Stephen P McDonald1, Bin Tong. 1. Renal unit, Central Northern Adelaide Renal and Transplantation Service, Adelaide, South Australia. stephenm@anzdata.org.au
Abstract
BACKGROUND: Mortality associated with dialysis and transplantation is well characterized. Less well described are hospital separation rates for "non-renal" diagnoses among people receiving kidney replacement therapy (KRT = haemodialysis, peritoneal dialysis and kidney transplantation). We examined these rates among Australians receiving KRT. METHODS: Observational study based on Australian National Hospital Morbidity Database, incorporating Australian public and private hospitals. Separations from this dataset were examined for 2002-7, excluding day-only haemodialysis. ICD (International Classification of Disease) codes were used to identify separations for people receiving chronic KRT. Separations categorized into "renal" and "non-renal" by principal diagnosis. Separation rate, admission length and in-hospital mortality were compared with the general population. RESULTS: Overall hospital separation rate (adjusted for age and gender) was increased relative to the general population for all groups: for HD patients, relative rate (RR) was 4.49 [95% confidence interval 4.460-4.53]; for PD patients 5.52 [5.460-5.59]; for transplant recipients 4.83 [4.20-4.28] (all p < 0.001). When restricted to separations with a "non-renal" principal diagnosis, the excess remained among KRT groups: HD adjusted RR 2.20 [2.170-2.22], PD 2.00 [1.950-2.04] and transplants 2.63 [2.600-2.66], all p < 0.001). The length and in-hospital mortality for separations in each KRT group was also increased. By ICD-10 chapter, rates of separations with infectious and metabolic causes were increased in all KRT groups; separations with circulatory and respiratory causes were also increased. CONCLUSION: Among people receiving KRT in Australia, there is a substantial burden of morbidity in addition to that directly related to KRT. This is most marked for infective, endocrine and circulatory and respiratory hospitalisations.
BACKGROUND: Mortality associated with dialysis and transplantation is well characterized. Less well described are hospital separation rates for "non-renal" diagnoses among people receiving kidney replacement therapy (KRT = haemodialysis, peritoneal dialysis and kidney transplantation). We examined these rates among Australians receiving KRT. METHODS: Observational study based on Australian National Hospital Morbidity Database, incorporating Australian public and private hospitals. Separations from this dataset were examined for 2002-7, excluding day-only haemodialysis. ICD (International Classification of Disease) codes were used to identify separations for people receiving chronic KRT. Separations categorized into "renal" and "non-renal" by principal diagnosis. Separation rate, admission length and in-hospital mortality were compared with the general population. RESULTS: Overall hospital separation rate (adjusted for age and gender) was increased relative to the general population for all groups: for HDpatients, relative rate (RR) was 4.49 [95% confidence interval 4.460-4.53]; for PDpatients 5.52 [5.460-5.59]; for transplant recipients 4.83 [4.20-4.28] (all p < 0.001). When restricted to separations with a "non-renal" principal diagnosis, the excess remained among KRT groups: HD adjusted RR 2.20 [2.170-2.22], PD 2.00 [1.950-2.04] and transplants 2.63 [2.600-2.66], all p < 0.001). The length and in-hospital mortality for separations in each KRT group was also increased. By ICD-10 chapter, rates of separations with infectious and metabolic causes were increased in all KRT groups; separations with circulatory and respiratory causes were also increased. CONCLUSION: Among people receiving KRT in Australia, there is a substantial burden of morbidity in addition to that directly related to KRT. This is most marked for infective, endocrine and circulatory and respiratory hospitalisations.
Authors: Arianne van Koppen; Jaap A Joles; Bas W M van Balkom; Sai Kiang Lim; Dominique de Kleijn; Rachel H Giles; Marianne C Verhaar Journal: PLoS One Date: 2012-06-19 Impact factor: 3.240
Authors: Dharmenaan Palamuthusingam; Arun Nadarajah; Elaine M Pascoe; Jonathan Craig; David W Johnson; Carmel M Hawley; Magid Fahim Journal: PLoS One Date: 2020-06-26 Impact factor: 3.240