ArticlePatterns (New York, N.Y.)2026
Mainzelliste: Ten years of pseudonymization, record linkage, and informed consent management.
Article in Patterns (New York, N.Y.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Record linkage and pseudonymization are crucial tasks in collaborative biomedical research. Data for a patient are rarely stored in one place and therefore often need to be linked and integrated across multiple institutions. Mainzelliste is an open-source software solution designed to solve these challenges by providing a comprehensive and flexible toolkit for pseudonymization, record linkage, and consent management. It supports a variety of pseudonyms, record linkage methods, and modular, informed patient consents. A highly flexible REST application programming interface (API) allows tight integration into existing applications and workflows. Since its initial release in 2015, Mainzelliste has evolved into a vibrant open-source software solution "by researchers, for researchers" including a user-friendly graphical interface, support for HL7 FHIR for consent and patient data, and record linkage based on secure multi-party computation, thereby supporting secure and efficient biomedical research.
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What Socratic holds
Registered trials
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 Socratic graph.