Evidence map›Paper›PMID 39002978›Full record

ArticleInjury prevention : journal of the International Society for Child and Adolescent Injury Prevention2025

International Classification of Disease based Injury Severity Score (ICISS): a comparison of methodologies applied to linked data from New South Wales, Australia.

Janneke Berecki-Gisolf, Ehsan Rezaei-Darzi, D Tharanga Fernando, Angelo DElia

Abstract readComparative Study
In one paragraph

Article in Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Janneke Berecki-GisolfMonash University Accident Research Centre, Monash University, Clayton, Victoria, Australia janneke.berecki-gisolf@monash.edu.ORCID 0000-0002-5035-3547
Ehsan Rezaei-DarziMonash University Accident Research Centre, Monash University, Clayton, Victoria, Australia.
D Tharanga FernandoMonash University Accident Research Centre, Monash University, Clayton, Victoria, Australia.
Angelo DEliaMonash University Accident Research Centre, Monash University, Clayton, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe International Classification of Disease Injury Severity Score (ICISS) provides an efficient method to determine injury severity in hospitalised injury patients. Injury severity metrics are of particular interest for the tracking of road transport injury rates and trends. The aims of this study were to calculate ICISS using linked morbidity and mortality datasets and to compare predictive ability of various methods and metrics.

methodsThis was a retrospective analysis of Admitted Patient Data Collection records from New South Wales, Australia, linked with mortality data. Using a split sample approach, design data (2008-2014; n=1 035 174 periods of care) was used to derive survival risk ratios and calculate various ICISS scales based on in-hospital death and 3-month death. These scales were applied to testing data (2015-2017; n=575 306). Logistic regression modelling was used to determine model discrimination and calibration.

resultsThere were 12 347 (1.19%) in-hospital deaths and 29 275 (2.83%) 3-month deaths in the design data. Model discrimination ranged from acceptable to excellent (area under the curve 0.75-0.88). Serious injury (ICISS≤0.941) rates in the testing data varied, with a range of 10%-31% depending on the methodology. The 'worst injury' ICISS was always superior to 'multiplicative injury' ICISS in model discrimination and calibration.

conclusionsIn-hospital death and 3-month death were used to generate ICISS; the former is recommended for settings with a focus on short-term threat to life, such as in trauma care settings. The 3-month death approach is recommended for outcomes beyond immediate clinical care, such as injury compensation schemes.

Indexed as

Accidents, TrafficInjury Severity ScoreInternational Classification of DiseasesWounds and InjuriesAdolescentAdultAgedFemaleHospital MortalityHumansMaleMiddle AgedNew South WalesRetrospective StudiesYoung AdultDesignOutcome of InjurySeverity Scales

Identifiers

PMID39002978
PMCPMC12703290

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.