Massive transfusion prediction with inclusion of the pre-hospital Shock Index

doi:10.1016/j.injury.2014.12.009

Injury

Volume 46, Issue 5, May 2015, Pages 822-826

https://doi.org/10.1016/j.injury.2014.12.009 Get rights and content

Abstract

Background

Detecting occult bleeding can be challenging and may delay resuscitation. The Shock Index (SI) defined as heart rate divided by systolic blood pressure has attracted attention. Prediction models using combinations of pre-hospital SI (phSI) and the trauma centre SI (tcSI) values may be effective in identifying patients requiring massive blood transfusions (MT).

Aim

To explore whether combinations of the phSI and the tcSI augment MT prediction.

Methods

The scores were retrospectively developed using all major trauma patients that presented to The Alfred Hospital between 2006 and 2012. The first PH and TC observations were used. To avoid exclusion of the ‘sickest’ patients, the SI was imputed to 2 where SBP was missing, but HR was present. We developed 4 models. (i) ‘Dichotomised’, defined as positive when both phSI and tcSI were ≥1. (ii) ‘Formulaic’, defined by logistic regression analysis. (iii) ‘Combination’, defined pragmatically based on the logistic regression. (iv) ‘Trending’, defined as: tcSI minus phSI.

Results

There were 6990 major trauma patients and 360 (5.2%) received MT. There were 1371 cases with either phSI or tcSI missing and were thus excluded from the analysis. The ‘Dichotomised’ had higher positive predictive value than the tcSI with a further 5 per 100 patients identified. The ‘Formulaic’ model, defined as: log Odds (MT) = 2.16 × tcSI + 0.89 × phSI − 5.42, and the ‘Combination’ model, defined as: phSI × 0.5 + tcSI, performed equally (AUROC 0.83 versus 0.83, χ² = 0.86, p = 0.35). The ‘Formulaic’ performed marginally, but statistically significantly, more accurate than the tcSI alone (AUROC 0.83 versus 0.82, χ² = 6.89, p < 0.01). An ‘Upward Trending’ SI was observed in 1758 patients, revealing a 4.6-fold univariate association with MT (OR 4.55; 95%CI 2.64–7.83), and an AUROC of 0.79 (95%CI 0.74–0.83). The ‘Downward Trending’ SI was protective against MT (OR 0.44; 95%CI 0.34–0.57).

Conclusion

The initial pre-hospital SI is associated with MT. However, this relationship did not clinically augment MT decision when combined with the in-hospital SI. The simplicity of the SI makes it a favourable option to explore further. Computer-assisted technology in data capturing, analysis and prognostication presents avenues for further research.

Section snippets

Background

Haemorrhagic shock (HS) is responsible for a third of all trauma deaths [1]. Timely diagnosis is therefore crucial, but remains challenging [2]. Diagnosis of HS relies primarily on the clinician's gestalt as traditional vital signs are commonly insufficient to diagnose HS [3]. The time-critical nature of the initial trauma resuscitation has necessitated reliance on single time-point measurements – rather than trends – that may add to delays in diagnosis and treatment of HS [4].

A key component

Setting

The state of Victoria in Australia has three Major Trauma Services (MTS) within metropolitan Melbourne, of which The Alfred Hospital is the largest. In 2008 a massive transfusion protocol (MTP) was introduced. This guideline recommended a 2:1 units ratio of Red Blood Cells (RBC) to Fresh Frozen Plasma (FFP), and 4:1 units of RBCs and leucocyte depleted platelets. Each unit of RBC has an average volume of 260 (SD 19) mL, each unit of FFP has an average volume of 280 (14) mL, and each unit of

Results

There were 6990 major trauma patients and 360 (5.2%) received MT. The mean age of the total cohort was 47.4 (21.9) years. The median ISS was 24 (17–29), and the overall mortality at hospital discharge was 9.7%. Blunt mechanism of injury was commonest (93.8%), whilst penetrating mechanisms only accounted for 2.5%. The remaining injuries comprised burns and ‘unknown’. Demographics, initial vital signs and initial pathology results are presented in Table 2.

