Validating performance of TRISS, TARN and NORMIT survival prediction models in a Norwegian trauma population.

INTRODUCTION: Anatomic injury, physiological derangement, age, injury mechanism and pre-injury comorbidity are well-founded predictors of trauma outcome. Statistical prediction models may have poorer discrimination, calibration and accuracy when applied in new locations. We aimed to compare the TRISS, TARN and NORMIT survival prediction models in a Norwegian trauma population. METHODS: Consecutive patients admitted to Oslo University Hospital Ullevål within 24 h after injury, with Injury Severity Score ≥ 10, proximal penetrating injuries, or received by trauma team, were studied. Original NORMIT coefficients were updated in a derivation dataset (NORMIT 2; n = 5923; 2005-2009). TRISS, TARN and NORMIT prediction models were evaluated in the validation dataset (n = 6348; 2010-2013) using two different AIS editions for injury coding. Exclusion due to missing data was 0.26%. Outcome was 30-day mortality. Validation included AUROC, scaled Brier statistics, and calibration plots. RESULTS: The NORMIT models had significantly better discrimination, calibration, and overall fit than the TRISS 09, TARN 09 and TARN 12 models. The updated NORMIT 2 had higher numerical values of AUROC and scaled Brier than the original NORMIT, but with overlapping 95%CI. Overlapping 95%CI for AUROCs and Discrimination slopes indicated that the TARN and TRISS models performed similarly. Calibration plots showed tight and consistent predictions over all Ps strata for NORMIT 2 run on AIS'98 coded data, and only little deterioration when AIS'08 data was substituted. CONCLUSIONS: In a Norwegian trauma population, the updated Norwegian survival prediction model in trauma (NORMIT 2) performed better than well-established British and US alternatives. External validation of these three models in other Nordic populations is warranted.

Norwegian survival prediction model in trauma: modelling effects of anatomic injury, acute physiology, age, and co-morbidity.

INTRODUCTION: Anatomic injury, physiological derangement, age, and injury mechanism are well-founded predictors of trauma outcome. We aimed to develop and validate the first Scandinavian survival prediction model for trauma. METHODS: Eligible were patients admitted to Oslo University Hospital Ullevål within 24 h after injury with Injury Severity Score ≥ 10, proximal penetrating injuries or received by a trauma team. The derivation dataset comprised 5363 patients (August 2000 to July 2006); the validation dataset comprised 2517 patients (August 2006 to July 2008). Exclusion because of missing data was < 1%. Outcome was 30-day mortality. Logistic regression analysis incorporated fractional polynomial modelling and interaction effects. Model validation included a calibration plot, Hosmer-Lemeshow test and receiver operating characteristic (ROC) curves. RESULTS: The new survival prediction model included the anatomic New Injury Severity Score (NISS), Triage Revised Trauma Score (T-RTS, comprising Glascow Coma Scale score, respiratory rate, and systolic blood pressure), age, pre-injury co-morbidity scored according to the American Society of Anesthesiologists Physical Status Classification System (ASA-PS), and an interaction term. Fractional polynomial analysis supported treating NISS and T-RTS as linear functions and age as cubic. Model discrimination between survivors and non-survivors was excellent. Area (95% confidence interval) under the ROC curve was 0.966 (0.959-0.972) in the derivation and 0.946 (0.930-0.962) in the validation dataset. Overall, low mortality and skewed survival probability distribution invalidated model calibration using the Hosmer-Lemeshow test. CONCLUSIONS: The Norwegian survival prediction model in trauma (NORMIT) is a promising alternative to existing prediction models. External validation of the model in other trauma populations is warranted.

Grave acidosis after severe anaphylactic bronchospasm: friend or foe?

In a 20-year-old woman with known asthma, anaphylactic bronchospasm induced a grave combined respiratory and metabolic acidosis (pH(a) 6.66) with marked hypoxaemia (S(a)O(2) 45%). The beneficial effects of the rightward shift of the oxyhaemoglobin dissociation curve on tissue O(2) unloading at such pH was more than offset by the negative effect on S(a)O(2) at the reduced P(a)O(2) (7.0 kPa) found in this patient. This case illustrates the detrimental effect of grave acidosis on arterial blood oxygen content at subnormal P(a)O(2) values, the beneficial effect of a supranormal P(a)O(2) on the S(a)O(2) in such patients, and the rapid remission rate of life-threatening acidosis and blood lactate after adequate ventilation and tissue oxygenation were secured. The initial treatment of the patient and clinically relevant considerations are discussed.