@article{BeierleSchobelVogeletal.2021,
  author    = {Beierle, Felix and Schobel, Johannes and Vogel, Carsten and Allgaier, Johannes and Mulansky, Lena and Haug, Fabian and Haug, Julian and Schlee, Winfried and Holfelder, Marc and Stach, Michael and Schickler, Marc and Baumeister, Harald and Cohrdes, Caroline and Deckert, J{\"u}rgen and Deserno, Lorenz and Edler, Johanna-Sophie and Eichner, Felizitas A. and Greger, Helmut and Hein, Grit and Heuschmann, Peter and John, Dennis and Kestler, Hans A. and Krefting, Dagmar and Langguth, Berthold and Meybohm, Patrick and Probst, Thomas and Reichert, Manfred and Romanos, Marcel and St{\"o}rk, Stefan and Terhorst, Yannik and Weiß, Martin and Pryss, R{\"u}diger},
  title     = {Corona Health — A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic},
  series = {International Journal of Environmental Research and Public Health},
  volume    = {18},
  journal   = {International Journal of Environmental Research and Public Health},
  number    = {14},
  issn      = {1660-4601},
  doi       = {10.3390/ijerph18147395},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-242658},
  year      = {2021},
  abstract  = {Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.},
  language  = {en}
}
@article{OezkurMagyarThomasetal.2018,
  author    = {Oezkur, Mehmet and Magyar, Atilla and Thomas, Phillip and Reif, Andreas and St{\"o}rk, Stefan and Heuschmann, Peter U. and Leyh, Rainer G. and Wagner, Martin},
  title     = {The COMT-polymorphism is not associated with the incidence of acute kidney injury after cardiac surgery - a prospective cohort study},
  series = {BMC Nephrology},
  volume    = {19},
  journal   = {BMC Nephrology},
  number    = {34},
  doi       = {10.1186/s12882-018-0820-x},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-175529},
  year      = {2018},
  abstract  = {Background: The Catechol-O-methyltransferase (COMT) represents the key enzyme in catecholamine degradation. Recent studies suggest that the COMT rs4680 polymorphism is associated with the response to endogenous and exogenous catecholamines. There are, however, conflicting data regarding the COMT Met/Met phenotype being associated with an increased risk of acute kidney injury (AKI) after cardiac surgery. The aim of the current study is to prospectively investigate the impact of the COMT rs4680 polymorphism on the incidence of AKI in patients undergoing cardiac surgery. Methods: In this prospective single center cohort study consecutive patients hospitalized for elective cardiac surgery including cardiopulmonary-bypass (CPB) were screened for participation. Demographic clinical data, blood, urine and tissue samples were collected at predefined time points throughout the clinical stay. AKI was defined according to recent recommendations of the Kidney Disease Improving Global Outcome (KDIGO) group. Genetic analysis was performed after patient enrolment was completed. Results: Between April and December 2014, 150 patients were recruited. The COMT genotypes were distributed as follows: Val/Met 48.7\%, Met/Met 29.3\%, Val/Val 21.3\%. No significant differences were found for demography, comorbidities, or operative strategy according to the underlying COMT genotype. AKI occurred in 35 patients (23.5\%) of the total cohort, and no differences were evident between the COMT genotypes (20.5\% Met/Met, 24.7\% Val/Met, 25.0\% Val/Val, p = 0.66). There were also no differences in the post-operative period, including ICU or in-hospital stay. Conclusions: We did not find statistically significant variations in the risk for postoperative AKI, length of ICU or in-hospital stay according to the underlying COMT genotype.},
  language  = {en}
}