Type 2 diabetes is a chronic disease where the body produces reduced amounts of insulin and/or the body's ability to properly use the insulin is reduced. Studies have shown that obesity is closely linked to type 2 diabetes in general, while the link between excess body weight and length and cost of hospital stay for complications related to diabetes are less described in the literature. We want to investigate if body weight in terms of body mass index (BMI, classified as underweight, normal, pre-obese, obese class I, II and III) measured at the time of admission to the hospital influences the length and the cost of the stay at the hospital. For specific complications to Type 2 diabetes and for specific procedures to treat the complications, we want to investigate the relation between the mentioned categories of BMI and the length and cost of the stay at the hospital. Examples of complications include amongst others heart failure angioplasty (widening of blocked or narrowed coronary arteries), non fatal stroke, lower limb amputation and renal complications.
Type 2 diabetes mellitus (T2DM) is a chronic disease characterized by the body's inability to produce sufficient insulin and/or properly use insulin. Overweight and obesity are closely linked to T2DM and increased body weight could potentially increase the risk of some diabetes related complications as well as the length of a hospital admission. For hospital admissions among people with T2DM , we will investigate the association between body weight (pre-hospitalisation body mass index, BMI) and hospitalisations in terms of the outcomes length of stay (LoS) and cost of stay (CoS). Hospital admissions will be classified according to pre-specified complication-related diagnoses/procedures. The effect of BMI categories will be modelled for each outcome separately using regression analysis for a) each pre-specified complication-related diagnosis/procedure, and b) overall, including the hospital admission classification as covariates. For the regression analysis, we will use Generalised Linear Models (GLMs), with normal distribution for LoS and for CoS a gamma model with logarithmic link function. We will also investigate the effect of BMI as a continuous variable and using alternative BMI categorisations. Finally, we will evaluate the effect of BMI, controlling for other covariates.
For each hospitalisation (each spell) we will derive the outcomes LoS and CoS. CoS will be derived using the NHS HRG Grouper Software and the NHS reference cost list. We will identify diabetes complications and categories based on the diagnosis and/or procedure (ICD-10 code for the primary and secondary diagnosis and/or the OPDC 4.7 code). The diabetes complications categories are Severe hypoglycaemia, Myocardial infarction (MI), Unstable angina pectoris, Percutaneous coronary intervention (PCI), Heart failure, Non-fatal stroke, Transient Ischaemic Attack (TIA), Lower limb amputation, Revascularization, Hypoglycaemia, cardiovascular diseases (CV), Peripheral ischaemia, Angina, Neuropathy, Renal complications, Related retinopathy, Multiple complications/unspecified complications, Without complications. The identification of non-fatal stroke will be based on the ICD-10 diagnosis and exclude people where date of death is within 28 days after the diagnosis.
Marc Evans - Chief Investigator - Llandough Hospital
Marc Andersen - Corresponding Applicant - Statgroup Ap S - Denmark
Anne Helene Olsen - Collaborator - Novo Nordisk A/S
Arne Haahr Andreasen - Collaborator - Statgroup Ap S - Denmark
Emil Bo Nortoft - Collaborator - Statgroup Ap S - Denmark
Johanne Spanggaard Piltoft - Collaborator - Novo Nordisk A/S
Lars Wilkinson - Collaborator - Novo Nordisk A/S
Uffe Jon Plough - Collaborator - Novo Nordisk A/S
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Townsend Score