Development of a new score for early mortality prediction in trauma ICU patients: RETRASCORE

Severe trauma remains the leading cause of mortality and disability in young adults [1]. In this setting, trauma registries provide relevant information in terms of benchmarking of the care provided and, therefore, constitute a relevant contribution to quality assessment and scientific research in an area where classical randomized trials are difficult to perform [2‐4]. To this purpose, the Injury Severity Score (ISS) has been the most commonly used score to assess severity of trauma [5]. Several years later, the Trauma and Injury Severity Score (TRISS) became the most frequently used tool for outcome adjustment and benchmarking in worldwide trauma registries [6].

More recently, The TraumaRegister DGU™ (TR-DGU) developed the Revised Injury Severity Classification (RISC) score [7] and its updated version in 2014 [8] for outcome adjustment, achieving an astonishing AUC 0.95 in the derivation and validation datasets in terms of mortality prediction, with appropriate precision and calibration [8]. However, these scores can be applied to the general trauma patients and, therefore, are not specific for the trauma ICU patients, in whom the physiological consequences of trauma itself play a major role in outcomes. Indeed, intensive care units (ICUs) commonly use severity scores such as the Acute Physiology and Chronic Health Evaluation (APACHE II), the Simplified Acute Physiologic Score (SAPS II) or the Mortality Probability Models (MPM II), which take into consideration age, comorbidities and the physiological burden of critical illness rather than anatomic considerations [9].

This is a retrospective study that aims to develop and validate a mortality prognostic model with variables included in the RETRAUCI project. RETRAUCI is an observational, prospective and multicentre nationwide registry that currently includes 52 ICUs in Spain. It has the endorsement of the Neurointensive Care and Trauma Working Group of the Spanish Society of Intensive Care Medicine (SEMICYUC) and currently operates in a web-based electronic format (www.​retrauci.​org). Additional file 1 shows the screenshots of the web application and the list of variables collected in RETRAUCI. The records for the years 2015–2019 were used. To achieve internal validation, the total records were divided into two sets: derivation set (2015–2017) and validation set (2018–2019). It is a study with complete-case analysis with temporal validation. The development of the models was carried out following the recommendations established in the Transparency Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) initiative [10].

Ethics Committee approval for the registry was obtained (Hospital Universitario 12 de Octubre, Madrid: 12/209). Due to the retrospective analysis of de-identified collected data, informed consent was not obtained for this study.

The study group included a total of 9465 patients with complete data who were divided into a derivation set with 5976 patients and a validation set with 3489 patients. Additional file 2: Figure S1 shows the flowchart of the study. Thirty-day mortality reached 12.2%. Table 1 shows the variables potentially associated with mortality selected from the RETRAUCI database, differentiating between the derivation and validation sets. The only significant differences found in the validation set were a higher percentage of pre-hospital medical attentions (80.1 vs. 76.1%), a higher proportion of assaults (6.0 vs. 4.3%) and a lower need of mechanical ventilation (49.8 vs. 45.9%).

The appropriate use of trauma scoring is of paramount importance in terms of outcome adjustment and benchmarking of the care provided [20]. The ideal score for stratifying the risk of death in the trauma ICU should be performed early, must be easy-to-calculate and include specific factors derived from the intensive care management of critical trauma patients. However, classical trauma-specific scoring systems (ISS, RTS, TRISS) are still used with a poor calibration and discrimination capacity, and their performance is lower than that obtained by general ICU scores where anatomical injuries caused by trauma are not considered [21, 22], raising the need of specific trauma ICU scores that take into consideration early anatomic consideration but also pre-hospital care, physiological derangements, organ failures and treatments provided. We believe that the model presented meets these expectations [23].

Different types of variables were finally included in our model, according to its relationship with mortality in conventional models.

Non-modifiable factors depending on the patient were age and the prior treatment of antiplatelet/anticoagulant therapy. Age is a critical factor in the outcomes of trauma patients, as mortality increases with age [8, 24]. On the other side, prior treatment with antiplatelets/anticoagulants contributes to the size and burden of traumatic injuries, especially in patients with traumatic brain injury (TBI) [11].

