Performance of International Classification of Diseases-based injury severity measures used to predict in-hospital mortality and intensive care admission among traumatic brain-injured patients
| Autor: | Brice Lionel Batomen Kuimi, Lynne Moore, Claudia Beaudoin, Mathieu Gagné, Marie-Josée Sirois, Marc Simard |
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| Rok vydání: | 2017 |
| Předmět: |
Adult
Male medicine.medical_specialty Adolescent Traumatic brain injury education Population MEDLINE macromolecular substances Critical Care and Intensive Care Medicine 03 medical and health sciences 0302 clinical medicine Injury Severity Score International Classification of Diseases Predictive Value of Tests Brain Injuries Traumatic medicine Humans Intensive care admission Hospital Mortality Intensive care medicine health care economics and organizations Aged Retrospective Studies Aged 80 and over education.field_of_study In hospital mortality business.industry Quebec 030208 emergency & critical care medicine Retrospective cohort study Middle Aged medicine.disease Intensive Care Units nervous system Predictive value of tests Surgery Female business 030217 neurology & neurosurgery |
| Zdroj: | The journal of trauma and acute care surgery. 82(2) |
| ISSN: | 2163-0763 |
| Popis: | The International Classification of Diseases (ICD) is the main classification system used for population-based traumatic brain injury (TBI) surveillance activities but does not contain direct information on injury severity. International Classification of Diseases-based injury severity measures can be empirically derived or mapped to the Abbreviated Injury Scale, but no single approach has been formally recommended for TBI.The aim of this study was to compare the accuracy of different ICD-based injury severity measures for predicting in-hospital mortality and intensive care unit (ICU) admission in TBI patients.We conducted a population-based retrospective cohort study. We identified all patients 16 years or older with a TBI diagnosis who received acute care between April 1, 2006, and March 31, 2013, from the Quebec Hospital Discharge Database. The accuracy of five ICD-based injury severity measures for predicting mortality and ICU admission was compared using measures of discrimination (area under the receiver operating characteristic curve [AUC]) and calibration (calibration plot and the Hosmer-Lemeshow goodness-of-fit statistic).Of 31,087 traumatic brain-injured patients in the study population, 9.0% died in hospital, and 34.4% were admitted to the ICU. Among ICD-based severity measures that were assessed, the multiplied derivative of ICD-based Injury Severity Score (ICISS-Multiplicative) demonstrated the best discriminative ability for predicting in-hospital mortality (AUC, 0.858; 95% confidence interval, 0.852-0.864) and ICU admissions (AUC, 0.813; 95% confidence interval, 0.808-0.818). Calibration assessments showed good agreement between observed and predicted in-hospital mortality for ICISS measures. All severity measures presented high agreement between observed and expected probabilities of ICU admission for all deciles of risk.The ICD-based injury severity measures can be used to accurately predict in-hospital mortality and ICU admission in TBI patients. The ICISS-Multiplicative generally outperformed other ICD-based injury severity measures and should be preferred to control for differences in baseline characteristics between TBI patients in surveillance activities or injury research when only ICD codes are available.Prognostic study, level III. |
| Databáze: | OpenAIRE |
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