Shailen Jasani and Viktor Szatmári: recipients of the 2017 FECAVA Best Paper Awards

(03.08.2017) Shailen Jasani (UK) and Viktor Szatmári (Netherlands) are the 2017 recipients of the FECAVA awards for best original and best reprint paper, respectively, published in the European Journal of Companion Animal Practice (EJCAP).

The awards will be presented during the opening ceremony of the 23rd congress of the Federation of European Companion Animal Veterinary Associations (FECAVA), to be held in Copenhagen next month.

Viktor Szatmári and Shailen Jasani

Shailen Jasani will receive his award for the paper “Analgesia for the emergency/critical care patient: pain assessment and analgesic agents”, published in the 2016 EJCAP special issue on emergency and critical care (Vol 26(3): 2016, 4-18).

Shailen has published widely on emergency and critical care. He is a diplomate of the American College of Veterinary Emergency and Critical Care and has a particular interest in helping to progress the development of veterinary ECC in the non-referral setting.

Projects he has undertaken to that end include an online community called Veterinary ECC Small Talk, a book on small animal emergency medicine aimed at primary care practice, and a small animal emergency medicine app.

Viktor Szatmári will receive his award for the paper “Innocent cardiac murmur in puppies - prevalence, correlation with haematocrit and auscultation characteristics”, also on behalf of co-authors Martin van Leeuwen and Erik Teske.

The paper was published in the summer 2016 issue of EJCAP (Vol 26(2): 4-10), and originally appeared in the Journal of Veterinary Internal Medicine. Viktor, originally from Hungary, is a diplomate of the European College of Veterinary Internal Medicine – Companion Animals (Cardiology) and is currently head of the Thorax Unit (cardiovascular and pulmonary medicine) at the Faculty of Veterinary Medicine of Utrecht University.

Both papers can be accessed via the FECAVA website, for an interactive presentation as well as a pdf download.

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