In our model, two variables related to the pre-hospital care were included, the type of attention with trained medical attention specialized in advanced resuscitation techniques and the need of pre-hospital intubation [25, 26]. These factors are closely related to the quality of a mature trauma system in each country. We also considered type and intentionality of trauma. We grouped different mechanisms into a single one variable associated with high mortality including pedestrian falls, suicidal high-energy falls, firearms injuries and unknown mechanisms [27, 28]. These are well-known mechanisms associated with higher mortality. For the purpose of an external validation of our score, it would be especially important to check how this variable performs.

TBI is the leading cause of mortality in the trauma ICU in our environment. Therefore, it is not surprising that three neurological factors were finally included in our model. All of them are well-known clinical factors related to outcomes: pupillary reactivity, which is easy to determine and carries an important weight in TBI [8, 29], GCS ≤ 8 and the anatomical burden of head injury evaluated by the AIS [8].

Additionally, haemodynamic instability, respiratory failure and trauma-induced coagulopathy in patients with critical bleeding are associated with a worst prognosis and were also present in our model [13, 14, 30, 31].

The need for MV is an indicator of severity in critical trauma patients. It does not only potentially express respiratory failure, but also neurological or haemodynamic involvement or the need of procedures that require sedation.

We observed that severe chest trauma was a protective factor of trauma ICU patients. This intriguing result merits further investigation since the real contribution of chest trauma to the mortality of severe trauma patients is still a matter of debate [32]. Approximately 600 patients were admitted to the participating ICUs with severe chest trauma and without other major injuries, and most of these patients received pain control, had early physiotherapy and had a good outcome. Likely, this is the reason why severe chest trauma received a score of − 1 in the RETRASCORE model.

Taking together these variables, our easy-to-calculate and specific trauma ICU score achieves an excellent performance in terms of mortality prediction with an AUROC of almost 0.93 in the validation dataset. This is very close to the astonishing predictive ability of the RISC-II updated score, but ours is specific to the trauma ICU patients and is easier to use since it does not include data on pre-trauma ASA status, base deficit, haemoglobin and cardiopulmonary resuscitation [8]. Instead, it uses common clinical conditions such as respiratory failure or trauma-induced coagulopathy that reflect the physiological response to trauma based on predefined definitions. In this line, our score should be also confronted with general ICU scores. Magee et al. recently compared general ICU scores with traditional trauma scores and observed an improved performance of general ICU scores evaluating physiological derangements in the initial 24 h over anatomical scores [20]. Due to the increasing age of trauma populations who carry on additional comorbidities, we believe that scores like ours combining anatomical injuries and physiological derangements in the initial 24 h will improve our early prediction ability, especially in different subgroups of trauma patients [21].

We expect our score to be further externally validated in different databases allowing additional comparison with general ICU scores.

Our study presents some limitations:

First, the most important limitation is the lack of an external validation. This must be performed before the score can be applied in daily clinical practice. Second, the inclusion criteria of being admitted to the participating ICUs may not appropriately reflect the critical trauma population due to differences in admission criteria and bed and staffing availability. Third, unless patients were managed following the Advanced Trauma Life Support principles, we cannot rule out deviations so this could affect patients’ management and therefore outcomes [22]. Fourth, we have only used the TRISS as a comparison model; RETRASCORE should be compared with other scores, both specific to trauma patients and of a general type. Fifth, if a random partition had been made of the derivation and validation groups, no differences would have been found between the sets; we chose a temporary partition since we had a sufficiently large sample that could provide us with a temporal validation [10]. Finally, machine learning techniques have been used in our environment to predict outcome [33], but in this study, our objective was to develop a simple and early, easy-to-calculate and specific trauma ICU score rather than using complex methodologies.

In conclusion, the newly developed RETRASCORE is an early, easy-to-calculate and specific score to predict in-hospital mortality in trauma ICU patients. This is the first trauma score specifically designed for the trauma ICU population. Although it has achieved adequate internal validation, it must be externally validated.