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Adi Givon
Researcher at Sheba Medical Center
Publications - 71
Citations - 897
Adi Givon is an academic researcher from Sheba Medical Center. The author has contributed to research in topics: Poison control & Injury Severity Score. The author has an hindex of 14, co-authored 62 publications receiving 707 citations. Previous affiliations of Adi Givon include Tel Aviv University.
Papers
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Journal Article
Burns in Israel: demographic, etiologic and clinical trends, 1997-2003.
TL;DR: The groups at highest risk were children 0-1 years old, males and non-Jews (the incidence rate among non- Jews was 1.5 times higher than their share in the general population), and those with the highest mortality rate were victims of burns > 90% TBSA and patients older than 70.
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Traumatic brain injury: It is all about definition.
TL;DR: This study recommends the adoption of an AIS cut-off ≥ 5 as a valid definition of severe TBI in epidemiological studies, while AIS 3–4 may be defined as ’moderate’ TBI and AIS 1–2 as ‘mild’.
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Rib fractures: comparison of associated injuries between pediatric and adult population.
Boris Kessel,Jasmin Dagan,Forat Swaid,Itamar Ashkenazi,Oded Olsha,Kobi Peleg,Adi Givon,Ricardo Alfici +7 more
TL;DR: The incidence of associated head, thoracic, and abdominal solid organ injuries in children was significantly higher than in adults suffering from rib fractures, and in spite of a higher Injury Severity Score and incidence of related injuries, mortality rate was similar.
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Incidence and Severity of Maxillofacial Injuries During the Second Lebanon War Among Israeli Soldiers and Civilians
TL;DR: In the Second Lebanon War, the incidence and severity of true maxillofacial injuries, without dental injuries alone, were relatively low compared with previous reports of other conflicts, however, because most injuries involved multiple organs, special attention is required when planning and providing emergency, as well as secondary and tertiary medical care to war wounded.
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ISS groups: Are we speaking the same language?
Michael Rozenfeld,Irina Radomislensky,Laurence S. Freedman,Adi Givon,Iliya Novikov,Kobi Peleg +5 more
TL;DR: Using a statistical analysis of two very large databases of trauma patients, it is found that partitioning of ISS into groups based on their association with patient mortality enables us to establish clear cut-off points for these groups.