Literature DB >> 14608168

Independently derived survival risk ratios yield better estimates of survival than traditional survival risk ratios when using the ICISS.

J Wayne Meredith1, Patrick D Kilgo, Turner M Osler.   

Abstract

BACKGROUND: The International Classification of Diseases, Ninth Revision Injury Severity Score (ICISS) is criticized because it relies on survival risk ratios (SRRs) that are contaminated by incidents with multiple injuries. An SRR for an International Classification of Diseases, Ninth Revision code is the number of patients who survive the injury divided by the number who display it. The ICISS is the product of SRRs that correspond to a patient's injuries. Traditional SRRs are derived from databases that include patients with multiple injuries and are biased toward mortality, making them nonindependent. Independent SRRs are derived from incidents where patients sustained only an isolated injury. The objective of this study is to compare the mortality prediction abilities of independent and traditional SRRs via the ICISS.
METHODS: A 10-fold cross-validation design was used to estimate independent and traditional SRRs and their resulting ICISSs from 192,347 National Trauma Data Bank patients. Logistic regression modeled the scores as a function of mortality. The area under the receiver operating characteristic curve measured discrimination. Model fit was measured with the Akaike information criterion, a deviance statistic (lower is better). R2 values were compared to determine which score explained the most variance.
RESULTS: The independent ICISS statistically outperforms the traditional ICISS.
CONCLUSION: Traditional SRRs used by the ICISS produce less accurate estimates of mortality than independent SRRs. The ICISS can be calculated in 97.9% of incidents using independent SRRs.

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Year:  2003        PMID: 14608168     DOI: 10.1097/01.TA.0000085646.71451.5F

Source DB:  PubMed          Journal:  J Trauma        ISSN: 0022-5282


  6 in total

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2.  Mortality-based Quantification of Injury Severity for Frequently Occurring Motor Vehicle Crash Injuries.

Authors:  Ashley A Weaver; Ryan T Barnard; Patrick D Kilgo; R Shayn Martin; Joel D Stitzel
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3.  Incorporation of physiological trend and interaction effects in neonatal severity of illness scores: an experiment using a variant of the Richardson score.

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4.  Evaluating the validity of multiple imputation for missing physiological data in the national trauma data bank.

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5.  Predicting mortality with the international classification of disease injury severity score using survival risk ratios derived from an Indian trauma population: A cohort study.

Authors:  Jonatan Attergrim; Mattias Sterner; Alice Claeson; Satish Dharap; Amit Gupta; Monty Khajanchi; Vineet Kumar; Martin Gerdin Wärnberg
Journal:  PLoS One       Date:  2018-06-27       Impact factor: 3.240

Review 6.  Systematic review of predictive performance of injury severity scoring tools.

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  6 in total

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