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N orwegian survival prediction model in trauma: modelling effects of anatomic injury, acute physiology, age, and co‐morbidity
Author(s) -
JONES J. M.,
SKAGA N. O.,
SØVIK S.,
LOSSIUS H. M.,
EKEN T.
Publication year - 2014
Publication title -
acta anaesthesiologica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.738
H-Index - 107
eISSN - 1399-6576
pISSN - 0001-5172
DOI - 10.1111/aas.12256
Subject(s) - medicine , glasgow coma scale , receiver operating characteristic , injury severity score , logistic regression , triage , revised trauma score , confidence interval , emergency medicine , poison control , surgery , injury prevention
Anatomic injury, physiological derangement, age, and injury mechanism are well‐founded predictors of trauma outcome. We aimed to develop and validate the first S candinavian survival prediction model for trauma. Methods Eligible were patients admitted to O slo U niversity H ospital U llevål within 24 h after injury with I njury S everity S core ≥ 10, proximal penetrating injuries or received by a trauma team. The derivation dataset comprised 5363 patients ( A ugust 2000 to J uly 2006); the validation dataset comprised 2517 patients ( A ugust 2006 to J uly 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, H osmer– L emeshow test and receiver operating characteristic ( ROC ) curves. Results The new survival prediction model included the anatomic N ew I njury S everity S core ( NISS ), T riage R evised T rauma S core ( T‐RTS , comprising G lascow C oma S cale score, respiratory rate, and systolic blood pressure), age, pre‐injury co‐morbidity scored according to the A merican S ociety of A nesthesiologists P hysical S tatus C lassification S ystem ( 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 H osmer– L emeshow test. Conclusions The N orwegian 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.