@article{MarenholzEsparzaGordilloRueschendorfetal.2015,
  author    = {Marenholz, Ingo and Esparza-Gordillo, Jorge and R{\"u}schendorf, Franz and Bauerfeind, Anja and Strachan, David P. and Spycher, Ben D. and Baurecht, Hansj{\"o}rg and Magaritte-Jeannin, Patricia and S{\"a}{\"a}f, Annika and Kerkhof, Marjan and Ege, Markus and Baltic, Svetlana and Matheson, Melanie C. and Li, Jin and Michel, Sven and Ang, Wei Q. and McArdle, Wendy and Arnold, Andreas and Homuth, Georg and Demenais, Florence and Bouzigon, Emmanuelle and S{\"o}derh{\"a}ll, Cilla and Pershagen, G{\"o}ran and de Jongste, Johan C. and Postma, Dirkje S. and Braun-Fahrl{\"a}nder, Charlotte and Horak, Elisabeth and Ogorodova, Ludmila M. and Puzyrev, Valery P. and Bragina, Elena Yu and Hudson, Thomas J. and Morin, Charles and Duffy, David L. and Marks, Guy B. and Robertson, Colin F. and Montgomery, Grant W. and Musk, Bill and Thompson, Philip J. and Martin, Nicholas G. and James, Alan and Sleiman, Patrick and Toskala, Elina and Rodriguez, Elke and F{\"o}lster-Holst, Regina and Franke, Andre and Lieb, Wolfgang and Gieger, Christian and Heinzmann, Andrea and Rietschel, Ernst and Keil, Thomas and Cichon, Sven and N{\"o}then, Markus M. and Pennel, Craig E. and Sly, Peter D. and Schmidt, Carsten O. and Matanovic, Anja and Schneider, Valentin and Heinig, Matthias and H{\"u}bner, Norbert and Holt, Patrick G. and Lau, Susanne and Kabesch, Michael and Weidinger, Stefan and Hakonarson, Hakon and Ferreira, Manuel A. R. and Laprise, Catherine and Freidin, Maxim B. and Genuneit, Jon and Koppelman, Gerard H. and Mel{\´e}n, Erik and Dizier, Marie-H{\´e}l{\`e}ne and Henderson, A. John and Lee, Young Ae},
  title     = {Meta-analysis identifies seven susceptibility loci involved in the atopic march},
  series = {Nature Communications},
  volume    = {6},
  journal   = {Nature Communications},
  number    = {8804},
  doi       = {10.1038/ncomms9804},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-139835},
  year      = {2015},
  abstract  = {Eczema often precedes the development of asthma in a disease course called the 'atopic march'. To unravel the genes underlying this characteristic pattern of allergic disease, we conduct a multi-stage genome-wide association study on infantile eczema followed by childhood asthma in 12 populations including 2,428 cases and 17,034 controls. Here we report two novel loci specific for the combined eczema plus asthma phenotype, which are associated with allergic disease for the first time; rs9357733 located in EFHC1 on chromosome 6p12.3 (OR 1.27; P = 2.1 x 10(-8)) and rs993226 between TMTC2 and SLC6A15 on chromosome 12q21.3 (OR 1.58; P = 5.3 x 10(-9)). Additional susceptibility loci identified at genome-wide significance are FLG (1q21.3), IL4/KIF3A (5q31.1), AP5B1/OVOL1 (11q13.1), C11orf30/LRRC32 (11q13.5) and IKZF3 (17q21). We show that predominantly eczema loci increase the risk for the atopic march. Our findings suggest that eczema may play an important role in the development of asthma after eczema.},
  language  = {en}
}
@article{GabrielJirůHillmannKraftetal.2020,
  author    = {Gabriel, Katharina M. A. and J{\´i}rů-Hillmann, Steffi and Kraft, Peter and Selig, Udo and R{\"u}cker, Victoria and M{\"u}hler, Johannes and D{\"o}tter, Klaus and Keidel, Matthias and Soda, Hassan and Rascher, Alexandra and Schneider, Rolf and Pfau, Mathias and Hoffmann, Roy and Stenzel, Joachim and Benghebrid, Mohamed and Goebel, Tobias and Doerck, Sebastian and Kramer, Daniela and Haeusler, Karl Georg and Volkmann, Jens and Heuschmann, Peter U. and Fluri, Felix},
  title     = {Two years' experience of implementing a comprehensive telemedical stroke network comprising in mainly rural region: the Transregional Network for Stroke Intervention with Telemedicine (TRANSIT-Stroke)},
  series = {BMC Neurology},
  volume    = {20},
  journal   = {BMC Neurology},
  doi       = {10.1186/s12883-020-01676-6},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229214},
