Elena Dudukina

Elena Dudukina

Clinical Specialist and PhD student

Aarhus University

About me

I am a clinical specialist and a PhD candidate (awaiting defense) at the Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital. For the thesis, I conducted research in reproductive health focusing on abortive or near abortive events in pregnancy and their effects on the long-term health of the children and women. I work as part of the team investigating drug safety in longitudinal observational studies.

I am interested in pharmacoepidemiology, especially drug utilization and safety in pregnancy, women’s health. I am also passionate about causal inference methods and R stats.

Interests

  • Causal Inference
  • Pharmacoepidemiology (drug utilization, drug safety and efficacy)
  • Women’s health and reproductive epidemiology
  • R stats

Education

  • Logic, Causation and Probability, 2019

    University of California, Los Angeles

  • Pharmacoepidemiology Summer School, 2019 & 2018

    Aarhus University

  • Causal Inference in Health Sciences, 2019

    Aarhus University

  • Causal Inference Part II Drawing Causal Conclusions from Epidemiological Studies, 2018

    University of Copenhagen

  • Biostatistics I & II, 2018

    Aarhus University

Experience

 
 
 
 
 

Clinical Specialist

Aarhus University Hospital, Department of Clinical Epidemiology

Sep 2021 – Present Denmark

Responsibilities include:

  • Contributing to the design, execution and reporting of real-world database (RWD) pharmacoepidemiologic studies
  • Contributing to the writing of study protocols, statistical analysis plans and study reports
  • Providing scientific and methodological input on various aspects of study design to answer research questions
  • Developing abstracts, manuscripts and presentations to conferences for research projects
  • Time management due to involvement in multiple projects with overlapping timelines

Skills include:

  • Using time-to-event modelling (Cox proportional hazards regression, Fine-Gray subdistribution hazard model), logistic regression, log-binomial regression, propensity-score based adjustment methods
  • Teaching incl. epidemiological designs and methods to Masters students overall covering approx. 200 hours
  • Data management, including complex cohort and variables ascertainment from various health and administrative databases, and statistical analyses involving construction of multiple propensity score models and computation of inverse probability of treatment (IPW) and average treatment effect in the treated (ATT) weights as well as use of conventional adjustment methods
 
 
 
 
 

PhD student in Epidemiology

Aarhus University, Department of Clinical Epidemiology

Jun 2018 – Jun 2021 Denmark

Responsibilities include:

  • Participating in development of the research protocols and statistical analyses plans for own and collaborative projects
  • Independent data management, incl. cohort and variables ascertainment from various Danish health and administrative databases
  • Statistical analyses

PhD Defense is anticipated in last quarter of 2022.

 
 
 
 
 

MSc in Biomedicine

Radboud University

Jan 2015 – Jan 2017 the Netherlands
MSc level courses in clinical epidemiology, epidemiology of infectious diseases, and statistics. Applied training during 6-months internship at Radboudumc and another 6-months external internship at Rijksinstituut voor Volksgezondheid en Milieu (RIVM).
 
 
 
 
 

MD

First Moscow State Medical University

Jan 2008 – Jun 2015 Russia
Specialization in Medicine and Public Health; graduated with honors (magna cum laude)

Recent Posts

Recent Publications

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Antibody binding and complement-mediated killing of invasive Haemophilus influenzae isolates from Spain, Portugal, and the Netherlands

Evasion of IgM binding by NTHi strains increases strains' survival in blood.

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