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Searching for mortality predictors in trauma patients: a challenging task

Overview of attention for article published in European Journal of Trauma and Emergency Surgery, August 2017
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Title
Searching for mortality predictors in trauma patients: a challenging task
Published in
European Journal of Trauma and Emergency Surgery, August 2017
DOI 10.1007/s00068-017-0830-6
Pubmed ID
Authors

A. A. Cevik, F. M. Abu-Zidan

Abstract

We aimed to study the value of new physiological variables compared with ISS and GCS as predictors for trauma mortality in a high-income developing country having a young population. Data of 1008 consecutive trauma patients who were included in Al-Ain City Road Traffic Collision Registry were analyzed. Demography of patients, systolic blood pressure, heart rate, shock index, shock index age (SIA), blood pressure age index (BPAI), Glasgow Coma Scale (GCS), injury severity score (ISS), and in-hospital mortality were analyzed. Univariate analysis was used to compare those who died with those who survived. Significant factors were then entered into a backward logistic regression model to define factors predicting mortality. 80.3% of the patients were males. The median (range) age of patients was 26 (1-78) years. Significant factors that predicted mortality were GCS (p < 0.0001), SIA (p = 0.003), ISS (p = 0.007), and BPAI (p = 0.022). The physiological variables including GCS and shock index age were better predictors for trauma mortality comparted with ISS in our young population. A large global multi-centric study could possibly define an accurate global formula that uses both anatomical and physiological variables for predicting trauma mortality.

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The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 11%
Student > Ph. D. Student 3 8%
Researcher 3 8%
Professor 3 8%
Student > Master 3 8%
Other 9 25%
Unknown 11 31%
Readers by discipline Count As %
Medicine and Dentistry 18 50%
Nursing and Health Professions 2 6%
Biochemistry, Genetics and Molecular Biology 1 3%
Environmental Science 1 3%
Engineering 1 3%
Other 0 0%
Unknown 13 36%