Type 2 diabetes is a leading cause of chronic kidney disease globally. Around 10-40% of people with type 2 diabetes eventually suffer from kidney failure.
Good control of blood sugar levels could prevent complications of diabetes including kidney disease, although the level of blood sugar at which kidney function starts to decline is not known, and people with high blood sugar, but who are not yet diabetic might also be at risk. A simple blood test named glycated haemoglobin (usually called HbA1c) is used for the diagnosis of type 2 diabetes and monitoring of diabetes. However, kidney disease and associated complications such as anaemia, can make HbA1c inaccurate. Doctors are advised not to use HbA1c among people with kidney disease for this reason, although exactly how severe kidney disease needs to be before HbA1c is affected is also not known.
This study will use data from Clinical Practice Research Datalink (CPRD) to test how well HbA1c measures blood sugar among people with kidney disease with or without anaemia. We will then test how HbA1c predicts changes in kidney function. This will inform guidelines for setting targets for monitoring and control of blood sugar levels in people with high blood sugar and kidney disease, and ultimately help to prevent the progression of kidney disease.
The primary aim of this study is to understand how glycaemic control, measured by HbA1c predicts trajectories of chronic kidney disease (CKD), among patients with non-diabetic hyperglycaemia (HbA1c of 42-47mmol/mol) or with newly diagnosed type 2 Diabetes Mellitus (T2DM) (HbA1c of 48mmol/mol or greater). Although the relationship between HbA1c and renal outcomes is well described for patients with established T2DM, precise monitoring thresholds or ranges that would indicate lower progression rates of kidney failure is not known. Hence, a retrospective cohort study to assess this issue will be used: patients will enter the study at the first time at which HbA1c is measured at or above 42mmol/mol and will leave upon censoring, or death. A continuous time multi-state model will estimate the transition rate between CKD stages during follow-up, and transition to "absorbing" states of mortality from cardiovascular diseases (CVD) or other causes from each stage. Estimating the effect of glycaemia on each transition probability is the primary objective.
The utility of HbA1c for the measurement of glycaemia and diagnosis of DM has been well described. Since the measurement of glycaemic control is known to be affected by CKD and associated complications such as anaemia, we will first test the validity of HbA1c as a measure of glycaemic control at different CKD stages among anaemic and non-anaemic patients. Hence, the validity of HbA1c will be assessed by using all available occasions where HbA1c tests are paired with a fasting plasma glucose (FPG), Full Blood Count (FBC), defined by Haemoglobin (Hb) index, and where CKD stage is known. Using a regression analysis of HbA1c on FPG and CKD we will estimate the effect of CKD stage measured by glomerular filtration rate (GFR) and test the effect of anaemia on the relationship between CKD, glucose and HbA1c.
Primary Outcomes: The validity of glycated haemoglobin (HbA1c ) as a measure of glycaemia in patients with CKD with or without anaemia Chronic kidney disease (CKD) incidence and progression Secondary outcomes: Cardiovascular (CVD) mortality conditional on HbA1c and CKD stage Mortality from other non-CVD causes conditional on HbA1c and CKD stage
George Savva - Chief Investigator - University of East Anglia
Stamatina Maria Cheilari - Corresponding Applicant - University of East Anglia
Emma English - Collaborator - University of East Anglia
Kathryn Richardson - Collaborator - University of East Anglia
Paul Wisdom - Collaborator - University of East Anglia
Yoon Loke - Collaborator - University of East Anglia
ONS Death Registration Data;Practice Level Index of Multiple Deprivation