Access to insulin delivery devices and glycated haemoglobin in lower-income countries

Affordable oral proinsulin bioencapsulated in plant cells regulates blood sugar levels similar to natural insulin

Diabetes Mellitus is a silent epidemic affecting >500 million, which claimed 6.7 million lives in 2021, a projected increase of >670% in <20 years old in the next two decades but insulin is unaffordable for the large majority of the globe. Therefore, we engineered proinsulin in plant cells to facilitate oral delivery. Stability of the proinsulin gene and expression in subsequent generations, after removal of the antibiotic-resistance gene, was confirmed using PCR, Southern and western blots. Proinsulin expression was high (up to 12 mg/g DW or 47.5% of total leaf protein), stable up to one year after storage of freeze-dried plant cells at ambient temperature and met FDA regulatory requirements of uniformity, moisture content and bioburden. GM1 receptor binding, required for uptake via gut epithelial cells was confirmed by pentameric assembly of CTB-Proinsulin. IP insulin injections (without C peptide) in STZ mice rapidly decreased blood glucose level leading to transient hypoglycemia, followed by hepatic glucose compensation. On the other hand, other than the 15-min lag period of oral proinsulin (transit time required to reach the gut), the kinetics of blood sugar regulation of oral CTB-Proinsulin in STZ mice was very similar to naturally secreted insulin in healthy mice (both contain C-peptide), without rapid decrease or hypoglycemia. Elimination of expensive fermentation, purification and cold storage/transportation should reduce cost and increase other health benefits of plant fibers. The recent approval of plant cell delivery of therapeutic proteins by FDA and approval of CTB-ACE2 for phase I/II human clinical studies augur well for advancing oral proinsulin to the clinic.

Comparison of diagnostic accuracy for diabetes diagnosis: A systematic review and network meta-analysis

Aim

Fasting Plasma Glucose (FPG) and Hemoglobin A1c (HbA1c) are used as diagnostic tests for diagnosing diabetes mellitus, but it is unclear which test has the best diagnostic accuracy. This systematic review and network meta-analysis aimed to estimate the diagnostic accuracy of HbA1c ≥ 6.5%, FPG ≥ 126 mg/dl, and the combination of HbA1c ≥ 6.5% or FPG ≥ 126 mg/dl (HbA1c| FPG), compared with Oral Glucose Tolerance Test (OGTT) ≥ 200 mg/dl for diagnosis diabetes.

Materials and methods

We performed a comprehensive search in PubMed, Embase, Cochrane Library, and Scopus from inception to September 24th, 2021. Inclusion criteria were any study design comparing HbA1c ≥ 6.5%, FPG ≥ 126 mg/dl, and HbA1c ≥ 6.5% or FPG ≥ 126 mg/dl with OGTT ≥ 200 mg/dl as the reference test. Data were independently extracted, risk of bias was assessed using QUADAS-2 by two reviewers. Network meta-analysis was done using a bivariate regression model using the Bayesian framework. The relative ranking of all tests was also assessed.

Results

Out of 5,026 studies, 73 were included. The sensitivities of HbA1c, FPG, and HbA1c| FPG were 0.51 [95% Credible Interval (CrI): 0.43, 0.58], 0.49 (95% CrI: 0.43, 0.55), and 0.64 (95% CrI: 0.51, 0.75), while the specificities were 0.96 (95% CrI: 0.94, 0.97), 0.98 (95% CrI: 0.97, 0.98), and 0.95 (95% CrI: 0.88, 0.98), respectively. The corresponding positive likelihood ratios (LR) were 13.36 (95% CrI: 8.91, 20.72), 21.94 (95% CrI: 15.04, 31.88), and 11.78 (95% CrI: 5.48, 26.56). HbA1c| FPG is superior based on sensitivity, whereas FPG is ranked best based on specificity and positive LR.

Conclusion

Our findings suggest that FPG ≥ 126 mg/dl should be recommended as the best diagnostic test for diabetes.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42021282856.

Time to first optimal glycemic control and its predictors among type 1 diabetic children in Bahir Dar city public referral hospitals, North West Ethiopia: a retrospective follow up study

Background

Recognizing the level of glycemic control of a client is an important measure/tool to prevent acquiring complications and risk of death from diabetes. However, the other most important variable, which is the time that the patient stayed in that poor glycemic level before reaching optimal glycemic control, has not been studied so far. Therefore, this study aim to estimate time to first optimal glycemic control and identify predictors among type 1 diabetic children in Bahir Dar city public referral hospitals, Northwest, Ethiopia, 2021.

