Predicting mortality with the international classification of disease injury severity score using survival risk ratios derived from an Indian trauma population: A cohort study
Adult
Male
Trauma Severity Indices
Adolescent
Science
Q
R
India
Middle Aged
Survival Analysis
3. Good health
Cohort Studies
Young Adult
03 medical and health sciences
0302 clinical medicine
ROC Curve
Risk Factors
Medicine
Humans
Wounds and Injuries
Female
Child
Research Article
DOI:
10.1371/journal.pone.0199754
Publication Date:
2018-06-27T13:54:04Z
AUTHORS (8)
ABSTRACT
Background Trauma is predicted to become the third leading cause of death in India by 2020, which indicate need for urgent action. scores such as international classification diseases injury severity score (ICISS) have been used with great success trauma research and quality programmes improve care. To this date no valid has developed Indian population. Study design This retrospective cohort study a dataset 16047 trauma-patients from four public university hospitals urban India, was divided into derivation validation subsets. All injuries were assigned an disease (ICD) code. Survival Risk Ratios (SRRs), mortality within 24 hours 30 days then calculated each ICD-code calculate corresponding ICISS. Score performance measured using discrimination calculating area under receiver operating characteristics curve (AUROCC) calibration slope intercept plot curve. Results Predictions 30-day showed AUROCC 0.618, 0.269 0.071. Estimates 24-hour consistently low AUROCCs negative slopes. Conclusions We attempted derive validate version ICISS SRRs However, ICISS-scores overestimate implementing these clinical or policy contexts not recommended. study, well previous reports, suggest that other scoring systems might be better suited Low- middle-income countries until more data are available.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES (28)
CITATIONS (5)
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....