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Risk prediction score for death of traumatised and injured children
Sakda Arj-ong Vallipakorn1, Adisak Plitapolkarnpim, Paibul Suriyawongpaisal
1Section for Clinical Epidemiology and Biostatistics, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Rama VI Road, Rajathevi, Bangkok 10400, Thailand. dr.sakda@gmail.com.
Insights
A new Thai pediatric injury death prediction score was developed to aid clinical management. This validated model accurately identifies children at risk of death in emergency settings.
Area of Science:
- Pediatric emergency medicine
- Trauma care
- Clinical prediction modeling
Background:
- Existing injury prediction scores lack specificity for pediatric populations.
- There is a need for a validated risk assessment tool for injured children in Thailand.
Purpose of the Study:
- To develop and validate a risk prediction model for mortality in injured and traumatized Thai children.
- To create a simplified scoring system for practical use in emergency settings.
Main Methods:
- A cross-sectional study of 43,516 injured children from 34 emergency services.
- Logistic regression analysis was used to derive a model with 15 predictors.
- Model performance was assessed using the concordance statistic (C-statistic) and observed/expected (O/E) ratio, with internal validation via bootstrap analysis.
Main Results:
- The mortality rate was 1.7%. Ten predictors, including age, airway intervention, injury mechanism, body regions, Glasgow Coma Scale, and vital signs, were significant.
- The model demonstrated strong performance with a C-statistic of 0.938 and an O/E ratio of 0.86.
- The scoring scheme provided risk stratifications with distinct likelihood ratios for low, intermediate, and high risk of death, showing good calibration and discrimination.
Conclusions:
- A simplified Thai pediatric injury death prediction score was successfully developed.
- The score exhibits satisfactory calibrated and discriminative performance for use in emergency room settings.
- This tool can potentially improve clinical management protocols and reduce mortality in injured children.
Background:
Injury prediction scores facilitate the development of clinical management protocols to decrease mortality. However, most of the previously developed scores are limited in scope and are non-specific for use in children. We aimed to develop and validate a risk prediction model of death for injured and Traumatised Thai children.
Methods:
Our cross-sectional study included 43,516 injured children from 34 emergency services. A risk prediction model was derived using a logistic regression analysis that included 15 predictors. Model performance was assessed using the concordance statistic (C-statistic) and the observed per expected (O/E) ratio. Internal validation of the model was performed using a 200-repetition bootstrap analysis.
Results:
Death occurred in 1.7% of the injured children (95% confidence interval [95% CI]: 1.57-1.82). Ten predictors (i.e., age, airway intervention, physical injury mechanism, three injured body regions, the Glasgow Coma Scale, and three vital signs) were significantly associated with death. The C-statistic and the O/E ratio were 0.938 (95% CI: 0.929-0.947) and 0.86 (95% CI: 0.70-1.02), respectively. The scoring scheme classified three risk stratifications with respective likelihood ratios of 1.26 (95% CI: 1.25-1.27), 2.45 (95% CI: 2.42-2.52), and 4.72 (95% CI: 4.57-4.88) for low, intermediate, and high risks of death. Internal validation showed good model performance (C-statistic = 0.938, 95% CI: 0.926-0.952) and a small calibration bias of 0.002 (95% CI: 0.0005-0.003).
Conclusions:
We developed a simplified Thai pediatric injury death prediction score with satisfactory calibrated and discriminative performance in emergency room settings.
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