Methods

A Retrospective cohort study was conducted at Bahir Dar city public referral hospitals among a randomly selected sample of 385 patients with type 1 diabetes who were on follow up from January 1, 2016 to February30, 2021.Data were collected by using a data abstraction tool and then entered into Epi-data version 4.6 and exported into STATA 14.0 statistical software. Descriptive statistics, Kaplan Meier plots and median survival times, Log-rank test and Cox-proportional hazard regression were used for reporting the findings of this study. After performing Cox-proportional hazard regression, model goodness-of-fit and assumptions were checked. Finally, the association between independent variables and time to first optimal glycemic control in months was assessed using the multivariable Cox Proportional Hazard model and variables with a p-value < 0.05 were considered as statistically significant.

Results

Median survival time to first optimal glycemic control among type 1 diabetic clients was 8 months (95%CI: 6.9–8.9). The first optimal glycemic achievement rate was 8.2 (95%CI: 7.2–9.2) per 100 person/month observation. Factors that affect time to first optimal glycemic control were age > 10–14 years (AHR = 0.32;95%CI = 0.19–0.55), increased weight (AHR = 0.96;95%CI = 0.94–0.99), having primary care giver (AHR = 2.09;95%CI = 1.39–3.13), insulin dose (AHR = 1.05;95%CI = 1.03–1.08), duration of diabetes ≥4 years (AHR = 0.64;95%CI = 0.44–0.94), adherence to diabetic care (AHR = 9.72;95%CI = 6.09–15.51), carbohydrate counting (AHR = 2.43;95%CI = 1.12–5.26), and comorbidity (AHR = 0.72;95%CI = 0.53–0.98).

Conclusion

The median survival time to first optimal glycemic control in this study was long. Age, weight, primary care giver, insulin dose, duration of diabetes, adherence, and carbohydrate counting, including history of comorbidity were determinant factors. Giving attention for overweight and comorbid illness prevention, increasing either the dose or frequency of insulin during initial treatment; counseling parent (for both the mother and father) about adherence to diabetic care focusing on insulin drugs and how to audit their children’s diet as prescription helps to reduce the length of glycemic control.

Protocol for a feasibility randomised control trial for continuous glucose monitoring in patients with type 1 diabetes at first-level hospitals in rural Malawi

INTRODUCTION

The majority of people living with type 1 diabetes (PLWT1D) struggle to access high-quality care in low-income countries (LICs), and lack access to technologies, including continuous glucose monitoring (CGM), that are considered standard of care in high resource settings. To our knowledge, there are no studies in the literature describing the feasibility or effectiveness of CGM at rural first-level hospitals in LICs.

METHODS AND ANALYSIS

This is a 3-month, 2:1 open-randomised trial to assess the feasibility and clinical outcomes of introducing CGM to the entire population of 50 PLWT1D in two hospitals in rural Neno, Malawi. Participants in both arms will receive 2 days of training on diabetes management. One day of training will be the same for both arms, and one will be specific to the diabetes technology. Participants in the intervention arm will receive Dexcom G6 CGM devices with sensors and solar chargers, and patients in the control arm will receive Safe-Accu home glucose metres and logbooks. All patients will have their haemoglobin A1c (HbA1c) measured and take WHO Quality of Life assessments at study baseline and endline. We will conduct qualitative interviews with a selection of participants from both arms at the beginning and end of study and will interview providers at the end of the study. Our primary outcomes of interest are fidelity to protocols, appropriateness of technology, HbA1c and severe adverse events.

ETHICS AND DISSEMINATION

This study is approved by National Health Sciences Research Committee of Malawi (IRB Number IR800003905) and the Mass General Brigham (IRB number 2019P003554). Findings will be disseminated to PLWT1D through health education sessions. We will disseminate any relevant findings to clinicians and leadership within our study catchment area and networks. We will publish our findings in an open-access peer-reviewed journal.

TRIAL REGISTRATION NUMBER

PACTR202102832069874.

HbA1c performs well in monitoring glucose control even in populations with high prevalence of medical conditions that may alter its reliability: the OPTIMAL observational multicenter study

INTRODUCTION

The utility of HbA1c (glycosylated hemoglobin) to estimate glycemic control in populations of African and other low-resource countries has been questioned because of high prevalence of other medical conditions that may affect its reliability. Using continuous glucose monitoring (CGM), we aimed to determine the comparative performance of HbA1c, fasting plasma glucose (FPG) (within 5 hours of a meal) and random non-fasting glucose (RPG) in assessing glycemic burden.

