SurgCalc
Trauma
CEM-Trauma Expected Mortality Model
A transparent expected-mortality estimate for registry-based trauma quality review, benchmark comparison, and research. It uses AIS/ISS injury coding plus early physiology and is not a standalone bedside decision tool.
Train N3,817,361
Test AUC0.903
TRISS AUC0.879
cNRI vs TRISS+0.517
Model lockApr 2026
Intended use: registry/QI expected-mortality review
For benchmarking, audit, and research after injury coding is available. Not for bedside triage, treatment, disposition, or goals-of-care decisions. No data leaves your browser.
Full disclosures, limitations & terms of use
Use Case
CEM-Trauma is designed for post hoc expected-mortality review, not real-time clinical command.
Appropriate: registry-based quality review, observed-to-expected benchmarking, transparent model audit, and research comparison with historical TRISS.
Not appropriate: standalone bedside decisions, trauma activation, admission level, procedures, consultations, disposition, or goals-of-care conversations.
Implementation note: EMR integration is most defensible after AIS/ISS coding or reliable automated injury coding, with local recalibration and governance.
Step 1 — Injuries by Body Region
Select the most severe injury in each region. AIS scores and ISS update automatically.
Head / Brain
AIS 0
Face
AIS 0
Chest / Thorax
AIS 0
Abdomen / Pelvis
AIS 0
Extremity / Pelvis
AIS 0
External / Burns
AIS 0
ISS
0
Top 3 regions²
Head
0
—
Face
0
—
Chest
0
—
Abdomen
0
—
Extremity
0
—
External
0
—
ISS (auto)
0
Sum of top 3 AIS²
AIS Head (auto)
0
Model predictor
AIS Chest (auto)
0
Model predictor
AIS Abdomen (auto)
0
Model predictor
Mechanism
—
From Step 2
Step 2 — Demographics, Mechanism & ED Physiology
All values from ED presentation at time of trauma activation.
Glasgow Coma Scale
GCS Total (E+V+M)
15
Severe TBI: ≤8
Moderate: 9–12
Mild: 13–15
Moderate: 9–12
Mild: 13–15
Step 3 — Predicted Mortality Risk
TQIP logistic model — temporally validated prospective test set 2023–2024
In-Hospital Mortality
—
—
Predicted probability—
Linear predictor (b)—
Risk tier—
ISS used—
GCS used—
Model AUC (test set 2023–2024)0.903
Brier score (test set)0.0193
Test set N1,581,953 patients
Model Comparison — CEM-Trauma vs. TRISS
This model — predicted risk—
TRISS test-set AUC0.879 (historical benchmark)
Improvement (ΔAUC)+0.024 absolute
Net reclassification (cNRI)+0.517
—