Deutsch Intern
Institute for Clinical Epidemiology and Biometry

Olga Miljukov

2024[ to top ]
  • 1.
    Morbach C, Gelbrich G, Schreckenberg M, Hedemann M, Pelin D, Scholz N, et al. Population data-based federated machine learning improves automated echocardiographic quantification of cardiac structure and function: the Automatisierte Vermessung der Echokardiographie project. Eur Heart J Digit Health. 2024;5(1):77-88.
  • 1.
    Appel KS, Nurnberger C, Bahmer T, Forster C, Polidori MC, Kohls M, et al. Definition of the Post-COVID syndrome using a symptom-based Post-COVID score in a prospective, multi-center, cross-sectoral cohort of the German National Pandemic Cohort Network (NAPKON). Infection [Internet]. 2024;. Available from: https://www.ncbi.nlm.nih.gov/pubmed/38587752
2023[ to top ]
  • 1.
    Schmiemann G, Greser A, Maun A, Bleidorn J, Schuster A, Miljukov O, et al. Effects of a multimodal intervention in primary care to reduce second line antibiotic prescriptions for urinary tract infections in women: parallel, cluster randomised, controlled trial. Bmj. 2023;383:e076305.
  • 1.
    Yusuf KO, Chaplinskaya-Sobol I, Schoneberg A, Hanss S, Valentin H, Lorenz-Depiereux B, et al. Impact of Clinical Study Implementation on Data Quality Assessments - Using Contradictions within Interdependent Health Data Items as a Pilot Indicator. Stud Health Technol Inform. 2023;307:152-8.
  • 1.
    Yusuf KO, Miljukov O, Schoneberg A, Hanß S, Wiesenfeldt M, Stecher M, et al. Consistency as a Data Quality Measure for German Corona Consensus Items Mapped from National Pandemic Cohort Network Data Collections. Methods Inf Med. 2023;62(S 01):e47-e56.
  • 1.
    Steinbeis F, Thibeault C, Steinbrecher S, Ahlgrimm Y, Haack IA, August D, et al. Analysis of acute COVID-19 including chronic morbidity: protocol for the deep phenotyping National Pandemic Cohort Network in Germany (NAPKON-HAP). Infection. 2023;.
2022[ to top ]
  • 1.
    Schons M, Pilgram L, Reese JP, Stecher M, Anton G, Appel KS, et al. The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics. Eur J Epidemiol. 2022;37(8):849-70.
  • 1.
    Parisi S, Lehner N, Schrader H, Kierer L, Fleischer A, Miljukov O, et al. Experiencing COVID-19, home isolation and primary health care: A mixed-methods study. Front Public Health. 2022;10:1023431.
  • 1.
    Appel KS, Maier D, Hopff SM, Mitrov L, Stecher M, Scherer M, et al. 1886. External Validation of the 4C Mortality Score and the qSOFA for Different Variants of Concerns of SARS-CoV-2 Using Data of the NAPKON Cross-Sectoral Cohort Platform (SUEP). Open Forum Infectious Diseases [Internet]. 2022;9(Supplement_2). Available from: https://doi.org/10.1093/ofid/ofac492.1513
  • 1.
    Koll CEM, Hopff SM, Meurers T, Lee CH, Kohls M, Stellbrink C, et al. Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients. Sci Data. 2022;9(1):776.
  • 1.
    Bahmer T, Borzikowsky C, Lieb W, Horn A, Krist L, Fricke J, et al. Severity, predictors and clinical correlates of Post-COVID syndrome (PCS) in Germany: A prospective, multi-centre, population-based cohort study. EClinicalMedicine. 2022;51:101549.
2021[ to top ]
  • 1.
    Vollmuth C, Miljukov O, Abu-Mugheisib M, Angermaier A, Barlinn J, Busetto L, et al. Impact of the coronavirus disease 2019 pandemic on stroke teleconsultations in Germany in the first half of 2020. European Journal of Neurology [Internet]. 2021;28(10):3267-78. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1111/ene.14787