APOLLO DB: CHARACTERISTICS OF DIALYSIS PATIENTS ACROSS MAJOR WORLD REGIONS

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APOLLO DB: CHARACTERISTICS OF DIALYSIS PATIENTS ACROSS MAJOR WORLD REGIONS
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
 
 
Large amounts of longitudinal data are captured during dialysis. This data can be used for secondary purposes to understand and advance care models. However, secondary data is often not available on a multinational level due to challenges in harmonizing data from different clinical systems and need to adhere to various data protection regulations in the world. Apollo DB is an anonymized dialysis dataset that combines and harmonizes real-world data from a global provider for research and quality improvement activities worldwide.
Apollo DB captures longitudinal observation level data from 40 countries on demographics, diagnoses, laboratories, medications, treatments, patient reported quality of life, 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 first version of the dataset contains data on more than 360 variables from Jan 2018 to Mar 2021 and will be updated periodically.
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 treatment observations. Selected characteristics are shown by world region in Figure 1. Most patients were 45-64 years old (yo) at dialysis start in all regions except Western Europe where most patients started dialysis at ≥75 yo. A higher proportion of younger patients (18-44 yo) started dialysis in Latin America, South Africa, Southeast Asia and Western Asia. Whereas a higher proportion of older patients (≥75 yo) started dialysis in Southern and Western Europe, as well as in Oceania. The proportion of females across regions differs about 10%. Northern Europe has the lowest proportion of females (35%), whereas Eastern Asia has the highest proportion of females (46%). Most of the patients are between 160-169 cm tall overall regions. In the EMEA regions as well as in Western Asia, Oceania and Northern America a high proportion is between 170-179 cm tall. Whereas a higher proportion of patients in Eastern Asia, Southeast Asia and Latin America are between 150-159 cm tall. The most common modality in EMEA is hemodiafiltration, and hemodialysis is most common in the other regions. Nonetheless, PD was used by 17% of patients in Latin America and 13% of patients in Northern America.
In a descriptive analysis of Apollo DB, 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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