Point-of-care capillary HbA1c measurement in the emergency department: a useful tool to detect unrecognized and uncontrolled diabetes

How Can Point-of-Care Technologies Support In-Hospital Diabetes Care?

People with diabetes admitted to hospital are at risk of diabetes related complications including hypoglycaemia and diabetic ketoacidosis. Point-of-care (POC) tests undertaken at the patient bedside, for glucose, ketones, and other analytes, are a key component of monitoring people with diabetes, to ensure safety. POC tests implemented with a quality framework are critical to ensuring accuracy and veracity of results and preventing erroneous clinical decision making. POC results can be used for self-management of glucose levels in those well-enough and/or by healthcare professionals to identify unsafe levels. Connectivity of POC results to electronic health records further offers the possibility of utilising these results proactively to identify patients 'at risk' in real-time and for audit purposes. In this article, the key considerations when implementing POC tests for diabetes in-patient management are reviewed and potential to drive improvements using networked glucose and ketone measurements are discussed. In summary, new advances in POC technology should allow people with diabetes and the teams looking after them whilst in hospital to integrate to provide safe and effective care.

American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update

OBJECTIVE

The objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers.

METHODS

The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development.

RESULTS

This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes.

CONCLUSIONS

This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.

Diagnostic Accuracy of Point-of-Care Tests Measuring Glycosylated Haemoglobin (HbA1c) for Glycemic Control: A Field Study in India

Objectives This study was performed to estimate diagnostic accuracy of the two commercially available point-of-care tests to identify poor glycemic control defined by HbA1c levels, with high-performance liquid chromatography (HPLC) as a reference. Settings The study was carried at two locations, general medical outpatient department of a teaching medical college in Bhopal (urban), and a primary health care centre in a rural area in the state of Madhya Pradesh, India. Participants All individuals with diabetes mellitus who presented to the health care facility for assessment of glycemic control. We compared HbA1c estimated from two index tests (Hemocue Hb 501, Sweden; SD Biosensor, South Korea) from capillary blood samples with HPLC performed from venous blood, as a reference standard. Primary and secondary outcome measures Diagnostic properties of index tests such as sensitivity, specificity, positive and negative predictive value and diagnostic accuracy for identifying poor glycemic control were primary outcome measures. Lin's concordance correlation coefficient (CCC) was secondary outcome measure. Results Out of 114 patients, all received reference standard - 103 patients received Hemocue A1C test and 110 patients received SD Biosensor test. Overall both the index tests had similar diagnostic accuracy estimates. The area under the Receiver Operating Curve for SDA1c device was 0.935 (95% CI 0.886-0.983), and for Hemocue device was 0.938 (95% CI 0.893-0.984). The Hemocue device HbA1c value of above 7.0 (positive) correctly predicted poor glycemic control 92% times (81.58% for SD device). There were 4 vs. 11 device failures and 14 vs. 12 failures with SD and Hemocue, respectively. Ambient air temperatures were no different for the device test failures. Conclusions Commercially available point-of-care tests evaluated in this study are comparable and an acceptable alternative to HPLC-based measurements for the assessment of glycemic control. Tests and device failure rates of both the index tests are similar.

Diabetes Patient Surveillance in the Emergency Department: Proof of Concept and Opportunities

INTRODUCTION

The purpose of this study was to characterize the at-risk diabetes and prediabetes patient population visiting emergency department (ED) and urgent care (UC) centers in upstate South Carolina.

METHODS

We conducted this retrospective study at the largest non-profit healthcare system in South Carolina, using electronic health record (EHR) data of patients who had an ED or UC visit between February 2, 2016-July 31, 2018. Key variables including International Classification of Diseases, 10th Revision codes, laboratory test results, family history, medication, and demographic characteristics were used to classify the patients as healthy, having prediabetes, having diabetes, being at-risk for prediabetes, or being at-risk for diabetes. Patients who were known to have diabetes were classified further as having controlled diabetes, management challenged, or uncontrolled diabetes. Population analysis was stratified by the patient's annual number of ED/UC visits.

RESULTS

The risk stratification revealed 4.58% unique patients with unrecognized diabetes and 10.34% of the known patients with diabetes considered to be suboptimally controlled. Patients identified as diabetes management challenged had more ED/UC visits. Of note, 33.95% of the patients had unrecognized prediabetes/diabetes risk factors identified during their ED/UC with 87.95% having some form of healthcare insurance.

