Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed

Permanent URI for this communityhttps://hdl.handle.net/11727/4806

Browse

Filters

2019 - 201912020 - 20211

Settings

Subject: search.filters.subject.public health

Search Results

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Unravelling data for rapid evidence-based response to COVID-19: a summary of the unCoVer protocol
    (2021) Penalvo, Jose L.; Mertens, Elly; Ademovic, Enisa; Akgun, Seval; Baltazar, Ana Lucia; Buonfrate, Dora; Coklo, Miran; Devleesschauwer, Brecht; Diaz Valencia, Paula Andrea; Fernandes, Joao C.; Javier Gomez, Enrique; Hynds, Paul; Kabir, Zubair; Klein, Jorn; Kostoulas, Polychronis; Jimenez, Lucia Llanos; Lotrean, Lucia Maria; Majdan, Marek; Menasalvas, Ernestina; Nguewa, Paul; Oh, In-Hwan; O'Sullivan, Georgie; Pereira, David M.; Ortiz, Miguel Reina; Riva, Silvia; Soriano, Gloria; Soriano, Joan B.; Spilki, Fernando; Tamang, Mary Elizabeth; Trofor, Antigona Carmen; Vaillant, Michel; Van Ierssel, Sabrina; Vukovic, Jakov; Castellano, Jose M.; 34794999
    Introduction unCoVer-Unravelling data for rapid evidence-based response to COVID-19-is a Horizon 2020-funded network of 29 partners from 18 countries capable of collecting and using real-world data (RWD) derived from the response and provision of care to patients with COVID-19 by health systems across Europe and elsewhere. unCoVer aims to exploit the full potential of this information to rapidly address clinical and epidemiological research questions arising from the evolving pandemic. Methods and analysis From the onset of the COVID-19 pandemic, partners are gathering RWD from electronic health records currently including information from over 22 000 hospitalised patients with COVID-19, and national surveillance and screening data, and registries with over 1 900 000 COVID-19 cases across Europe, with continuous updates. These heterogeneous datasets will be described, harmonised and integrated into a multi-user data repository operated through Opal-DataSHIELD, an interoperable open-source server application. Federated data analyses, without sharing or disclosing any individual-level data, will be performed with the objective to reveal patients' baseline characteristics, biomarkers, determinants of COVID-19 prognosis, safety and effectiveness of treatments, and potential strategies against COVID-19, as well as epidemiological patterns. These analyses will complement evidence from efficacy/safety clinical trials, where vulnerable, more complex/heterogeneous populations and those most at risk of severe COVID-19 are often excluded. Ethics and dissemination After strict ethical considerations, databases will be available through a federated data analysis platform that allows processing of available COVID-19 RWD without disclosing identification information to analysts and limiting output to data aggregates. Dissemination of unCoVer's activities will be related to the access and use of dissimilar RWD, as well as the results generated by the pooled analyses. Dissemination will include training and educational activities, scientific publications and conference communications.
  • No Thumbnail Available
    Item
    The impact of addressing modifiable risk factors to reduce the burden of cardiovascular disease in Turkey
    (2019) Balbay, Yucel; Gagnon-Arpin, Isabelle; Malhan, Simten; Oksuz, Mehmet Ergun; Sutherland, Greg; Dobrescu, Alexandru; Villa, Guillermo; Ertugul, Gulnihal; Habib, Modhar; 0000-0002-5723-5965; 31483303; K-8238-2012
    Objective: Our study aimed to estimate the impact of addressing modifiable risk factors on the future burden of cardiovascular diseases (CVD) in the general population and in two high-risk populations (heterozygous familial hypercholesterolemia and secondary prevention) for Turkey. Methods: One model investigated the impact of reaching the World Health Organization (WHO) voluntary targets for tobacco use, hypertension, type 2 diabetes, obesity and physical inactivity in the general population. Another model estimated the impact of reducing LDL-cholesterol in two high-risk populations through increased access to effective treatment. Inputs for the models include disease and risk factor prevalence rates, a population forecast, baseline CVD event rates, and treatment effectiveness, primarily derived from the published literature. Direct costs to the public health care system and indirect costs from lost production are included, although the cost of programs and pharmacological interventions to reduce risk factors were not considered. Results: The value of reaching WHO risk factor reduction targets is estimated at US$9.3 billion over the next 20 years, while the value of reducing LDL-cholesterol is estimated at up to US$8.1 billion for high-risk secondary prevention patients and US$691 million for heterozygous familial hypercholesterolemia patients. Conclusion: Efforts to achieve WHO risk factor targets and further lower LDL-cholesterol through increased access to treatment for high-risk patients are projected to greatly reduce the growing clinical and economic burden of CVD in Turkey.