The phSI was available in 5694 cases, of

Discussion

This study demonstrated statistically significant improvements in prediction of MT by incorporating pre-hospital SI. The ‘Combination’ SI, defined as: 0.5 × phSI + tcSI, was only marginally more accurate than tcSI alone, thus of limited clinical significance. Regardless of in-hospital values, this study demonstrated an association between phSI and subsequent in-hospital MT and highlights the potential utility of early, pre-hospital variables to predict MT.

Improved prediction of haemorrhage

Conclusion

The initial pre-hospital SI is associated with in-hospital massive transfusion. However, pre-hospital objective measures of haemorrhagic shock did not clinically augment massive transfusion decision when combined with in-hospital values. The simplicity and absence of pathology, radiology or other resources make the SI a favourable option to explore further. Adding further time points and continuing real-time computer assisted predictive models throughout the patient's journey may improve

Conflict of interest

None.

References (32)

H.R. Guly et al.
Vital signs and estimated blood loss in patients with major trauma: testing the validity of the ATLS classification of hypovolaemic shock
Resuscitation
(2011)
B. Mitra et al.
Massive blood transfusion and trauma resuscitation
Injury
(2007)
K. Sisak et al.
Acute transfusion practice during trauma resuscitation: who, when, where and why?
Injury
(2013)
J.S. McKinney et al.
Hospital prenotification of stroke patients by emergency medical services improves stroke time targets
J Stroke Cerebrovasc Dis
(2013)
B. Mitra et al.
Acute coagulopathy and early deaths post major trauma
Injury
(2012)
D.S. Kauvar et al.
Impact of hemorrhage on trauma outcome: an overview of epidemiology, clinical presentations, and therapeutic considerations
J Trauma
(2006)
T. Brockamp et al.
Predicting on-going hemorrhage and transfusion requirement after severe trauma: a validation of six scoring systems and algorithms on the TraumaRegister DGU(R)
Crit Care
(2012)
H.C. Tien et al.
Preventable deaths from hemorrhage at a level I Canadian trauma center
J Trauma
(2007)
S. Burman et al.
Trauma patients at risk for massive transfusion: the role of scoring systems and the impact of early identification on patient outcomes
Expert Rev Hematol
(2012)
L.J. Morrison et al.
Prehospital 12-lead electrocardiography impact on acute myocardial infarction treatment times and mortality: a systematic review
Acad Emerg Med.
(2006)

R. Pacagnella et al.

A systematic review of the relationship between blood loss and clinical signs

PLoS ONE

(2013)

A. Olaussen et al.

Review article: shock index for prediction of critical bleeding post-trauma: a systematic review

Emerg Med Australas

(2014)

M.J. Vandromme et al.

Identifying risk for massive transfusion in the relatively normotensive patient: utility of the prehospital shock index

J Trauma

(2011)

A. Zatta et al.

Elucidating the clinical characteristics of patients captured using different definitions of massive transfusion

Vox Sang

(2014)

B. Mitra et al.

The definition of massive transfusion in trauma: a critical variable in examining evidence for resuscitation

Eur J Emerg Med

(2011)

M. Mutschler et al.

The shock index revisited – a fast guide to transfusion requirement? A retrospective analysis on 21,853 patients derived from the TraumaRegister DGU(R)

Crit Care

(2013)

Cited by (44)

