Literature DB >> 30270118

Mortality prediction in pediatric trauma.

Teddy Muisyo1, Erika O Bernardo2, Maraya Camazine3, Ryan Colvin4, Kimberly A Thomas3, Matthew A Borgman5, Philip C Spinella3.   

Abstract

BACKGROUND: In trauma research, accurate estimates of mortality that can be rapidly calculated prior to enrollment are essential to ensure appropriate patient selection and adequate sample size. This study compares the accuracy of the BIG (Base Deficit, International normalized ratio and Glasgow Coma scale) score in predicting mortality in pediatric trauma patients to Pediatric Risk of Mortality III (PRISM III) score, Pediatric Index of Mortality 2 (PIM2) score and Pediatric Logistic Organ Dysfunction (PELOD) score.
METHODS: Data were collected from Virtual Pediatric Systems (VPS, LLC) database for children between 2004 and 2015 from 149 PICUs. Logistic regression models were developed to evaluate mortality prediction. The Area under the Curve (AUC) of Receiver Operator Characteristic (ROC) curves were derived from these models and compared between scores.
RESULTS: A total of 45,377 trauma patients were analyzed. The BIG score could only be calculated for 152 patients (0.33%). PRISM III, PIM2, and PELOD scores were calculated for 44,360, 45,377 and 14,768 patients respectively. The AUC of the BIG score was 0.94 compared to 0.96, 0.97 and 0.93 for the PRISM III, PIM2, and PELOD respectively.
CONCLUSIONS: The BIG score is accurate in predicting mortality in pediatric trauma patients. LEVEL OF EVIDENCE: Level I prognosis.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  BIG score; Mortality prediction; Pediatric trauma

Mesh:

Year:  2018        PMID: 30270118     DOI: 10.1016/j.jpedsurg.2018.08.045

Source DB:  PubMed          Journal:  J Pediatr Surg        ISSN: 0022-3468            Impact factor:   2.545


  4 in total

1.  Comparison of pediatric scoring systems for mortality in septic patients and the impact of missing information on their predictive power: a retrospective analysis.

Authors:  Christian Niederwanger; Thomas Varga; Tobias Hell; Daniel Stuerzel; Jennifer Prem; Magdalena Gassner; Franziska Rickmann; Christina Schoner; Daniela Hainz; Gerard Cortina; Benjamin Hetzer; Benedikt Treml; Mirjam Bachler
Journal:  PeerJ       Date:  2020-10-05       Impact factor: 2.984

2.  Impact of Intracranial Hypertension on Outcome of Severe Traumatic Brain Injury Pediatric Patients: A 15-Year Single Center Experience.

Authors:  Christos Tsitsipanis; Marianna Miliaraki; Konstantinos Ntotsikas; Dimitrios Baldounis; Emmanouil Kokkinakis; George Briassoulis; Maria Venihaki; Antonios Vakis; Stavroula Ilia
Journal:  Pediatr Rep       Date:  2022-08-16

3.  A hybrid method of recurrent neural network and graph neural network for next-period prescription prediction.

Authors:  Sicen Liu; Tao Li; Haoyang Ding; Buzhou Tang; Xiaolong Wang; Qingcai Chen; Jun Yan; Yi Zhou
Journal:  Int J Mach Learn Cybern       Date:  2020-06-23       Impact factor: 4.012

4.  Comparison of Injury Severity Score, Glasgow Coma Scale, and Revised Trauma Score in Predicting the Mortality and Prolonged ICU Stay of Traumatic Young Children: A Cross-Sectional Retrospective Study.

Authors:  Yii-Ting Huang; Ying-Hsien Huang; Ching-Hua Hsieh; Chao-Jui Li; I-Min Chiu
Journal:  Emerg Med Int       Date:  2019-12-01       Impact factor: 1.112

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.