CONCLUSION

This study supports the idea that a single ED/UC unscheduled visit can identify individuals with unrecognized diabetes and an at-risk prediabetes population using EHR data. A patient's ED/UC visit, regardless of their primary reason for seeking care, may be an opportunity to provide early identification and diabetes disease management enrollment to augment the medical care of our community.

Cost-Effectiveness of Point-of-Care A1C Tests in a Primary Care Setting

Objective: We evaluated the cost-effectiveness of the point-of-care A1c (POC-A1c) test device vs. the traditional laboratory dosage in a primary care setting for people living with type 2 diabetes. Materials and Methods: The Markov model with a 10-year time horizon was based on data from the HealthRise project, in which a group of interventions was implemented to improve diabetes and hypertension control in the primary care network of the urban area of a Brazilian municipality. A POC-A1c device was provided to be used directly in a primary care unit, and for a period of 18 months, 288 patients were included in the point-of-care group, and 1,102 were included in the comparison group. Sensitivity analysis was performed via Monte Carlo simulation and tornado diagram. Results: The results indicated that the POC-A1c device used in the primary care unit was a cost-effective alternative, which improved access to A1c tests and resulted in an increased rate of early control of blood glucose. In the 10-year period, POC-A1c group presented a mean cost of US$10,503.48 per patient and an effectiveness of 0.35 vs. US$9,992.35 and 0.09 for the traditional laboratory test, respectively. The incremental cost was US$511.13 and the incremental effectiveness was 0.26, resulting in an incremental cost-effectiveness ratio of 1,947.10. In Monte Carlo simulation, costs and effectiveness ranged between $9,663.20-$10,683.53 and 0.33-0.37 for POC-A1c test group, and $9,288.28-$10,413.99 and 0.08-0.10 for traditional laboratory test group, at 2.5 and 97.5 percentiles. The costs for nephropathy, retinopathy, and cardiovascular disease and the probability of being hospitalized due to diabetes presented the greatest impact on the model's result. Conclusion: This study showed that using POC-A1c devices in primary care settings is a cost-effective alternative for monitoring glycated hemoglobin A1c as a marker of blood glucose control in people living with type 2 diabetes. According to our model, the use of POC-A1c device in a healthcare unit increased the early control of type 2 diabetes and, consequently, reduced the costs of diabetes-related outcomes, in comparison with a centralized laboratory test.

Diabetes Detection and Communication among Patients Admitted through the Emergency Department of a Public Hospital

Early identification/diagnosis of diabetes and frequent monitoring of hyperglycemia reduces hospitalizations and diabetes-related complications. The present study investigated the proportion of older adults coded with diabetes or newly diagnosed during their admissions and assessed discharge summary content for diabetes-related information. The study used electronic data on 4796 individuals aged ≥60 years admitted through the emergency department (ED) of a public hospital from 2017 to 2018 extracted using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM code). The proportion of admitted patients who were diagnosed with diabetes over a one-year period, proportion with glycated hemoglobin A1c (HbA1c) and random blood glucose (RBG) test performed during their stay, length of stay, discharge summary information and the factors associated with elevated HbA1c (>7%/53 mmol/mol) were investigated. In total, 8.6% of ED presentations to the hospital were coded with diabetes, excluding gestational consisting of 879 patients (449 males, 430 females) aged ≥ 60 years (74.6 ± 8.9 years). In total, 98% had type 2 diabetes (n = 863), 53% were Australian-born (n = 467), and the mean body mass index (BMI, 31 ± 7 kg/m²; n = 499, 56.8%), RBG (9.8 ± 5.2 mmol/L; n = 824, 93.7%) and HbA1c (8.0 ± 2.0%; n = 137, 15.6%) and length of stay (6.7 ± 25.4 days) were similar between gender, age, and nationality (p > 0.05). Three coded patients (0.3%) were newly diagnosed during the admission. In total, 86% had elevated HbA1c, but this was recorded in 20% of discharge summaries. Patients who are on a combination therapy (adjusted odds ratio 23%, 95% confidence intervals: 7%/38%), those on SGLT2 Inhibitors (aOR, 14%: 2%/26%) or had a change in medication (aOR, 40%: 22%/59%) had lower odds of having elevated HbA1c during admission. The low diagnosis rate of diabetes and the lack of clinical assessment of HbA1c in older adults admitted through the ED of a South Western Sydney public hospital suggest that many patients with diabetes either remain undiagnosed even during admission and/or are going to the ED with unknown diabetes that is unidentified with current practices. The clinically important HbA1c results were only infrequently communicated with general practitioners (GPs).