Effectiveness of massive transfusion protocol activation in pre-hospital setting for major trauma
2022, Injury
Citation Excerpt :
Before transfusion, nurses take a blood sample for the typing of red blood cells, then blood products are administered directly in the ED. The choice of the 2:1:1 ratio (PRBCs:FFP:PLT) for the “first pack” is borrowed from the analysis of previous studies [20,38–40], and the administration of FFP aims to reduce the ACT [14]. This study also aimed to analyze if the pre-hospital activations of MTP were confirmed upon admission to the ED, and if the inclusion criteria were effective in identifying the patients requiring massive transfusions.
Hemorrhage in major trauma is life-threatening and the activation of the Massive Transfusion Protocol (MTP) was found to reduce the time to transfusion and mortality. The purpose was (i) to verify whether MTP activation identifies patients that require massive transfusions once admitted to the Emergency Department (ED), (ii) to establish whether pre-hospital MTP activation reduces the time to transfusion on arrival at the ED, (iii) to identify the variable that best predicts MTP activation.
This is a retrospective, single-center study. The MTP was implemented at the end of 2012; it was activated for major trauma in pre-hospital setting on the basis on established criteria. Pre-hospital MTP activation aimed to make blood products available prior to the patients’ arrival at the ED. The blood products are transfused when the patient arrives at the hospital.
The MTP was activated in pre-hospital setting in 219 patients. On arrival at the hospital, the Trauma Team Leader confirmed MTP activation in 146 (66.7%) patients. Patients with MTP criteria received a higher amount of blood products than the patients without MTP criteria, median 7 (IQR 2–13) units versus 2 (0–6) units, respectively (P < 0.001). At the same time, patients with a Shock Index ≥ 0.9 received more transfusions (5.5 [2–13] units) compared with patients characterized by a lower SI (2 [0–7.25] units, P = 0.009). 146 patients were transfused in the first hour of ED admission. Poisson's multiple regression shows that the SI is the variable that better predicted MTP activation compared to age, gender and the number of injured sites.
Pre-hospital MTP activation is useful to identify patients that require an urgent blood transfusion on arrival at the ED. Further analysis should be considered to evaluate the implementation of the Shock Index as a criterion to activate MTP.
Blunt Trauma Massive Transfusion (B-MaT) Score: A Novel Scoring Tool
2022, Journal of Surgical Research
Citation Excerpt :
We observed a MT rate of 0.7% which is lower than most other studies, however this may be expected as this study focuses on blunt trauma patients.7-14, 32 Next, the definition of MT is rather controversial and differs between studies.2, 14, 30, 32, 35-36 This study used a combination of the traditional definition and a shorter time frame (≥ 10 units of PRBCs within 24 hours or ≥ 6 units of PRBCs transfused within 4 hours), though an alternative definition may have yielded different results.
Multiple tools predicting massive transfusion (MT) in trauma have been developed but utilize variables that are not immediately available. Additionally, they only differentiate blunt from penetrating trauma and do not account for the large range of blunt mechanisms and their difference in force. We aimed to develop a Blunt trauma Massive Transfusion (B-MaT) score that accounts for high-risk blunt mechanisms and predicts MT needs in blunt trauma patients (BTPs) prior to arrival.
The adult 2017 Trauma Quality Improvement Program database was used to identify BTPs who were divided into 2 sets at random (derivation/validation). First, multiple logistic regression models were created to determine risk factors of MT (≥6 units of PRBCs within 4-hours or ≥10 units within 24-hours). Next, the weighted average and relative impact of each independent predictor was used to derive a B-MaT score. Finally, the area under the receiver-operating curve (AROC) was calculated.
Of 172,423 patients in the derivation-set, 1,160 (0.7%) required MT. Heart rate ≥ 120bpm, systolic blood pressure ≤ 90mmHg, and high-risk blunt mechanisms were identified as independent predictors for MT. B-MaT scores were derived ranging from 0 –9, with scores of 6, 7, and 9 yielding a MT rate of 11.7%, 19.4%, and 32.4%, respectively. The AROC was 0.86. The validation-set had an AROC of 0.85.
B-MaT is a novel scoring tool that predicts need for MT in BTPs and can be calculated prior to arrival. B-MaT warrants prospective validation to confirm its accuracy and assess its ability to improve patient outcomes and blood product allocation.
Pre-hospital modified shock index for prediction of massive transfusion and mortality in trauma patients
2020, American Journal of Emergency Medicine
Citation Excerpt :
However, SI and MSI are simple and quick to calculate, so they are well-suited for use in the pre-hospital stage. Previous studies have evaluated the utility of preSI in trauma patients [6,10,12,13,22]. These studies found that preSI was a useful predictor for MT, hospital resource use, mortality, and major hemorrhage.
Modified shock index (MSI) is a useful predictor in trauma patients. However, the value of prehospital MSI (preMSI) in trauma patients is unknown. The aim of this study was to investigate the accuracy of preMSI in predicting massive transfusion (MT) and hospital mortality among trauma patients.
This was a retrospective, observational, single-center study. Patients presenting consecutively to the trauma center between January 2016 and December 2017, were included. The predictive ability of both prehospital shock index (preSI) and preMSI for MT and hospital mortality was assessed by calculating the areas under the receiver operating characteristic curves (AUROCs).
A total of 1007 patients were included. Seventy-eight (7.7%) patients received MT, and 30 (3.0%) patients died within 24 h of admission to the trauma center. The AUROCs for predicting MT with preSI and preMSI were 0.773 (95% confidence interval [CI], 0.746–0.798) and 0.765 (95% CI, 0.738–0.791), respectively. The AUROCs for predicting 24-hour mortality with preSI and preMSI were 0.584 (95% CI, 0.553–0.615) and 0.581 (95% CI, 0.550–0.612), respectively.
PreSI and preMSI showed moderate accuracy in predicting MT. PreMSI did not have higher predictive power than preSI. Additionally, in predicting hospital mortality, preMSI was not superior to preSI.
