Relative inaccuracy of the A1cNow in children with type 1 diabetes

Point-of-Care HbA1c in Clinical Practice: Caveats and Considerations for Optimal Use

Hemoglobin A1c (A1C) is widely used for the diagnosis and management of diabetes. Accurate measurement of A1C is necessary for optimal clinical value. Assay standardization has markedly improved the accuracy and consistency of A1C testing. Devices to measure A1C at point of care (POC) are commercially available, allowing rapid results when the patient is seen. In this review, we describe how standardization of A1C testing was achieved, leading to high-quality results in clinical laboratories. We address the use of POC A1C testing in clinical situations and summarize the advantages and disadvantages of POC A1C testing. We emphasize the importance of considering the limitations of these devices and following correct testing procedures to ensure that accurate A1C results are obtained for optimal care of patients.

Rapid Adoption of Telemedicine Along with Emergent Use of Continuous Glucose Monitors in the Ambulatory Care of Young Persons with New-Onset Type 1 Diabetes in the Time of COVID-19: A Case Series

Aims: The COVID-19 pandemic has caused strain on hospital systems and potential delay in diagnosis of type 1 diabetes (T1D). Outpatient diagnosis and treatment of metabolically stable young persons with new-onset T1D have been shown to be equivalent to inpatient. We describe an approach to outpatient management of newly diagnosed T1D during the COVID-19 pandemic using an interdisciplinary team, telemedicine, and diabetes technologies including rapid implementation of continuous glucose monitoring (CGM). Methods: Following the onset of the COVID-19 pandemic, new-onset cases of T1D were tracked. After laboratory confirmation of diagnosis and metabolic stability, patients and families were referred for ambulatory initiation of insulin therapy and diabetes education. These cases were reviewed using data extracted from the electronic health record, comments from multidisciplinary team members, and cloud-based glucose data. Results: We report on seven young people with new-onset T1D without diabetic ketoacidosis from April to June 2020, during the COVID-19 pandemic. Ages ranged 9-23 years with presenting hemoglobin A1c (HbA1c) values 10-14.5%. Initial evaluation was generally face-to-face, followed by frequent telemedicine visits. Five patients had a family history of T1D. Two patients had access to at-home HbA1c kits prompting evaluation in the absence of symptoms. Four patients required emergency department evaluation. Five patients presented with ketosis. All patients were prescribed CGM at the first visit, most starting within 1 month. Conclusions: Technology is extraordinarily useful for the care of young persons with new-onset T1D in the ambulatory setting during the COVID-19 pandemic. Large observational studies are needed to better understand outcomes of an outpatient, technology-focused approach.

Assessment of the performance of A1CNow(+) and development of an error grid analysis graph for comparative hemoglobin A1c measurements

BACKGROUND

This study investigated the performance of the A1CNow(+®) test (Bayer Diabetes Care, Sunnyvale, CA) in a large population of Chinese patients with diabetes.

SUBJECTS AND METHODS

Hemoglobin A1c (HbA1c) levels in 1,618 Chinese patients with diabetes 10-94 years of age were measured with both the A1CNow(+) test, from a fingerstick blood sample, and the high-performance liquid chromatography (HPLC) test, using a venous blood sample, within 24 h. The reportable ranges of the HbA1c values were 4.0-13.0% (A1CNow(+)) and 4.1-16.8% (HPLC). An error grid analysis (EGA) method was developed to quantify the accuracy of the A1CNow(+) results against the HPLC reference results.

RESULTS

The A1CNow(+) results were highly correlated with the HPLC reference results (r=0.945, P<0.01). Passing-Bablok regression analysis showed a good linear agreement between the two variables, and the linear regression equation fitted as y=-0.10+1.00x (P=0.21). The Bland-Altman difference plot presented that the mean bias of the A1CNow(+) results minus the HPLC reference results was -0.09% (P<0.001); the 95% confidence intervals for the limits of agreement were -1.28% to 1.09%, with 96.5% of the data points lying within this zone. The results of the EGA showed that 80.2% of the A1CNow(+) results were accurate, 17.7% were acceptable, 1.9% may lead to inappropriate treatment, and 0.3% may lead to severe clinical consequence.

CONCLUSIONS

The A1CNow(+) test values demonstrated a slight negative bias from the HPLC values. The majority of A1CNow(+) test values were accurate when compared with results from the reference method.

Diabetes research in children network:availability of protocol data sets

The Diabetes Research in Children Network (DirecNet) was established in 2001 by the National Institute of Child Health and Human Development and the National Institute of Diabetes and Digestive and Kidney Diseases through special congressional funding for type 1 diabetes research. The network consists of five clinical centers, a coordinating center, and a central laboratory. Since its inception, DirecNet has conducted nine protocols, resulting in 28 published manuscripts with an additional 2 under review and 5 in development. The protocols have involved evaluation of technology available for the treatment of type 1 diabetes, including home glucose meters (OneTouch Ultra, FreeStyle, and BD Logic), continuous glucose monitoring systems (GW2B, CGMS, FreeStyle Navigator, and Guardian RT), and hemoglobin A1c (HbA1c) devices (DCA 2000 and A1cNow). In addition, the group has conducted several studies evaluating factors affecting hypoglycemia, including exercise and bedtime snack composition. The data sets that have resulted from these studies include data from the devices being evaluated, central laboratory glucose, HbA1c and hormone data, clinical center glucose and HbA1c data, accelerometer data, and pump data depending on the procedures involved with each protocol. These data sets are, or will be, available at no charge on the study group's public Web site. Several psychosocial questionnaires developed by DirecNet are also available.

Advances in hemoglobin A1c point of care technology

Measurement of hemoglobin A1c (A1C) has long been accepted as the best indicator of glucose control over time. Assays for A1C use technologies based on either charge differences (high-pressure liquid chromatography) or structure (boronate affinity or immunoassay combined with general chemistry). These technologies are generally employed in expensive laboratory instruments. More recently, A1C technology has been incorporated into point of care (POC) devices, allowing for immediate availability of A1C measurements, greatly facilitating diabetes care in both specialist and general practices. POC A1C tests should have acceptable performance, standardization to national reference, National Glycohemoglobin Standardization Program (NGSP) certification, simple operation without need for costly instrumentation, and Clinical Laboratory Improvement Amendments (CLIA) waiver. CLIA-waived POC technology includes Bio-Rad MicroMat II (distributed by Cholestech as GDX) and the Axis-Shield Afinion, both of which utilize boronate affinity. The DCA 2000(R)+ utilizes combined immunoassay and general chemistry. These instruments cost $1000 to $3000 and require regular maintenance, making them appropriate only for high-volume physician offices. The newly improved A1CNow+ also utilizes combined immunoassay and general chemistry, but the small, inexpensive, disposable monitor can be used by patients as well as by health care professionals. The new version of A1CNow+ has improved performance through recent introduction of automated solid state chemistry manufacturing, improved fluidics and automated assembly of the test cartridge, error-correcting software, and unitary meter calibration with factory calibration directly to the NGSP reference standard.