Update on the definition of polytrauma

Butcher, Nerida E.; Balogh, Zsolt J.

doi:10.1007/s00068-014-0391-x

Cited by 46 publications

(30 citation statements)

References 43 publications

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“…ISS > 20 or ISS > 25) results in an increased specificity but excludes patients with two injuries rated AIS = 3. In general, the exclusive use of an anatomical score ignores the physiological aspects of polytrauma, which are supposed to pose an extremely important additional factor in polytrauma rating [25, 26]. Of the 11 definitions scrutinized here, solely the Berlin definition includes five independent physiologic parameters, which were chosen by a panel of international experts after extensive research.…”

Section: Discussionmentioning

confidence: 99%

Does the applied polytrauma definition notably influence outcome and patient population? – a retrospective analysis

Frenzel

Krenn

Heinz

et al. 2017

Scand J Trauma Resusc Emerg Med

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BackgroundAlthough the term “polytrauma” has been in use for decades, no generally accepted definition exists. The aim of this study was to demonstrate that different polytrauma definitions applied to a specific patient population result in diverse subgroups of individuals, who in turn present a varying outcome.MethodsAll patients (≥18 years) treated at our level I trauma center within a time period of three years were classified according to 11 selected polytrauma definitions and included in our study, if they were rated “polytraumatized” by at least one of these definitions. All patients, who met the criteria of a certain definition, were combined to the relevant definition-positive group, thus resulting in 11 patient subgroups. Their demographic data (number of patients, mean patient age, mean Injury Severity Score value, median number of ventilator days, median length of stay at the intensive care unit and at the hospital, mortality rate and odds ratio) were statistically compared.ResultsThree hundred seventy-five patients (73% male) with a mean age of 47 years met the inclusion criteria and were allocated to the relevant subgroups; their patient number varied from 55 to 346 and their mean Injury Severity Score value ranged from 4 to 75. Not surprisingly, all examined parameters were subject to variations. Whereas most definition-positive groups showed a mortality rate of about 21% to 30%, 18% of the individuals, who met the criteria according to Blacker, and 40% of the polytrauma victims according to Schalamon died. The Pape 1-, Schalamon-, and Berlin-positive groups presented a significant odds ratio with regard to mortality that considerably exceeded 1.DiscussionA polytrauma definition can only be a reliable tool in classifying trauma victims if it provides a significant odds ratio with regard to mortality that considerably exceeds 1 and if it succeeds in capturing patients with multiple severe injuries and a higher mortality rate without reducing the number of polytraumatized patients to a not representatively small number.ConclusionsSolely the Berlin definition resulted in a patient number reflecting clinical reality, thus enabling a transparent evaluation of treatment results provided by different institutions and allowing objective comparison of published studies.

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Section: Discussionmentioning

confidence: 99%

Does the applied polytrauma definition notably influence outcome and patient population? – a retrospective analysis

Frenzel

Krenn

Heinz

et al. 2017

Scand J Trauma Resusc Emerg Med

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“…Patients with permanent altered consciousness or Glasgow Coma Scale (GCS) less than 12 and evidence of structural brain damage were considered as TBI. Patients with trauma to the thorax and abdomen or pelvic regions (two or more anatomical regions injured) [10] were defined as PI. We also considered Traynelis classification of AOD as a variable of study, as almost every published AOD patient has been classified using this system [8].…”

Section: Methodsmentioning

confidence: 99%

Prognostic factors in traumatic atlanto-occipital dislocation

Fard

Avila

Johnstone

et al. 2016

Journal of Clinical Neuroscience

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“…231 Th is defi nition has, however, been neither investigated nor validated in the TBI population, and thus, the role of MEI on outcome aft er TBI remains controversial. Standardized data collection and uniform defi nitions are advocated for appropriate prognostic research, so that the best treatment for TBI patients with associated injuries can be determined.…”

Section: Major Extra-cranial Injurymentioning

confidence: 99%

Prognostic models in traumatic brain injury

Raj

2015

Acta Anaesthesiol Scand

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Background Prognostic models are important tools for heterogeneity adjustment in traumatic brain injury (TBI). Prognoses after TBI have been particularly challenging to predict, with limited availability of robust prognostic models. TBI patients are by definition trauma patients, and often treated in the intensive care unit (ICU). Several prognostic models for ICU and trauma patients have been developed, although their applicability in patients with TBI is uncertain. Recently, however, some new prognostic models specifically designed for patients with TBI were introduced. Still, the optimal type of prognostic model in TBI remains unknown. Aim This aims to investigate the applicability of different types of prognostic models in patients with TBI and to develop novel models with enhanced performance to previous models, focusing on long‐ term outcome prediction. Methods Four patient databases of patients with TBI treated in the ICU were used to validate three TBI specific models, two computerized tomography (CT) scoring systems, one trauma scoring system, and three intensive care scoring systems. Models were validated by assessing their discrimination using area under the curve (AUC), calibration, and explanatory variation. Logistic regression was used for model customization and development. Models were internally validated using a resample bootstrap technique or a split‐sample technique. Primary outcome was 6‐month mortality and unfavorable neurological outcome by the Glasgow Outcome Scale. 30‐day in‐hospital mortality was used for the trauma scoring system. Results Study populations ranged from 342 to 9915 patients. The TBI models showed the best performance with AUCs between 0.80 and 0.85, followed by the intensive care scoring systems and the CT scores with AUCs between 0.68 to 0.80 and 0.63 to 0.70, respectively. Most models showed poor calibration, although good calibration was achieved following customization. The trauma scoring system exhibited modest to good discrimination (AUC 0.76–0.89) for short‐term mortality prediction but poor calibration. Several new prognostic models, with statistically significant superior performance to previous models were created, among them a combined TBI‐ICU model (‘IMPACT‐APACHE’) and a novel CT scoring system (‘The Helsinki CT score’). Using a TBI‐specific model, based on admission characteristics, up to 40% of the patient's final long‐term outcome could be predicted. Conclusion The TBI models showed superior predictive performance to the intensive care and trauma scoring systems, showing that TBI patients are a highly specific population in the trauma and ICU setting. Thus, the use of a TBI‐specific model is advocated in the setting of TBI. The newly proposed models were found to be significant improvements over previous models, but require external validation to show generalizability.

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Update on the definition of polytrauma

Cited by 46 publications

References 43 publications

Does the applied polytrauma definition notably influence outcome and patient population? – a retrospective analysis

Does the applied polytrauma definition notably influence outcome and patient population? – a retrospective analysis

Prognostic factors in traumatic atlanto-occipital dislocation

Prognostic models in traumatic brain injury

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