High Prevalence of Undiagnosed Hyperglycemia in Low-Income Overweight and Obese Hispanic Women in Oregon

BACKGROUND

Overweight Hispanic women are at high risk for type 2 diabetes. A clinical diagnosis of hyperglycemia is often necessary to access interventions. We examined the prevalence of undiagnosed hyperglycemia among a group of low-income overweight or obese Hispanic women, who were receiving care at a Federally Qualified Health Center (FQHC).

METHODS

Among 196 overweight or obese Hispanic women (mean age 44 ± 10 years, mean weight 86.8 ± 16.5 kg, mean body mass index [BMI] 36.5 ± 6.4 kg/m²) enrolled in a randomized clinical weight-loss trial, we compared A1C and fasting blood glucose (FBG) obtained at baseline with women's existing diabetes and prediabetes diagnoses in the medical record.

RESULTS

According to the information in participants' medical records, 36% (70/196) had diagnosed diabetes, 20% (39/196) had a diagnosis of prediabetes, and the remaining 44% (87/196) had neither diagnosis. Among participants without a diagnosis of diabetes or prediabetes during the baseline screening for our study, 63% (55/87) had at least one test in the prediabetes range (baseline A1C and FBG were in prediabetes range for 39 and 55 participants, respectively), and 13% (11/87) had at least one test in the diabetic range (baseline A1C and FBG values in diabetes range for 3 and 11 participants, respectively).

DISCUSSION

We found substantial prevalence of undiagnosed hyperglycemia among a sample of overweight and obese Hispanic women. It is possible that limited awareness of diabetes risk may be a barrier to patient compliance with screening recommendations.

Recommendations for in-clinic PoCT for diabetes management in India

A panel of expert diabetologist clinicians developed consensus standards to address the quality gaps inclinic point of care testing (PoCT) especially pertaining to diabetes care and management in India. The following summarized principles were established- 1. PoCT definition, 2. Advantages and critical aspects of PoCT including guideline recommendations and accreditations, analytical factors (pre &post analytical included) and consensus reached for an ideal PoC analyzer and 3. Key recommendations on in-clinic PoCT implementation by the panel. The experts suggested next steps that included key comparative (PoCT vs NGSP accredited lab) and patient benefit studies on PoCT.

Are point-of-care measurements of glycated haemoglobin accurate in the critically ill?

INTRODUCTION

Critically ill patients with type 2 diabetes mellitus (T2DM) and chronic hyperglycaemia may benefit from a more liberal approach to glucose control than patients with previously normal glucose tolerance. It may therefore be useful to rapidly determine HbA1c concentrations. Point-of-care (POC) analysers offer rapid results but may be less accurate than laboratory analysis.

AIM(S)

The aim of this study was to determine agreement between POC and laboratory HbA1c testing in critically ill patients with T2DM.

METHODS

Critically ill patients with T2DM had concurrent laboratory, capillary-, and arterial-POC HbA1c measurements performed. Data are presented as mean (standard deviation) or median [interquartile range]. Measurement agreement was assessed by Lin's concordance correlation coefficient, Bland-Altman 95% limits of agreement, and classification by Cohen's kappa statistic.

RESULTS

HbA1c analysis was performed for 26 patients. The time to obtain a result from POC analysis took a median of 9 [7, 10] minutes. Laboratory analysis took a median of 328 [257, 522] minutes from the time of test request to the time of report. Lin's correlation coefficient showed almost perfect agreement (0.99%) for arterial- vs capillary-POC and both POC methods vs arterial laboratory analysis. Bland-Altman plots showed a mean difference of 2.0 (3.7) with 95% limits of agreement of -5.4 to 9.3 for capillary vs laboratory, 1.6 (3.4) and -5.1 to 8.4 for arterial vs laboratory, and -0.137 (2.6) and -5.2 to 4.9 for capillary vs arterial. Patient classification as having inadequately controlled diabetes (>53 mmol/mol) showed 100% agreement across all tests.

CONCLUSIONS

HbA1c values can be accurately and rapidly obtained using POC testing in the critically ill.

Microwave-assisted synthesis of chitosan biguanidine hydrochloride and its regulation on InsR and GLUT2 in insulin resistant HepG2 cells

CSGH increased glucose consumption of HepG2 cells by accelerating the expression of InsR and inhibiting the high-insulin-induced over-expression of GLUT2.

Microwave-assisted synthesis of chitooligosaccharide guanidine and its effect on GLUT4-dependent glucose uptake through an Akt-activated protein kinase signaling pathway in L6 skeletal muscle cells

COSG was likely to be effective by increasing the phosphorylation level of Akt and promoting the membrane translocation of GLUT4, thereby increasing the glucose uptake of skeletal cells.