Injury profiles related to mortality in patients with a low Injury Severity Score

Joosse, Pieter; Schep, Niels W. L.; Goslings, J. Carel

doi:10.1097/ta.0b013e31824ac8f5

Cited by 3 publications

(2 citation statements)

References 32 publications

(23 reference statements)

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“… 31 Joosse et al even identified specific injury profiles of low ISS patients associated with mortality. 32 TEMPT provides benefit early in the course of care and does so independently of retrospective ISS.…”

Section: Discussionmentioning

confidence: 99%

Trauma Early Mortality Prediction Tool (TEMPT) for assessing 28-day mortality

Kunitake

Kornblith

Cohen

et al. 2018

Trauma Surg Acute Care Open

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BackgroundPrior mortality prediction models have incorporated severity of anatomic injury quantified by Abbreviated Injury Severity Score (AIS). Using a prospective cohort, a new score independent of AIS was developed using clinical and laboratory markers present on emergency department presentation to predict 28-day mortality.MethodsAll patients (n=1427) enrolled in an ongoing prospective cohort study were included. Demographic, laboratory, and clinical data were recorded on admission. True random number generator technique divided the cohort into derivation (n=707) and validation groups (n=720). Using Youden indices, threshold values were selected for each potential predictor in the derivation cohort. Logistic regression was used to identify independent predictors. Significant variables were equally weighted to create a new mortality prediction score, the Trauma Early Mortality Prediction Tool (TEMPT) score. Area under the curve (AUC) was tested in the validation group. Pairwise comparison of Trauma Injury Severity Score (TRISS), Revised Trauma Score, Glasgow Coma Scale, and Injury Severity Score were tested against the TEMPT score.ResultsThere was no difference between baseline characteristics between derivation and validation groups. In multiple logistic regression, a model with presence of traumatic brain injury, increased age, elevated systolic blood pressure, decreased base excess, prolonged partial thromboplastin time, increased international normalized ratio (INR), and decreased temperature accurately predicted mortality at 28 days (AUC 0.93, 95% CI 0.90 to 0.96, P<0.001). In the validation cohort, this score, termed TEMPT, predicted 28-day mortality with an AUC 0.94 (95% CI 0.92 to 0.97). The TEMPT score preformed similarly to the revised TRISS score for severely injured patients and was highly predictive in those having mild to moderate injury.DiscussionTEMPT is a simple AIS-independent mortality prediction tool applicable very early following injury. TEMPT provides an AIS-independent score that could be used for early identification of those at risk of doing poorly following even minor injury.Level of evidenceLevel II.

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Section: Discussionmentioning

confidence: 99%

Trauma Early Mortality Prediction Tool (TEMPT) for assessing 28-day mortality

Kunitake

Kornblith

Cohen

et al. 2018

Trauma Surg Acute Care Open

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“…Data from the trauma registry (TR) are also used for a variety of research purposes, such as validation studies (eg, emergency trauma score), retrospective observational or diagnostic research and for calculating the number of additional survivors in a hospital compared with a reference standard (standardised W statistics) 5 6. Accurate and reliable data are vital if meaningful conclusions are to be drawn.…”

Section: Introductionmentioning

confidence: 99%

A Dutch regional trauma registry: quality check of the registered data

et al. 2013

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Performance of the modified TRISS for evaluating trauma care in subpopulations: A cohort study

Munter

Polinder

Nieboer

et al. 2018

Injury

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A B S T R A C TIntroduction: Previous research showed that there is no agreement on a practically applicable model to use in the evaluation of trauma care. A modification of the Trauma and Injury Severity Score (modified TRISS) is used to evaluate trauma care in the Netherlands. The aim of this study was to evaluate the prognostic ability of the modified TRISS and to determine where this model needs improvement for better survival predictions. Methods: Patients were included if they were registered in the Brabant Trauma Registry from 2010 through 2015. Missing values were imputed according to multiple imputation. Subsets were created based on age, length of stay, type of injury and injury severity. Probability of survival was calculated with the modified TRISS. Discrimination was assessed with the Area Under the Receiver Operating Curve (AUROC). Calibration was studied graphically. Results: The AUROC was 0.84 (95% CI: 0.83, 0.85) for the total cohort (N = 69 747) but only 0.53 (95% CI: 0.51, 0.56) for elderly patients with hip fracture. Overall, calibration of the modified TRISS was adequate for the total cohort, with an overestimation for elderly patients and an underestimation for patients without brain injury. Conclusions: Outcome comparison conducted with TRISS-based predictions should be interpreted with care. If possible, future research should develop a simple prediction model that has accurate survival prediction in the aging overall trauma population (preferable with patients with hip fracture), with readily available predictors.

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Injury profiles related to mortality in patients with a low Injury Severity Score

Abstract: Prognostic study, level II.

Cited by 3 publications

References 32 publications

Trauma Early Mortality Prediction Tool (TEMPT) for assessing 28-day mortality

Trauma Early Mortality Prediction Tool (TEMPT) for assessing 28-day mortality

A Dutch regional trauma registry: quality check of the registered data

Performance of the modified TRISS for evaluating trauma care in subpopulations: A cohort study

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