UK Renal Registry 13th Annual Report (December 2010): Chapter 4: comorbidities and current smoking status amongst patients starting renal replacement therapy in England, Wales and Northern Ireland from 2008 to 2009.

INTRODUCTION

Comorbidity is an important determinant of survival for renal replacement therapy patients and impacts other care processes such as dialysis access creation and transplant wait-listing. The prevalence of comorbidities in incident patients on renal replacement therapy (RRT) changes with age and varies between ethnic groups. This study describes these associations and the independent effect of comorbidities on outcomes.

METHODS

Incident patients reported to the UK Renal Registry (UKRR) with comorbidity data in 2008 and 2009 (n = 5,617) were included in analyses exploring the association of comorbidity with patient demographics, treatment modality, haemoglobin and renal function at start of RRT. For analyses examining comorbidity and survival, adult patients starting RRT between 2004 and 2009 in centres reporting to the UKRR with comorbidity data (n = 16,527) were included. The relationship between comorbidities and mortality at 90 days and one year after 90 days from start of RRT was explored using Cox regression.

RESULTS

Completeness of comorbidity data was 44.4% in 2009 compared with 52.1% in 2004. Of patients with data, 56.5% had one or more comorbidities. Diabetes mellitus and ischaemic heart disease were the most common conditions seen in 32.9% and 22.5% of patients respectively. Current smoking was recorded for 12.4% of incident RRT patients in the 2-year period. The presence of comorbidities in patients <75 years became more common with increasing age in all ethnic groups. In multivariable survival analysis, malignancy and the presence of ischaemic/neuropathic ulcers were the strongest independent predictors of poor survival at 1 year after 90 days from the start of RRT in patients <65 years.

CONCLUSION

Differences in prevalence rates of comorbid illnesses in incident RRT patients may reflect variation in access to health care or competing risk prior to commencing treatment. The interpretation of analyses continues to be limited by poor data completeness.