ArticleHealthcare (Basel, Switzerland)2024
German Porphyria Registry (PoReGer)-Background and Setup.
Article in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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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.
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Authors and funding
13 authors.
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Abstract
Porphyrias, as most rare diseases, are characterized by complexity and scarcity of knowledge. A national registry in one of the largest European populations that prospectively collects longitudinal clinical and laboratory data are an important and effective tool to close this gap. The German Porphyria Registry (PoReGer) was founded by four centers with longstanding expertise in the field of porphyrias and rare diseases (Charité-Universitätsmedizin Berlin, Porphyria Center Saxony Chemnitz, University Medical Center Hamburg-Eppendorf, University Medical Center Göttingen) and the German reference laboratory for porphyria, and is supported by the largest German porphyria patient organization. A specified data matrix for three subgroups (acute, chronic blistering cutaneous, acute non-blistering cutaneous) includes data on demographics, specific porphyria-related symptoms, clinical course, general medical history, necessary follow-up assessments (including laboratory and imaging results), symptomatic and disease-modifying therapies, and side-effects. Additionally, the registry includes patient-reported outcome measures on quality of life, depression, and fatigue. PoReGer aims to broaden and deepen the understanding on all porphyria-related subjects. We expect these data to significantly improve the management and care of porphyria patients. Additionally, the data can be used for educational purposes to increase awareness, for the planning of healthcare services, and for machine learning algorithms for early detection of porphyrias.
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