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Antonella Bodini

Researcher at National Research Council

Publications -  38
Citations -  489

Antonella Bodini is an academic researcher from National Research Council. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 10, co-authored 33 publications receiving 322 citations. Previous affiliations of Antonella Bodini include University of Pavia.

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Burnout Among Healthcare Workers in the COVID 19 Era: A Review of the Existing Literature

TL;DR: In this article, the authors proposed measures to prevent or reduce burnout at individual level (physical activity, balanced diet, good sleep hygiene, family support, meaningful relationships, reflective practices and small group discussions), organizational level (blame-free environments for sharing experiences and advices, broad involvement in management decisions, multi-disciplinary psychosocial support teams, safe areas to withdraw quickly from stressful situations, adequate time planning, social support), and cultural level (involvement of healthcare workers in the development, implementation, testing, and evaluation of measures against burnout).
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On minimum Kantorovich distance estimators

TL;DR: In this article, the authors introduce estimators defined as minimizers of Kantorovich distances between statistical models and empirical distributions, and study the existence, measurability and consistency of these estimators.
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Vulnerability assessment of Central-East Sardinia (Italy) to extreme rainfall events

TL;DR: In this article, a statistical analysis of the heavy rainfall phenomenon in Sardinia is presented, focusing on the existence of trends in heavy rainfall and the characterization of the distribution of extreme events.
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An effect of the PAI-1 4G/5G polymorphism on cholesterol levels may explain conflicting associations with myocardial infarction and stroke.

TL;DR: This finding may explain the involvement of the PAI-1 polymorphism in the clustering of atherothrombotic risk factors, and why people with the 4G/4G genotype are at increased risk for myocardial infarction.
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Using a hidden Markov model to analyse extreme rainfall events in Central‐East Sardinia

TL;DR: In this paper, the authors investigated the capability of a hidden Markov model (HMM) in identifying possible recurrent patterns in the occurrence of extreme events over a small area of Central-East Sardinia (Italy), for the purposes of hydrogeological risk prevention.