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Diana Pietzner

Researcher at Martin Luther University of Halle-Wittenberg

Publications -  7
Citations -  610

Diana Pietzner is an academic researcher from Martin Luther University of Halle-Wittenberg. The author has contributed to research in topics: Thyroid peroxidase & Thyroid disease. The author has an hindex of 6, co-authored 7 publications receiving 532 citations.

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Intra‐aortic balloon pump counterpulsation (IABP) for myocardial infarction complicated by cardiogenic shock

TL;DR: There is no convincing randomised data to support the use of IABP in infarct-related cardiogenic shock, however, available evidence suggests that IABp may have a beneficial effect on some haemodynamic parameters.
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Identification of Novel Genetic Loci Associated with Thyroid Peroxidase Antibodies and Clinical Thyroid Disease

Marco Medici, +117 more
- 27 Feb 2014 - 
TL;DR: A GWAS meta-analysis for TPOAbs identified five newly associated loci, three of which were also associated with clinical thyroid disease, and the MAGI3 and BACH2 variants were associated with an increased risk of hyperthyroidism, which was replicated in an independent cohort of patients with Graves' disease as discussed by the authors.

Identification of Novel Genetic Loci Associated with Thyroid Peroxidase Antibodies and Clinical Thyroid Disease

Marco Medici, +117 more
TL;DR: The results provide insight into why individuals with thyroid autoimmunity do or do not eventually develop thyroid disease, and these markers may therefore predict which TPOAb-positives are particularly at risk of developing clinical thyroid dysfunction.
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Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

Philipp S. Wild, +147 more
TL;DR: The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac architecture and warrant follow-up in future functional studies.
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The trend-renewal process: a useful model for medical recurrence data

TL;DR: The suggested version of the trend-renewal process is fitted to a data set of hospital readmission times of colon cancer patients to illustrate the method for application to clinical data.