Mortality prediction in pediatric trauma

Teddy Muisyo, Erika O. Bernardo, Maraya Camazine, Ryan Colvin, Kimberly A. Thomas, Matthew A. Borgman, Philip C. Spinella

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1613-1616
Number of pages4
JournalJournal of Pediatric Surgery
Volume54
Issue number8
DOIs
StatePublished - Aug 2019
Externally publishedYes

Keywords

  • BIG score
  • Mortality prediction
  • Pediatric trauma

ASJC Scopus subject areas

  • Surgery
  • Pediatrics, Perinatology, and Child Health

Fingerprint

Dive into the research topics of 'Mortality prediction in pediatric trauma'. Together they form a unique fingerprint.

Cite this