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Other literature type . 2025
License: CC BY
Data sources: ZENODO
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Research . 2025
License: CC BY
Data sources: Datacite
ZENODO
Research . 2025
License: CC BY
Data sources: Datacite
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Protocol: Federated analysis of Randomized Controlled Trial and Real-World data across two Trusted Research Environments to compare comorbidities in older adults vaccinated against COVID-19

Authors: Ohmann, Christian; Panagiotopoulou, Maria; Contrino, Sergio; Cudilla, Léopold; Hall, Chris; Guignard-Duff, Magalie; Cole, Christian; +1 Authors

Protocol: Federated analysis of Randomized Controlled Trial and Real-World data across two Trusted Research Environments to compare comorbidities in older adults vaccinated against COVID-19

Abstract

The EOSC-ENTRUST project aims to create a European network of Trusted Research Environments (TREs) for sensitive data and drive European interoperability through the development of a common blueprint for federated data access and analysis. EOSC-ENTRUST has four drivers, or use cases, which are prototypic for federated, multinational use of TREs in research practice across scientific domains and user communities. Driver 3 demonstrates the potential ability of the blueprint to bridge the traditionally very separated data domains of clinical trials and real-world health data in one solution architecture. The present document is the protocol of the prototype for EOSC-ENTRUST Driver 3, utilising individual participant data (IPD) from a randomized controlled trial (RCT) hosted in crDSR (TSD TRE), along with real-world data (RWD) hosted in the Health Informatics Centre (HIC), University of Dundee TRE with the aim of comparing comorbidities in older adults vaccinated against COVID-19.

Keywords

Data processing, Clinical Trials as Topic, Data analysis, healthcare data, trusted research environment, federated analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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