Evidence map›Paper›PMID 41278327›Full record

ArticleKidney international reports2025

Creating a Globally Distributed Multinational Dialysis Database - The Apollo

Melanie Wolf, Yue Jiao, Kaitlyn Croft, Carly Hahn Contino, Justin Zimbelman, Kanti Singh, Mitesh Soni, Andrew Dickinson, Jeroen P Kooman, Dinesh Chatoth and 8 more

Abstract read
In one paragraph

Article in Kidney international reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Melanie WolfRenal Research Institute, New York, New York, USA.
Yue JiaoRenal Research Institute, New York, New York, USA.
Kaitlyn CroftRenal Research Institute, New York, New York, USA.
Carly Hahn ContinoFresenius Medical Care Holdings Inc., Waltham, Massachusetts, USA.
Justin ZimbelmanRenal Research Institute, New York, New York, USA.
Kanti SinghFresenius Medical Care Holdings Inc., Waltham, Massachusetts, USA.
Mitesh SoniFresenius Medical Care Holdings Inc., Waltham, Massachusetts, USA.
Andrew DickinsonPrivacy Analytics, Ottawa, Ontario, Canada.
Jeroen P KoomanFaculty of Health Medicine and Life Science, Maastricht University, Maastricht, Netherlands.
Dinesh ChatothFresenius Medical Care Holdings Inc., Waltham, Massachusetts, USA.
Adrian GuinsburgFresenius Medical Care, Madrid, Spain.
Stefano StuardFresenius Medical Care Deutschland GmbH, Bad Homburg, Hessen, Germany.
Milind NikamFresenius Medical Care, Singapore, Singapore.
Michelle CarverFresenius Medical Care Holdings Inc., Waltham, Massachusetts, USA.
Len UsvyatRenal Research Institute, New York, New York, USA.
Franklin W MadduxFresenius Medical Care Holdings Inc., Waltham, Massachusetts, USA.
Sheetal ChaudhuriRenal Research Institute, New York, New York, USA.
John LarkinRenal Research Institute, New York, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Large amounts of data are captured during dialysis, yet multinational datasets are scarce because of challenges in harmonizing and integrating clinical data, as well as complying with data protection regulations across the world. A global kidney care provider, Fresenius Medical Care, approached this challenge and finalized the creation of an anonymized dialysis database, coined Apollo Methods: To create this globally distributed multinational database, data from different electronic clinical systems were extracted, covering routinely collected medical information from dialysis clinics worldwide. This data were harmonized, and then anonymized following a reidentification risk assessment conducted by the external company Privacy Analytics, Ontario, Canada. The data was consolidated and is stored in a central cloud environment and will be updated periodically. Results: Apollo captures data from January 2018 to March 2021 from 40 countries and 543,169 patients worldwide (4.6% in Asia-Pacific [AP], 13.9% in Europe, Middle East, and Africa [EMEA], 7.0% in Latin America [LA], and 74.5% in North America [NA]). It contains demographic data, 35,874,039 laboratory, and 140,016,249 treatment observations as well as frequently recorded medication information, and clinical outcomes (e.g., hospitalization and mortality). Several regional differences can be observed using these data, such as age, treatment modality, and treatment time. Conclusion: Creating a robust multinational dialysis database offers vast opportunities to conduct real-world research and data analytics, including the development of artificial intelligence models. These activities hold promise of advancing the understanding of kidney disease and dialysis therapies. It can serve as comparative resource for the nephrology community.

Indexed as

end-stage kidney diseasemultinational databaseoutcomes

Identifiers

PMID41278327
PMCPMC12640056

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.