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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao University of Southe...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Trauma and Acute Care Surgery
Article . 2014 . Peer-reviewed
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Internationally comparable diagnosis-specific survival probabilities for calculation of the ICD-10–based Injury Severity Score

Authors: Gedeborg, R.; Warner, M.; Chen, L. H.; Gulliver, P.; Cryer, C.; Robitaille, Y.; Bauer, R.; +5 Authors

Internationally comparable diagnosis-specific survival probabilities for calculation of the ICD-10–based Injury Severity Score

Abstract

The International Statistical Classification of Diseases, 10th Revision (ICD-10)-based Injury Severity Score (ICISS) performs well but requires diagnosis-specific survival probabilities (DSPs), which are empirically derived, for its calculation. The objective was to examine if DSPs based on data pooled from several countries could increase accuracy, precision, utility, and international comparability of DSPs and ICISS.Australia, Argentina, Austria, Canada, Denmark, New Zealand, and Sweden provided ICD-10-coded injury hospital discharge data, including in-hospital mortality status. Data from the seven countries were pooled using four different methods to create an international collaborative effort ICISS (ICE-ICISS). The ability of the ICISS to predict mortality using the country-specific DSPs and the pooled DSPs was estimated and compared.The pooled DSPs were based on a total of 3,966,550 observations of injury diagnoses from the seven countries. The proportion of injury diagnoses having at least 100 discharges to calculate the DSP varied from 12% to 48% in the country-specific data set and was 66% in the pooled data set. When compared with using a country's own DSPs for ICISS calculation, the pooled DSPs resulted in somewhat reduced discrimination in predicting mortality (difference in c statistic varied from 0.006 to 0.04). Calibration was generally good when the predicted mortality risk was less than 20%. When Danish and Swedish data were used, ICISS was combined with age and sex in a logistic regression model to predict in-hospital mortality. Including age and sex improved both discrimination and calibration substantially, and the differences from using country-specific or pooled DSPs were minor.Pooling data from seven countries generated empirically derived DSPs. These pooled DSPs facilitate international comparisons and enables the use of ICISS in all settings where ICD-10 hospital discharge diagnoses are available. The modest reduction in performance of the ICE-ICISS compared with the country-specific scores is unlikely to outweigh the benefit of internationally comparable Injury Severity Scores possible with pooled data.Prognostic and epidemiological study, level III.

Keywords

Adult, Male, Canada, Denmark, Argentina, International Classification of Diseases, Predictive Value of Tests, Cause of Death, Humans, Wounds and Injuries/classification, Hospital Mortality, Probability, Sweden, Trauma Severity Indices, Australia, International Classification of Diseases/classification, Middle Aged, Survival Analysis, Patient Discharge, Logistic Models, Patient Discharge/statistics & numerical data, Austria, Female, New Zealand

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
53
Top 10%
Top 10%
Top 10%
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