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Submitted: 18 Nov 2016
Revision: 19 Nov 2016
Accepted: 19 Nov 2016
ePublished: 19 Nov 2016
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J Med Physiol. 2016;1(2): 67-71.
  Abstract View: 5
  PDF Download: 5

Original Research

Value of physiological scoring systems in prediction of long-term mortality in traumatic brain injury patients

Sahar Mirbaha, Alireza Baratloo, Parviz Karimi*
*Corresponding Author: Email: kpdrem91@gmail.com

Abstract

Introduction: Rapid acute physiological score (RAPS) and Worthing physiological scoring system (WPSS) models have received much attention in recent years. Yet, the value of these systems in outcome prediction of traumatic brain injury (TBI) patients has not been assessed. Therefore, the present study was designed aiming to compare the value of the 2 mentioned models in prediction of 6-month mortality of head trauma patients.

Methods: The present study is a diagnostic accuracy one evaluating head trauma patients presenting to emergency department. Each patient had a WPSS score and a RAPS score, and then the discriminatory powers of the 2 models with 95% confidence interval (95% CI) were compared.

Results: Data of 735 head trauma patients was assessed. During the 6-month follow-up, 48 (6.53%) patients died. Area under the curve of RAPS and WPSS in prediction of 6-month mortality were 0.93 (95% CI: 0.88-0.98) and 0.97 (95% CI: 0.96-0.98), respectively. The 2 evaluation models had similar value in prediction of mortality in head trauma patients (p = 0.10). The best cut off point for RAPS and WPSS in prediction of trauma patients’ mortality was 5 and 2, respectively. RAPS had sensitivity and specificity of 89.58 (95% CI: 76.56-96.10) and 85.15 (95% CI: 82.22-87.68), respectively. Sensitivity and specificity of WPSS model were 100.0 (95% CI: 90.77-100.0) and 87.92 (95% CI: 85.19-90.21), respectively.

Conclusion: Findings show that there is a significant correlation between physiological factors on admission and mortality of head trauma patients. In addition, it was determined that RAPS and WPSS physiological scoring systems have high value in prediction of mortality following TBI.

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