There seems to be a bidirectional relationship between diabetes and COVID-19. In fact, diabetes has been consistently reported as one of the most important risk factors of severe COVID-19 and related mortality. On the other hand, emerging evidence suggests a specific impact of COVID-19 on diabetes itself.
Cases of new-onset diabetes as well as acute, severe metabolic complications of pre-existing diabetes have been seen in people with COVID-191,2. In particular, there have been reports of life-threatening alterations of glucose metabolism, including both diabetic keto-acidosis (DKA) as well as hyperosmolar syndrome1-3. These manifestations of diabetes pose significant challenges in clinical management and suggest a complex pathophysiology.
SARS-Cov-2, the virus responsible for COVID-19, binds to ACE-2 receptors, which are expressed in several key metabolic organs and tissues including the pancreatic β-cells, adipose tissue, small intestine, liver, and kidney4. Thus, it is plausible that SARS-Cov-2 could cause multiple co-existing alterations of glucose metabolism that can complicate the pathophysiology of pre-existing diabetes or lead to new mechanisms of disease. There are, in fact, precedents for a viral etiology for ketosis-prone diabetes5.
There is, therefore, a very urgent need to characterize such COVID-19-related diabetes to inform the clinical management of people affected and explore potentially novel mechanisms of disease, particularly in communities disproportionally affected with poor outcomes in COVID-19 infections, those of Black ethnicity and those with increased body weight or BMI.
What We Don’t Know:
It is still unclear if the alterations of glucose metabolism that acutely occur with severe COVID-19 will persist after resolution of COVID-19, or remit when the infection resolves. If diabetes remits, do patients remain at higher risk of future diabetes or DKA? Does this phenomenon represent abrupt onset of classical type 1 and type 2 diabetes or a new type of diabetes? Answering these questions is a priority of vital importance to inform the immediate clinical management, follow-up and monitoring of those affected.
Aims of the CoviDiab Registry Project:
To establish the extent of, and characterize new-onset, COVID-19-related diabetes, and to investigate its pathogenesis, management and outcomes
We also aim to characterize the clinical course and outcomes of diabetes in patients with pre-existing disease that acutely develop severe metabolic complications during COVID-19, such as diabetic keto-acidosis (DKA) and hyperosmolar non-ketotic hyperglycaemia (HONKS).
The CoviDiab Registry Investigators are establishing an international clinical registry to determine the presentation and course of diabetes in COVID-19 disease and investigate its pathogenesis, management and outcomes.
The registry includes a minimal dataset, to be entered by all contributors (clinicians, researchers and authorised database managers). This will allow the establishment of the range of phenotypes at presentation and during recovery, focusing on phenotype, ethnicity, body habitus, insulin requirements and outcomes. The extended dataset (for additional data when available) will allow us to investigate questions of insulin secretory capacity, insulin resistance and autoimmune antibody status in greater detail. Data collection includes follow up after resolution of COVID-19, with specific regard to persistence, remission and relapse of diabetes.
To ensure capturing exclusive new-onset diabetes, only data from patients with confirmed COVID-19 diagnosis, negative history of diabetes and hyperglycemia in the context of documented normal HbA1c will be considered.
To ensure timely acquisition of a sufficiently large set of observations the registry will draw data from across the world. The registry uses established methodology behind similar international registries (Dendrite Clinical Systems)6.
CoviDiab Registry Investigators will work to quickly promote the registry through a number of initiatives, including seeking collaborations with national and international professional organizations, academic centres, hospital networks and other existing registry and databases.
Registry and Data Management:
The registry will be fully anonymised and researchers will have no access to patients’ personal identifiers. Data about clinical observations will be entered by clinicians that are members of the care team for the individual patient or by authorised research personnel when data are transferred from other research databases (i.e. other registries authorised to collect COVID-19 related observations). All “contributors” will have to register before being able to enter data into the registry. To be registered as “contributor’, clinicians/research coordinators will be asked to provide information about their professional credentials (i.e. GMC registration number for UK clinicians, or equivalent registration for other national medical bodies; statement of employment by responsible officers for research coordinators), state their type of medical practice; and Institutional affiliations).
Identifiers that could indirectly identify individual patients, such as their names, date of birth, date of death, residential postal code, medical insurance or hospital number will not be entered into the registry. No identifier is to be used in the registry database and the clinical data will be fully anonymised at source. In no circumstances will patients’ identifiable data be available to anyone outside of their own care teams or authorised local administration/research personnel (as specified above).
To ensure maintaining anonymised data in the registry while allowing follow up data to be correctly entered by the contributors, the registry generates a progressive unique number (Registry Unique Number, RUN) for each patient. Contributors will need to appropriately store the RUN and use it to enter follow-up data about individual patients. Patient data will not at any stage be held in identifiable form by the registry managers or any CoviDiab Registry Investigator.
Expected Outcomes Plans for Analysis:
A plan for statistical analysis will be determined by the research team in due time, and analyses will be appropriately scheduled to ensure timely reports of outcomes to inform clinical practice. Subset analyses will be performed to explore associations between symptoms, features and outcomes of newly diagnosed diabetes and patients demographics as well as for characterization of pathophysiology. The data from this registry will also be used to develop downstream hypotheses and inform the design of further research studies, for which we will seek specific ethics approval.
- Y. Jie Chee, S. Jia Huey Ng, E. Yeoh, Diabetic ketoacidosis precipitated by Covid-19 in a patient with newly diagnosed diabetes mellitus, Diabetes Research and Clinical Practice (2020), doi: https://doi.org/10.1016/j.diabres.2020.108166
- Juyi Li; Xiufang Wang; Jian Chen; et al; COVID-19 infection may cause ketosis and ketoacidosis; Diabetes Obes Metab; 2020 Apr 20; doi: 10.1111/dom.14057
- Huihui Ren, Yan Yang, Fen Wang, Association of the insulin resistance marker TyG index with the severity and mortality of COVID‑19. Cardiovasc Diabetol (2020) 19:58 https://doi.org/10.1186/s12933-020-01035-2
- Hamming I, Timens W, Bulthuis ML, et al. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. J Pathol 2004; 203(2): 631-7
- Sobngwi E, Choukern SP, Agbalika F; Ketosis-prone type 2 diabetes mellitus and human herpesvirus 8 infection in sub-saharan Africans. JAMA 2008 Jun 18;299(23):2770-6. doi: 10.1001/jama.299.23.2770
- Welbourn R, Hollyman M, Kinsman R, et al. Bariatric surgery worldwide: baseline demographic description and one-year outcomes from the Fourth IFSO Global Registry Report 2018. Obes Surg. 2019 (3):782-795. doi: 10.1007/s11695-018-3593-1.