  year      = {2020},
  abstract  = {Background Telemedicine improves the quality of acute stroke care in rural regions with limited access to specialized stroke care. We report the first 2 years' experience of implementing a comprehensive telemedical stroke network comprising all levels of stroke care in a defined region. Methods The TRANSIT-Stroke network covers a mainly rural region in north-western Bavaria (Germany). All hospitals providing acute stroke care in this region participate in TRANSIT-Stroke, including four hospitals with a supra-regional certified stroke unit (SU) care (level III), three of those providing teleconsultation to two hospitals with a regional certified SU (level II) and five hospitals without specialized SU care (level I). For a two-year-period (01/2015 to 12/2016), data of eight of these hospitals were available; 13 evidence-based quality indicators (QIs) related to processes during hospitalisation were evaluated quarterly and compared according to predefined target values between level-I- and level-II/III-hospitals. Results Overall, 7881 patients were included (mean age 74.6 years +/- 12.8; 48.4\% female). In level-II/III-hospitals adherence of all QIs to predefined targets was high ab initio. In level-I-hospitals, three patterns of QI-development were observed: a) high adherence ab initio (31\%), mainly in secondary stroke prevention; b) improvement over time (44\%), predominantly related to stroke specific diagnosis and in-hospital organization; c) no clear time trends (25\%). Overall, 10 out of 13 QIs reached predefined target values of quality of care at the end of the observation period. Conclusion The implementation of the comprehensive TRANSIT-Stroke network resulted in an improvement of quality of care in level-I-hospitals.},
  language  = {en}
}
@article{SommerAmrBavendieketal.2022,
  author    = {Sommer, Kim K. and Amr, Ali and Bavendiek, Udo and Beierle, Felix and Brunecker, Peter and Dathe, Henning and Eils, J{\"u}rgen and Ertl, Maximilian and Fette, Georg and Gietzelt, Matthias and Heidecker, Bettina and Hellenkamp, Kristian and Heuschmann, Peter and Hoos, Jennifer D. E. and Keszty{\"u}s, Tibor and Kerwagen, Fabian and Kindermann, Aljoscha and Krefting, Dagmar and Landmesser, Ulf and Marschollek, Michael and Meder, Benjamin and Merzweiler, Angela and Prasser, Fabian and Pryss, R{\"u}diger and Richter, Jendrik and Schneider, Philipp and St{\"o}rk, Stefan and Dieterich, Christoph},
  title     = {Structured, harmonized, and interoperable integration of clinical routine data to compute heart failure risk scores},
  series = {Life},
  volume    = {12},
  journal   = {Life},
  number    = {5},
  issn      = {2075-1729},
  doi       = {10.3390/life12050749},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-275239},
  year      = {2022},
  abstract  = {Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format. In this work, we demonstrate the feasibility of a multi-site solution to derive and calculate two exemplary HF scores from clinical routine data (MAGGIC score with six continuous and eight categorical variables; Barcelona Bio-HF score with five continuous and six categorical variables). Within HiGHmed, a German Medical Informatics Initiative consortium, we implemented an interoperable solution, collecting a harmonized HF-phenotypic core data set (CDS) within the openEHR framework. Our approach minimizes the need for manual data entry by automatically retrieving data from primary systems. We show, across five participating medical centers, that the implemented structures to execute dedicated data queries, followed by harmonized data processing and score calculation, work well in practice. In summary, we demonstrated the feasibility of clinical routine data usage across multiple partner sites to compute HF risk scores. This solution can be extended to a large spectrum of applications in clinical care.},
  language  = {en}
}