Existing systems for trauma severity scoring are based on studies of urban trauma in the North and are inaccurate in severity classification of rural trauma in the South. Accurate classifications are important for two reasons:
1. To triage and monitor the treatment of individual patients.
2. To monitor the quality of performance in trauma systems and identify patients with unexpected outcome, e.g. patients dying despite survival risk ratio < 0.5.
The international “golden standard” for severity scoring and probability of survival (Ps) calculation is the Trauma and Injury Severity Score/TRISS. TRISS is a composite calculator based on anatomical and physiological severity indicators. For TRISS operation, the RTS parameters (RR, BP, GCS) are vected, vectors being deducted by logistic regression analysis on large US trauma databases:
RTS (vected) = 0.9386(GCS code) + 0.7326(BP code) + 0.2908(RR code). RTS can thus take on values from 0 to 7.848.
TRISS is based on a probability distribution: Ps = 1 / (1 + e) ^(– b)
The value of b is set by the regression equation: b = b0 + b1(RTS) + b2(ISS) + b3(AGE). AGE is defined as a dichotome variable: (AGE ≤55 years) = 0; (AGE >55 years) = 1.The value of b is set separately for blunt and penetrating injuries.
Problems with TRISS
1. ISS is context dependent: The AIS codes are based on what is “moderate” or “critical” in high-tech US urban trauma systems.
2. RTS is context dependent: The vectors are derived from studies of well-fed, (mainly) healthy Westerners.
3. AGE is context dependent: “Old” being defined as age >55 years does not apply to all trauma settings.
4. The time factor is not included: Being briefly hypotensive (BP = 70, RTS code = 2) and being hypotensive for 3 hours (BP = 70, RTS code = 2) makes a big difference (PEKER).
5. Methodological failure – 1: The GCS parameter in RTS is inaccurate. The GCS scores are skewed toward motor response impact, patients with the same score may have significantly different Ps. There are also rater failures, particularly for inexperienced raters and for scoring at intermediate levels of consciousness. The rate of GCS scoring failures may be as high as 50% (PEKER).
6. Methodological failure - 2: In logistic regression analysis there should not be co-linearity between the predictors. But RR, BP, and GCS are tied, all three variables being indicators of oxygen starvation, which may give false high TRISS prediction.
7. Methodological failure – 3: The TRISS goodness-of-fit is low in your study population if the distribution of predictors differs significantly from the distribution in the US reference population.
Conclusion: Make your own “TRISS” !