Linking international registries to FHIR and Phenopackets with RareLink: a scalable REDCap-based framework for rare disease data interoperability.

While Research Electronic Data Capture (REDCap) has been widely adopted in rare disease research, its unconstrained data format often leads to implementations that lack native interoperability with global health data standards, limiting secondary data use. To address this, we developed and validated , an open-source framework implementing our previously-published ontology-based rare disease common data model, enabling standardised data exchange between REDCap, international registries, and downstream analysis tools. Its preconfigured pipelines interact with the local REDCap application programming interface and enable semi-automatic import or export of data to the Global Alliance for Genomics and Health (GA4GH) Phenopackets and Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) instances, conforming to the HL7 International Patient Summary and Genomics Reporting profiles.

[Retreatment after keratorefractive lenticule extraction (KLEx) : Results of various methods and influence of the recommendations of the Committee for Refractive Surgery (KRC) on the incidence of retreatment].

Background: Keratorefractive lenticule extraction (KLEx) has been shown to be safe and effective for the correction of myopia and myopic astigmatism. Residual refractive errors reduce the uncorrected postoperative visual acuity leading to patient dissatisfaction and increased retreatment rates.

Aim Of The Study: The aim was to assess the potential influence of the recommendations of the Committee for Refractive Surgery (KRC) on the likelihood of retreatment and to compare the results of various methods for retreatment after KLEx for myopia.

An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets.

Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. This work aims to harmonise the Common Data Set by European Rare Disease Registry Infrastructure, Health Level 7 Fast Healthcare Interoperability Base Resources, and the Global Alliance for Genomics and Health Phenopacket Schema into a novel rare disease common data model (RD-CDM), laying the foundation for developing international RD-CDMs aligned with these data standards. We developed a modular-based GitHub repository and documentation to account for flexibility, extensions and further development.

Seeing the primary tumor because of all the trees: Cancer type prediction on low-dimensional data.

The Cancer of Unknown Primary (CUP) syndrome is characterized by identifiable metastases while the primary tumor remains hidden. In recent years, various data-driven approaches have been suggested to predict the location of the primary tumor (LOP) in CUP patients promising improved diagnosis and outcome. These LOP prediction approaches use high-dimensional input data like images or genetic data.

Risk Factors for Re-treatment After Keratorefractive Lenticule Extraction (KLEx) for Myopia and Myopic Astigmatism.

Purpose: To identify potential risk factors that increase the likelihood of re-treatment following keratorefractive lenticule extraction (KLEx) for myopia and myopic astigmatism.

Methods: This was a retrospective study of patients with myopia and myopic astigmatism who underwent KLEx using the VisuMax 500 laser (Carl Zeiss Meditec) between April 2015 and December 2020. Patients were assigned to one of two groups: the control group and the re-treatment group (if they had additional refractive surgery within 2 years of the primary treatment).

Breaking Barriers for Interoperability: A Reference Implementation of CSV-FHIR Transformation Using Open-Source Tools.

FHIR is a widely accepted interoperability standard for exchanging medical data, but data transformation from the primary health information systems into FHIR is usually challenging and requires advanced technical skills and infrastructure. There is a critical need for low-cost solutions, and using Mirth Connect as an open-source tool provides this opportunity. We developed a reference implementation to transform data from CSV (the most common data format) into FHIR resources using Mirth Connect without any advanced technical resources or programming skills.

An OpenEHR Template with the Integrated German LOINC Terms.

An OpenEHR template based on LOINC terms in German language (LOINC-DE) has been created for the structured clinical data capture. The resulting template includes all terms available in LOINC-DE, which can be selected from the drop-down menu for clinical data capture. The template can be used as an independent laboratory form or it can be customized for local needs.