Predicting Early Death in Patients With Traumatic Bleeding
Predicting Early Death in Patients With Traumatic Bleeding
Objective To develop and validate a prognostic model for early death in patients with traumatic bleeding.
Design Multivariable logistic regression of a large international cohort of trauma patients.
Setting 274 hospitals in 40 high, medium, and low income countries
Participants Prognostic model development: 20,127 trauma patients with, or at risk of, significant bleeding, within 8 hours of injury in the Clinical Randomisation of an Antifibrinolytic in Significant Haemorrhage (CRASH-2) trial. External validation: 14,220 selected trauma patients from the Trauma Audit and Research Network (TARN), which included mainly patients from the UK.
Outcomes In-hospital death within 4 weeks of injury.
Results 3076 (15%) patients died in the CRASH-2 trial and 1765 (12%) in the TARN dataset. Glasgow coma score, age, and systolic blood pressure were the strongest predictors of mortality. Other predictors included in the final model were geographical region (low, middle, or high income country), heart rate, time since injury, and type of injury. Discrimination and calibration were satisfactory, with C statistics above 0.80 in both CRASH-2 and TARN. A simple chart was constructed to readily provide the probability of death at the point of care, and a web based calculator is available for a more detailed risk assessment (http://crash2.lshtm.ac.uk).
Conclusions This prognostic model can be used to obtain valid predictions of mortality in patients with traumatic bleeding, assisting in triage and potentially shortening the time to diagnostic and lifesaving procedures (such as imaging, surgery, and tranexamic acid). Age is an important prognostic factor, and this is of particular relevance in high income countries with an aging trauma population.
Each year around 4 million people die worldwide from unintentional injury and violence, and tens of millions are left permanently disabled. Most of the victims are from low and middle income countries. Although many of these deaths occur at the scene of the injury, 44% are estimated to occur after admission to hospital.
Severe bleeding accounts for about one third of in-hospital deaths due to trauma and is an important contributory factor for other causes of death, particularly head injury and multi-organ failure. Failure to start appropriate early management in bleeding trauma patients is a leading cause of preventable death from trauma. Triage criteria that allow the rapid identification of patients at high risk have the potential to reduce mortality from trauma. Recent evidence that the early administration of tranexamic acid substantially reduces mortality in bleeding trauma patients further underscores the clinical importance of the timely identification of life threatening bleeding. However, any such early prediction would have to be based on variables that can be readily measured soon after injury. Several clinical variables related to the physiological response to reduced intravascular volume predict the risk of death in bleeding trauma patients. These include blood pressure, capillary refill time, level of consciousness (Glasgow coma score), heart rate, and respiratory rate. Because all of these variables are of limited predictive value when considered in isolation, prognostic models that combine variables are needed for better predictive accuracy. An accurate and user friendly prognostic model to predict mortality in patients with traumatic bleeding could assist doctors and paramedics in pre-hospital triage, whether in civilian or battlefield settings; its use could shorten the time to diagnostic and lifesaving procedures (such as surgery and tranexamic acid). We have previously published a prognostic model for patients with traumatic brain injury, which was accurate, user friendly, and clinically useful for supporting physicians’ decision making.
Existing prognostic models for bleeding trauma patients are limited. Most were developed using data collected many decades ago and have methodological limitations. Models based on contemporary data are needed, as treatment practices have changed and the age of trauma patients has increased in high income countries. Furthermore, although most deaths due to trauma occur in low and middle income countries, most prognostic models are based on data from high income countries. We aimed to develop a simple prognostic model that could be used at the point of care to estimate risk of death in patients with traumatic bleeding.
Abstract and Introduction
Abstract
Objective To develop and validate a prognostic model for early death in patients with traumatic bleeding.
Design Multivariable logistic regression of a large international cohort of trauma patients.
Setting 274 hospitals in 40 high, medium, and low income countries
Participants Prognostic model development: 20,127 trauma patients with, or at risk of, significant bleeding, within 8 hours of injury in the Clinical Randomisation of an Antifibrinolytic in Significant Haemorrhage (CRASH-2) trial. External validation: 14,220 selected trauma patients from the Trauma Audit and Research Network (TARN), which included mainly patients from the UK.
Outcomes In-hospital death within 4 weeks of injury.
Results 3076 (15%) patients died in the CRASH-2 trial and 1765 (12%) in the TARN dataset. Glasgow coma score, age, and systolic blood pressure were the strongest predictors of mortality. Other predictors included in the final model were geographical region (low, middle, or high income country), heart rate, time since injury, and type of injury. Discrimination and calibration were satisfactory, with C statistics above 0.80 in both CRASH-2 and TARN. A simple chart was constructed to readily provide the probability of death at the point of care, and a web based calculator is available for a more detailed risk assessment (http://crash2.lshtm.ac.uk).
Conclusions This prognostic model can be used to obtain valid predictions of mortality in patients with traumatic bleeding, assisting in triage and potentially shortening the time to diagnostic and lifesaving procedures (such as imaging, surgery, and tranexamic acid). Age is an important prognostic factor, and this is of particular relevance in high income countries with an aging trauma population.
Introduction
Each year around 4 million people die worldwide from unintentional injury and violence, and tens of millions are left permanently disabled. Most of the victims are from low and middle income countries. Although many of these deaths occur at the scene of the injury, 44% are estimated to occur after admission to hospital.
Severe bleeding accounts for about one third of in-hospital deaths due to trauma and is an important contributory factor for other causes of death, particularly head injury and multi-organ failure. Failure to start appropriate early management in bleeding trauma patients is a leading cause of preventable death from trauma. Triage criteria that allow the rapid identification of patients at high risk have the potential to reduce mortality from trauma. Recent evidence that the early administration of tranexamic acid substantially reduces mortality in bleeding trauma patients further underscores the clinical importance of the timely identification of life threatening bleeding. However, any such early prediction would have to be based on variables that can be readily measured soon after injury. Several clinical variables related to the physiological response to reduced intravascular volume predict the risk of death in bleeding trauma patients. These include blood pressure, capillary refill time, level of consciousness (Glasgow coma score), heart rate, and respiratory rate. Because all of these variables are of limited predictive value when considered in isolation, prognostic models that combine variables are needed for better predictive accuracy. An accurate and user friendly prognostic model to predict mortality in patients with traumatic bleeding could assist doctors and paramedics in pre-hospital triage, whether in civilian or battlefield settings; its use could shorten the time to diagnostic and lifesaving procedures (such as surgery and tranexamic acid). We have previously published a prognostic model for patients with traumatic brain injury, which was accurate, user friendly, and clinically useful for supporting physicians’ decision making.
Existing prognostic models for bleeding trauma patients are limited. Most were developed using data collected many decades ago and have methodological limitations. Models based on contemporary data are needed, as treatment practices have changed and the age of trauma patients has increased in high income countries. Furthermore, although most deaths due to trauma occur in low and middle income countries, most prognostic models are based on data from high income countries. We aimed to develop a simple prognostic model that could be used at the point of care to estimate risk of death in patients with traumatic bleeding.
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