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3 Publications visible to you, out of a total of 3
The German Corona Consensus Dataset (GECCO): A standardized dataset for COVID-19 research

Abstract (Expand)

Background: The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing segmentation of … information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the "German Corona Consensus Dataset" (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data. Methods: Based on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats. Results: A core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, anamnesis, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined. Conclusion: GECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.

Authors: Julian Sass, Alexander Bartschke, Moritz Lehne, Andrea Essenwanger, Eugenia Rinaldi, Stefanie Rudolph, Kai Uwe Heitmann, Joerg Janne Vehreschild, Christof von Kalle, Sylvia Thun

Date Published: 29th Jul 2020

Publication Type: Journal

Analysis of hospitalized COVID-19 patients in the Mount Sinai Health System using electronic medical records (EMR) reveals important prognostic factors for improved clinical outcomes

Abstract

Not specified

Authors: Zichen Wang, Amanda B Zheutlin, Yu-Han Kao, Kristin L Ayers, Susan J Gross, Patricia Kovatch, Sharon Nirenberg, Alexander W Charney, Girish N Nadkarni, Paul F O'Reilly, Allan C Just, Carol R Horowitz, Glenn Martin, Andrea D Branch, Benjamin S Glicksberg, Dennis S Charney, David L Reich, William K Oh, Eric E Schadt, Rong Chen, Li Li

Date Published: 4th May 2020

Publication Type: Misc

The role of HPV RNA transcription, immune response-related gene expression and disruptive TP53 mutations in diagnostic and prognostic profiling of head and neck cancer.

Abstract (Expand)

Stratification of head and neck squamous cell carcinomas (HNSCC) based on HPV16 DNA and RNA status, gene expression patterns, and mutated candidate genes may facilitate patient treatment decision. We … characterize head and neck squamous cell carcinomas (HNSCC) with different HPV16 DNA and RNA (E6*I) status from 290 consecutively recruited patients by gene expression profiling and targeted sequencing of 50 genes. We show that tumors with transcriptionally inactive HPV16 (DNA+ RNA-) are similar to HPV-negative (DNA-) tumors regarding gene expression and frequency of TP53 mutations (47%, 8/17 and 43%, 72/167, respectively). We also find that an immune response-related gene expression cluster is associated with lymph node metastasis, independent of HPV16 status and that disruptive TP53 mutations are associated with lymph node metastasis in HPV16 DNA- tumors. We validate each of these associations in another large data set. Four gene expression clusters which we identify differ moderately but significantly in overall survival. Our findings underscore the importance of measuring the HPV16 RNA (E6*I) and TP53-mutation status for patient stratification and identify associations of an immune response-related gene expression cluster and TP53 mutations with lymph node metastasis in HNSCC.

Authors: G. Wichmann, M. Rosolowski, K. Krohn, M. Kreuz, A. Boehm, A. Reiche, U. Scharrer, D. Halama, J. Bertolini, U. Bauer, D. Holzinger, M. Pawlita, J. Hess, C. Engel, D. Hasenclever, M. Scholz, P. Ahnert, H. Kirsten, A. Hemprich, C. Wittekind, O. Herbarth, F. Horn, A. Dietz, M. Loeffler

Date Published: 15th Dec 2015

Publication Type: Journal

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