Pre-hospital shock index correlates with transfusion, resource utilization and mortality; The role of patient first vitals
2019, American Journal of Surgery
The aim of our study was to evaluate if pre-hospital shock index (SI) can predict transfusion requirements, resource utilization and mortality in trauma patients.
We performed a 2-year analysis of all adult trauma patients in the TQIP database. Shock index was calculated by dividing heart-rate over systolic blood pressure. Patients were divided into two groups pre-hospital SI ≤ 1 and prehospital SI > 1. Regression and ROC curve analyses were performed.
144951 patients were included in the study. Mean age was 45 ± 34 years, 61% were male, 84.7% had blunt injuries and median ISS was 13 [9–17]. Overall 9.1% of the patients had a pre-hospital SI > 1. Patients with pre-hospital SI > 1 had higher likelihood of requiring massive transfusion (25% vs. 0.012%, p < 0.02), interventional-radiology intervention (6.2% vs. 1%,p < 0.001) or operative intervention (14.7% vs. 2%,p < 0.001) compared to SI ≤ 1. Similarly, patients with SI > 1 had higher mortality (12.3% vs. 5.2%, p < 0.001) and were more likely to be discharged to Rehab/SNF (34.6% vs. 21.4%, p < 0.001).
Pre-hospital SI predicts trauma-center resource utilization and can guide patient triage and trauma resource recruitment.
Whole Blood in Trauma: A Review for Emergency Clinicians
2019, Journal of Emergency Medicine
Citation Excerpt :
They include blood pressure, heart rate, and end-tidal carbon dioxide parameters. These are based on previous trials showing that the initial prehospital shock index values of 1.0 and 1.2 were associated with the need for massive transfusion (48,49). Studies also show that low end-tidal carbon dioxide has a strong association with standard indicators for shock and is predictive of patients requiring operative intervention (50,51).
Blood products are a cornerstone of trauma resuscitation. From the historically distant battlefields of World War II through present-day conflict around the globe, whole blood (WB) has been a potent tool in the treatment of massive hemorrhagic shock. Component therapy with a targeted ratio of packed red blood cells, platelets, and plasma has previously been utilized.
This narrative review describes modern-day WB transfusion, its benefits, potential drawbacks, and implementation.
The current form of stored low-titer O WB seems to be the safest and most effective solution. There are many advantages to WB, including the maintenance of coagulation factors, the lack of subsequent thrombocytopenia, and the reduction of infused anticoagulant. Several studies suggest its utility in trauma. Most of the disadvantages of WB stem from a lack of prospective data on the topic, which are likely forthcoming. Logistical issues likely present the greatest barrier to this therapy, but an advanced prehospital protocol developed in San Antonio, Texas, has successfully overcome several of these challenges.
Although stored WB holds promise, it is not without its distinct challenges, including logistical issues, which this article addresses. There are programs underway currently that demonstrate its feasibility in metropolitan areas. As demonstrated in military settings, WB is likely the ideal resuscitation fluid for civilian trauma in the prehospital and emergency department settings.
Prediction of massive bleeding in a prehospital setting: validation of six scoring systems
2019, Medicina Intensiva
Validar a nivel extrahospitalario la capacidad diagnóstica de seis escalas de predicción para hemorragia masiva.
Cohorte retrospectiva.
Atención extrahospitalaria del paciente con enfermedad traumática grave.
Pacientes mayores de 15 años, que han sufrido un trauma grave (definido por los criterios de código 15), atendidos en el medio extrahospitalario por un servicio de atención sanitaria de emergencias desde enero de 2010 hasta diciembre de 2015 y trasladados a un centro hospitalario de alta complejidad en Madrid.
Se validaron las siguientes escalas: 1. Trauma Associated Severe Haemorrhage score. 2. Assessment of Blood Consumption Score. 3. Emergency Transfusion Score. 4. Índice de Shock. 5. Prince of Wales Hospital/Rainer Score. 6. Larson Score.
Se estudiaron 548 pacientes, el 76,8% (420) fueron hombres, una edad mediana de 38 (rango intercuartil [RIC]: 27-50). Injury Severity Score de 18 (RIC: 9-29). El trauma cerrado fue el 82,5% (452). La frecuencia global de HM fue de 9,2% (48), días de estancia en UCI de 2,1 (RIC: 0,8 - 6,2) y una mortalidad hospitalaria del 11,2% (59). La escala con mayor precisión fue la Emergency Transfusion Score (AUC 0,85), en segundo lugar se encuentran Trauma Associated Severe Haemorrhage y Prince of Wales Hospital/Rainer (AUC 0,82); la escala con menor precisión Assessment of Blood Consumption (AUC 0,68).
A nivel extrahospitalario la aplicación de cualquiera de las seis escalas predice la presencia de hemorragia masiva y permite la activación de los protocolos de transfusión masiva mientras el paciente es trasladado a un centro hospitalario.
To validate the diagnostic ability of six different scores to predict massive bleeding in a prehospital setting.
Retrospective cohort.
Prehospital attention of patients with severe trauma.
Subjects with more than 15 years, a history of severe trauma (defined by code 15 criteria), that were initially assisted in a prehospital setting by the emergency services between January 2010 and December 2015 and were then transferred to a level one trauma center in Madrid.
To validate: 1. Trauma Associated Severe Haemorrhage Score. 2. Assessment of Blood Consumption Score. 3. Emergency Transfusión Score. 4. Índice de Shock. 5. Prince of Wales Hospital/Rainer Score. 6. Larson Score.
548 subjects were studied, 76,8% (420) were male, median age was 38 (interquartile range [IQR]: 27-50). Injury Severity Score was 18 (IQR: 9-29). Blunt trauma represented 82,5% (452) of the cases. Overall, frequency of MB was 9,2% (48), median intensive care unit admission days was 2,1 (IQR: 0,8 - 6,2) and hospital mortality rate was 11,2% (59). Emergency Transfusión Score had the highest precisions (AUC 0,85), followed by Trauma Associated Severe Haemorrhage score and Prince of Wales Hospital/Rainer Score (AUC 0,82); Assessment of Blood Consumption Score was the less precise (AUC 0,68).
In the prehospital setting the application of any the six scoring systems predicts the presence of massive hemorrhage and allows the activation of massive transfusion protocols while the patient is transferred to a hospital.

