Routine use of HbA1c amongst inpatients hospitalised with decompensated heart failure and the association of dysglycaemia with outcomes.
K KhooJ LewP NeefL KearneyL ChurilovR RobbinsA TanM HachemL Owen-JonesQ LamG K HartA WilsonP SumithranD JohnsonP M SrivastavaO FarouqueLouise M BurrellJ D ZajacE I EkinciPublished in: Scientific reports (2018)
Diabetes is an independent risk factor for development of heart failure and has been associated with poor outcomes in these patients. The prevalence of diabetes continues to rise. Using routine HbA1c measurements on inpatients at a tertiary hospital, we aimed to investigate the prevalence of diabetes amongst patients hospitalised with decompensated heart failure and the association of dysglycaemia with hospital outcomes and mortality. 1191 heart failure admissions were identified and of these, 49% had diabetes (HbA1c ≥ 6.5%) and 34% had pre-diabetes (HbA1c 5.7-6.4%). Using a multivariable analysis adjusting for age, Charlson comorbidity score (excluding diabetes and age) and estimated glomerular filtration rate, diabetes was not associated with length of stay (LOS), Intensive Care Unit (ICU) admission or 28-day readmission. However, diabetes was associated with a lower risk of 6-month mortality. This finding was also supported using HbA1c as a continuous variable. The diabetes group were more likely to have diastolic dysfunction and to be on evidence-based cardiac medications. These observational data are hypothesis generating and possible explanations include that more diabetic patients were on medications that have proven mortality benefit or prevent cardiac remodelling, such as renin-angiotensin system antagonists, which may modulate the severity of heart failure and its consequences.
Keyphrases
- heart failure
- type diabetes
- glycemic control
- cardiovascular disease
- intensive care unit
- left ventricular
- ejection fraction
- end stage renal disease
- risk factors
- newly diagnosed
- cardiovascular events
- atrial fibrillation
- blood pressure
- chronic kidney disease
- machine learning
- prognostic factors
- adipose tissue
- peritoneal dialysis
- insulin resistance
- cross sectional
- drug induced
- liver failure
- artificial intelligence