Chapter title |
Prognosis of Severe Traumatic Brain Injury Outcomes in Children
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Chapter number | 3 |
Book title |
Intracranial Pressure & Neuromonitoring XVI
|
Published in |
Acta neurochirurgica Supplement, January 2018
|
DOI | 10.1007/978-3-319-65798-1_3 |
Pubmed ID | |
Book ISBNs |
978-3-31-965797-4, 978-3-31-965798-1
|
Authors |
Semen V. Meshcheryakov, Zhanna B. Semenova, Valery I. Lukianov, Elena G. Sorokina, Olga V. Karaseva, Meshcheryakov, Semen V., Semenova, Zhanna B., Lukianov, Valery I., Sorokina, Elena G., Karaseva, Olga V. |
Abstract |
We aimed to determine prognostic factors that can influence the outcome of severe traumatic brain injury (TBI) in children. One hundred and sixty-nine patients with severe TBI were included. Consciousness was evaluated using the Glasgow Coma Scale (GCS). Severity of concomitant injuries was evaluated using the Injury Severity Score (ISS). Computer tomography (CT) scanning was used on admission and later. Intracranial injuries were classified using the Marshall CT scale. Intracranial pressure (ICP) monitoring took place in 80 cases. Serum samples of 65 patients were tested for S-100β protein and of 43 patients for neuron specific enolase (NSE). Outcomes were evaluated 6 months after trauma using the Glasgow Outcome Scale (GOS). Statistical and mathematical analysis was conducted. The accuracy of our prognostic model was defined in another group of patients (n = 118). GCS, pupil size and photoreaction, ISS, hypotension and hypoxia are significant predictors of outcome of severe TBI in children. CT results complement the forecast significantly. The accuracy of surviving prognosis came to 76% (0.76) in case of S-100β protein level ≤ 0.25 μg/l and NSE level < 19 μg/l. A mathematical model of outcome prognosis was based on discriminant function analysis. The model of prognosis was tested on the control group. The accuracy of prognosis was 86%. A personalised prognostic model makes it possible to predict the outcome of severe TBI in children on the first day after trauma. |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 31 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Bachelor | 7 | 23% |
Student > Postgraduate | 4 | 13% |
Student > Ph. D. Student | 3 | 10% |
Researcher | 3 | 10% |
Student > Doctoral Student | 2 | 6% |
Other | 5 | 16% |
Unknown | 7 | 23% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 6 | 19% |
Neuroscience | 4 | 13% |
Psychology | 3 | 10% |
Biochemistry, Genetics and Molecular Biology | 2 | 6% |
Nursing and Health Professions | 2 | 6% |
Other | 4 | 13% |
Unknown | 10 | 32% |