COMPARATIVE STUDY
JOURNAL ARTICLE
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A comparative study of the risk profile of hemodialysis patients in a for profit network and in two regional registries of the Italian Society of Nephrology.

Journal of Nephrology 2018 Februrary
In 2013, the Italian Society of Nephrology joined forces with Nephrocare-Italy to create a clinical research cohort of patients on file in the data-rich clinical management system (EUCLID) of this organization for the performance of observational studies in the hemodialysis (HD) population. To see whether patients in EUCLID are representative of the HD population in Italy, we set out to compare the whole EUCLID population with patients included in the regional HD registries in Emilia-Romagna (Northern Italy) and in Calabria (Southern Italy), the sole regions in Italy which have systematically collected an enlarged clinical data set allowing comparison with the data-rich EUCLID system. An analysis of prevalent and incident patients in 2010 and 2011 showed that EUCLID patients had a lower prevalence of coronary heart disease, peripheral vascular disease, heart failure, valvular heart disease, liver disease, peptic ulcer and other comorbidities and risk factors and a higher fractional urea clearance (Kt/V) than those in the Emilia Romagna and Calabria registries. Accordingly, survival analysis showed a lower mortality risk in the EUCLID 2010 and 2011 cohorts than in the combined two regional registries in the corresponding years: for 2010, hazard ratio (HR) EUCLID vs. Regional registries: 0.80 [95% confidence interval: 0.71-0.90]; for 2011, HR: 0.76 [0.65-0.90]. However, this difference was nullified by statistical adjustment for the difference in comorbidities and risk factors, indicating that the longer survival in the EUCLID database was attributable to the lower risk profile of patients included in that database. This preliminary analysis sets the stage for future observational studies and indicates that appropriate adjustment for difference in comorbidities and risk factors is needed to generalize to the Italian HD population analyses based on the data-rich EUCLID database.

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