GLOBAL DIALYSIS CHARACTERISTICS ACROSS SIX CONTINENTS IN THE APOLLO DB DATASET

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GLOBAL DIALYSIS CHARACTERISTICS ACROSS SIX CONTINENTS IN THE APOLLO DB DATASET
Melanie
Wolf
Yue Jiao Yue.Jiao@freseniusmedicalcare.com Fresenius Medical Care Global Medical Office Waltham
Kaitlyn Renee Croft Kaitlyn.Croft@fmc-ag.com Fresenius Medical Care Global Medical Office Bad Homburg
Marco Rancati marco.rancati@fmc-ag.com Fresenius Medical Care Digital Technology & Innovation Cremona
Anke Winter Anke.Winter@fmc-ag.com Fresenius Medical Care Global Medical Office Bad Homburg
Milind Nikam Milind.Nikam@fmc-asia.com Fresenius Medical Care Global Medical Office Singapore
Stefano Stuard stefano.stuard@fmc-ag.com Fresenius Medical Care Global Medical Office Bad Homburg
Adrian Marcos Guinsburg Adrian.Guinsburg@fmc-ag.com Fresenius Medical Care Global Medical Office Buenos Aires
Jeffrey Hymes Jeffrey.HymesMD@freseniusmedicalcare.com Fresenius Medical Care Global Medical Office Waltham
Kirill Koulechov Kirill.Koulechov@fmc-asia.com Fresenius Medical Care Care Enablement Bad Homburg
Stuart McGuigan Stuart.Mcguigan@freseniusmedicalcare.com Fresenius Medical Care Digital Technology & Innovation Waltham
Len Usvyat Len.Usvyat@freseniusmedicalcare.com Fresenius Medical Care Global Medical Office Waltham
John Larkin john.larkin@freseniusmedicalcare.com Fresenius Medical Care Global Medical Office Waltham
Franklin W. Maddux Frank.Maddux@freseniusmedicalcare.com Fresenius Medical Care Global Medical Office Waltham
 
 

A considerable amount of data is captured during the care of dialysis patients. This data can be used for secondary purposes to understand the delivery of care and advance treatment models. Despite this, multinational datasets are scarce due to differences in clinical systems and data protection regulations. Apollo DB is an anonymized dialysis dataset that combines and harmonizes real-world data from a global provider for quality improvement and research efforts. Our aim was to detail the characteristics of dialysis patients treated in 40 countries across six continents in the first version of the dataset.

Apollo DB captures longitudinal observation level data from 40 countries on demographics, diagnoses, laboratories, medications, treatments, quality of life surveys, and outcomes. Data from different electronic systems is harmonized and anonymized based on logic established in a re-identification risk assessment. Data is consolidated and stored in a central cloud environment. The initial version of the dataset contains data on 369 variables from Jan 2018 to Mar 2021 and will be updated periodically.

The first version of the Apollo DB includes data on 543,169 patients, with 4.6% from Asia-Pacific (AP), 13.9% from Europe, Middle East, & Africa (EMEA), 7.0% from Latin America (LA), and 74.5% from North America (NA) countries. Overall, the dataset contains information on 35,874,039 laboratory and 140,016,249 dialysis treatments observations. Selected characteristics are shown by world region in Figure 1. Most patients are 45-64 years old (yo), yet more are 18-44 yo in AP & LA, while more are 65-74 and ≥75 yo in EMEA and NA. There were regional differences in several parameters. Dialysis patients in EMEA had lower blood urea nitrogen levels before and after dialysis, and a higher proportion received hemodiafiltration. Peritoneal dialysis was more frequently used in LA and NA than in other regions. The mean treatment time was lower in NA and patients had a higher body weight versus other regions. Mean hemoglobin levels were consistent in all regions, yet transferrin saturation and ferritin levels were the lowest in EMEA and highest in NA. Mean albumin levels were slightly under 4.0 g/dL in all regions. Mineral bone disorder laboratories showed mean values in target range. Cholesterol, low/high density lipoprotein levels, and white blood cell counts were relatively unremarkable in all regions.


In a first descriptive analysis, several regional differences were observed. These findings act as benchmarks for the nephrology community. Apollo DB offers opportunities for investigators to conduct global analytics and advance the state of the art.

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