate the performance of a
POCT glucose analyzer specifically designed for hospital
use (StatStrip Glucose, Nova Biomedical, USA) within the
diagnostic procedure used for classifying diabetes and
intermediate hyperglycaemia.
Fasting blood samples were taken from consenting
subjects, referred to our Clinic with a working diagnosis of
dysglycaemia. Venous and capillary sample collection was
carried out within 5 minutes for the reference laboratory
method (RLM, hexokinase, Olympus AU400, Beckman
Coulter, USA) and StatStrip glucose measurement,
respectively.
Heparinized
venous
samples
were
immediately placed on ice and plasma separated from the
cells by centrifugation (3000 rpm, 10 min) within 30
minutes from sampling, in order to avoid the effect of in
vitro glycolysis on plasma glucose results. A 75 g oral
glucose tolerance test was performed in subjects with
inconclusive fasting glycaemia, followed by the respective
blood sampling 2 hours after glucose load. WHO criteria
for venous and capillary plasma glucose were used to
classify
patients
into
diagnostic
categories
of
normoglycaemia (NG), impaired fasting glucose (IFG),
impaired glucose tolerance (IGT) and diabetes mellitus
(DM).
Results
Abstract
(lick on the text to edit)
A total of 180 subjects (M/F: 80/100; age range 18-89, median 56 years) were included in this study. oGTT was performed in
subjects without clinical symptoms of diabetes, who had fasting plasma glucose below diagnostic treshold (7.0 mmol/L, n=88).
Passing-Bablok regression analysis showed excellent correlation between plasma glucose values measured by StatStrip and
rreference laboratory method (RLM) in fasting samples (Fig 1A) and a systematic positive bias in post-oGTT samples (Fig 1B).
Inter-rater agreement analysis showed very good agreement (weighted kappa=0,839) between the methods when classifying
subjects in diagnostic categories of normoglycaemia, intermediate hyperglycaemia and diabetes by sample type-related
classification criteria.
Figure 1
Comparison of glucose values measured with
StatStrip Glucose Hospital Meter vs. Reference laboratory
method (RLM) in fasting (A, n=180) and 2h post-oGTT
samples (B, n=88).
Table 1 Classification of glyceamic status between StatStrip
and reference laboratory method (RLM) validated by inter-rater
agreement analysis.
CLASSIFICATION
A
B
y= 0.261+0.98x
RLM
y= 1.23+0.9333x
StatStrip
DM
IFG
IGT
NG
N (%)
DM
IFG
IGT
114
0
3
4
11
1
1
1
9
0
1
3
119
13
16
(66.1%) (7.2%) (8.9%)
Weighted kappa = 0.839
NG
0
6
1
25
32
(17.8%)
N (%)
117 (65.0%)
22 (12.2%)
12 (6.7%)
29 (16.1%)
180
(100%)
Conclusion
This study revealed an excellent correlation between plasma glucose values measured by StatStrip POCT glucose analyzer
and reference laboratory method in subjects undergoing diagnostic procedure for diabetes mellitus. Significant bias observed
between results in 2h post-oGTT samples reflects well-known metabolic differences between capillary and venous blood.
However, this had no influence on classification of glycaemic status between normal and diabetic, when appropriate, sampletype-related diagnostic criteria were used.
Our data suggest that StatStrip POCT glucose analyzer might serve as a powerful tool for screening and diagnosis of diabetes
mellitus.
6th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD)
Paris, France, 2013