RESEARCH DESIGN AND METHODS

We assessed the performance of HbA1c, FPG and RPG in comparison to CGM mean glucose in 192 Ugandan participants with type 2 diabetes. Analysis was undertaken in all participants, and in subgroups with and without medical conditions reported to affect HbA1c reliability. We then assessed the performance of FPG and RPG, and optimal thresholds, in comparison to HbA1c in participants without medical conditions thought to alter HbA1c reliability.

RESULTS

32.8% (63/192) of participants had medical conditions that may affect HbA1c reliability: anemia 9.4% (18/192), sickle cell trait and/or hemoglobin C (HbC) 22.4% (43/192), or renal impairment 6.3% (12/192). Despite high prevalence of medical conditions thought to affect HbA1c reliability, HbA1c had the strongest correlation with CGM measured glucose in day-to-day living (0.88, 95% CI 0.84 to 0.91), followed by FPG (0.82, 95% CI 0.76 to 0.86) and RPG (0.76, 95% CI 0.69 to 0.81). Among participants without conditions thought to affect HbA1c reliability, FPG and RPG had a similar diagnostic performance in identifying poor glycemic control defined by a range of HbA1c thresholds. FPG of ≥7.1 mmol/L and RPG of ≥10.5 mmol/L correctly identified 78.2% and 78.8%, respectively, of patients with an HbA1c of ≥7.0%.

CONCLUSIONS

HbA1c is the optimal test for monitoring glucose control even in low-income and middle-income countries where medical conditions that may alter its reliability are prevalent; FPG and RPG are valuable alternatives where HbA1c is not available.

A global perspective on the issue of access to insulin

The discovery of insulin in 1921 changed the prognosis for people with type 1 diabetes. A century later, availability and affordability of insulin remain a challenge in many parts of the globe. Using the WHO's framework on understanding the life cycle of medicines, this review details the global and national challenges that affect patients' abilities to access and afford insulin. Current research and development in diabetes has seen some innovations, but none of these have truly been game-changing. Currently, three multinational companies control over 95% of global insulin supply. The inclusion of insulin on the WHO's Prequalification Programme is an opportunity to facilitate entry of new companies into the market. Many governments lack policies on the selection, procurement, supply, pricing and reimbursement of insulin. Moreover, mark-ups in the supply chain also affect the final price to the consumer. Whilst expenses related to diabetes are mostly covered by insurance in high-income countries, many patients from low- and middle-income countries have to pay out of their own pockets. The organisation of diabetes management within the healthcare system also affects patient access to insulin. The challenges affecting access to insulin are complex and require a wide range of solutions. Given that 2021 marks the centenary of the discovery of insulin, there is need for global advocacy to ensure that the benefits of insulin and innovations in diabetes care reach all individuals living with diabetes.

Diagnostics and monitoring tools for noncommunicable diseases: a missing component in the global response

A key component of any health system is the capacity to accurately diagnose individuals. One of the six building blocks of a health system as defined by the World Health Organization (WHO) includes diagnostic tools. The WHO’s Noncommunicable Disease Global Action Plan includes addressing the lack of diagnostics for noncommunicable diseases, through multi-stakeholder collaborations to develop new technologies that are affordable, safe, effective and quality controlled, and improving laboratory and diagnostic capacity and human resources. Many challenges exist beyond price and availability for the current tools included in the Package of Essential Noncommunicable Disease Interventions (PEN) for cardiovascular disease, diabetes and chronic respiratory diseases. These include temperature stability, adaptability to various settings (e.g. at high altitude), need for training in order to perform and interpret the test, the need for maintenance and calibration, and for Blood Glucose Meters non-compatible meters and test strips. To date the issues surrounding access to diagnostic and monitoring tools for noncommunicable diseases have not been addressed in much detail. The aim of this Commentary is to present the current landscape and challenges with regards to guidance from the WHO on diagnostic tools using the WHO REASSURED criteria, which define a set of key characteristics for diagnostic tests and tools. These criteria have been used for communicable diseases, but so far have not been used for noncommunicable diseases. Diagnostic tools have played an important role in addressing many communicable diseases, such as HIV, TB and neglected tropical diseases. Clearly more attention with regards to diagnostics for noncommunicable diseases as a key component of the health system is needed.