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Massive transfusion prediction with inclusion of the pre-hospital Shock Index

Abstract

Background

Aim

Methods

Results

Conclusion

Section snippets

Background

Setting

Results

Discussion

Conclusion

Conflict of interest

Resuscitation

Injury

Injury

J Stroke Cerebrovasc Dis

Injury

Impact of hemorrhage on trauma outcome: an overview of epidemiology, clinical presentations, and therapeutic considerations

J Trauma

Predicting on-going hemorrhage and transfusion requirement after severe trauma: a validation of six scoring systems and algorithms on the TraumaRegister DGU(R)

Crit Care

Preventable deaths from hemorrhage at a level I Canadian trauma center

J Trauma

Trauma patients at risk for massive transfusion: the role of scoring systems and the impact of early identification on patient outcomes

Expert Rev Hematol

Prehospital 12-lead electrocardiography impact on acute myocardial infarction treatment times and mortality: a systematic review

Acad Emerg Med.

A systematic review of the relationship between blood loss and clinical signs

PLoS ONE

Review article: shock index for prediction of critical bleeding post-trauma: a systematic review

Emerg Med Australas

Identifying risk for massive transfusion in the relatively normotensive patient: utility of the prehospital shock index

J Trauma

Elucidating the clinical characteristics of patients captured using different definitions of massive transfusion

Vox Sang

The definition of massive transfusion in trauma: a critical variable in examining evidence for resuscitation

Eur J Emerg Med

The shock index revisited – a fast guide to transfusion requirement? A retrospective analysis on 21,853 patients derived from the TraumaRegister DGU(R)

Crit Care