Base Deficit, International Normalized Ratio, and Glasgow Coma Scale (BIG) is a Predictor Tool for Survival and Mortality of Pediatric Trauma Patients
Bibliographic record
Abstract
Background: An accurate estimate of the survival and mortality at the initial trauma evaluation is essential to ensure appropriate triage and stratification of the patients for progressive care. One of the recognized tools for predicting mortality is the BIG Score, composed of admission base deficit, international normalized ratio (INR), and Glasgow Coma Scale (GCS). This study evaluates the BIG scale in predicting survival and mortality rates among pediatric trauma patients. Methods: Pediatric trauma patients, aged <18 years, visiting the emergency department of a tertiary hospital in the North of Jordan from 2014 to 2019 were included. Demographic data, trauma details, and lab results were collected. The BIG score for each patient was calculated. A receiver operator characteristic (ROC) curve was generated to determine the best suitable BIG cutoff point and its probabilities. Results: A total of 424 patients were included in this study. About two-thirds of the patients were males (n=298). The mean±SD of pH and GCS values were significantly lower among dead patients (6.0±2.5, 3.7±3.9, respectively) in comparison to alive ones (7.3±2.7, 11.5±5.5, respectively) (p=0.026, p<0.001, respectively). On the other hand, base deficit and INR values were significantly higher among dead patients (6.5±6.2, 1.9±2.5, respectively) than alive ones (1.9±3.6, 0.8±0.5, respectively), (p<0.001). The BIG score with a cutoff point of ≥10.0 has a high sensitivity (88.5%) and specificity (76.3%) for mortality prediction. The survival rate was correctly predicted in 100% of patients with a BIG score between 2.1 and 6. Also, the best survival predictions were seen in intubated patients (100%), followed by RTA-related trauma and ICU admission with decreasing frequency. Conclusions: The current study has shown the added value of the BIG score as a simple and rapid tool to predict prognosis in pediatric trauma settings. The BIG score with a cutoff point of ≥10.0 is highly efficient in predicting pediatric trauma patients' mortality rates. However, the BIG score demonstrates greater accuracy in predicting survival outcomes compared to its ability to predict mortality among pediatric trauma patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".