Early identification of uncontrolled hemorrhage after trauma: Current status and future direction

Non-invasive biomarkers for detecting progression toward hypovolemic cardiovascular instability in a lower body negative pressure model

Occult hemorrhages after trauma can be present insidiously, and if not detected early enough can result in patient death. This study evaluated a hemorrhage model on 18 human subjects, comparing the performance of traditional vital signs to multiple off-the-shelf non-invasive biomarkers. A validated lower body negative pressure (LBNP) model was used to induce progression towards hypovolemic cardiovascular instability. Traditional vital signs included mean arterial pressure (MAP), electrocardiography (ECG), plethysmography (Pleth), and the test systems utilized electrical impedance via commercial electrical impedance tomography (EIT) and multifrequency electrical impedance spectroscopy (EIS) devices. Absolute and relative metrics were used to evaluate the performance in addition to machine learning-based modeling. Relative EIT-based metrics measured on the thorax outperformed vital sign metrics (MAP, ECG, and Pleth) achieving an area-under-the-curve (AUC) of 0.99 (CI 0.95-1.00, 100% sensitivity, 87.5% specificity) at the smallest LBNP change (0-15 mmHg). The best vital sign metric (MAP) at this LBNP change yielded an AUC of 0.6 (CI 0.38-0.79, 100% sensitivity, 25% specificity). Out-of-sample predictive performance from machine learning models were strong, especially when combining signals from multiple technologies simultaneously. EIT, alone or in machine learning-based combination, appears promising as a technology for early detection of progression toward hemodynamic instability.

Detection of subclinical hemorrhage using electrical impedance: a porcine study

OBJECTIVE

Analyze the performance of electrical impedance tomography (EIT) in an innovative porcine model of subclinical hemorrhage and investigate associations between EIT and hemodynamic trends.

APPROACH

Twenty-five swine were bled at slow rates to create an extended period of subclinical hemorrhage during which the animal's heart rate (HR) and blood pressure (BP) remained stable from before hemodynamic deterioration, where stable was defined as < 15% decrease in BP and < 20% increase in HR - i.e. hemorrhages were hidden from standard vital signs of HR and BP. Continuous vital signs, photo-plethysmography, and continuous non-invasive EIT data were recorded and analyzed with the objective of developing an improved means of detecting subclinical hemorrhage - ideally as early as possible.

MAIN RESULTS

Best area-under-the-curve (AUC) values from comparing bleed to no-bleed epochs were 0.96 at a 80 ml bleed (~15.4 minutes) using an EIT-data-based metric and 0.79 at a 120 ml bleed (~23.1 minutes) from invasively measured BP - i.e. the EIT-data-based metric achieved higher AUCs at earlier points compared to standard clinical metrics without requiring image reconstructions.

SIGNIFICANCE

In this clinically relevant porcine model of subclinical hemorrhage, EIT appears to be superior to standard clinical metrics in early detection of hemorrhage.

Efficacy and Safety of Low Molecular Weight Heparin Versus Unfractionated Heparin for Prevention of Venous Thromboembolism in Trauma Patients: A Systematic Review and Meta-analysis

PURPOSE

Trauma patients are at high risk of VTE. We summarize the efficacy and safety of LMWH versus UFH for the prevention of VTE in trauma patients.

METHODS

We searched 6 databases from inception through March 12, 2021. We included randomized controlled trials (RCTs) or observational studies comparing LMWH versus UFH for thromboprophylaxis in adult trauma patients. We pooled effect estimates across RCTs and observational studies separately, using random-effects model and inverse variance weighting. We assessed risk of bias using the Cochrane tool for RCTs and the Risk of Bias in Non-Randomized Studies (ROBINS)-I tool for observational studies and assessed certainty of findings using Grading of Recommendations, Assessment, Development and Evaluations methodology.

RESULTS

We included 4 RCTs (879 patients) and 8 observational studies (306,747 patients). Based on pooled RCT data, compared to UFH, LMWH reduces deep vein thrombosis (RR 0.67, 95% CI 0.50 to 0.88, moderate certainty) and VTE (RR 0.68, 95% CI 0.51 to 0.90, moderate certainty). As compared to UFH, LMWH may reduce pulmonary embolism [adjusted odds ratio from pooled observational studies 0.56 (95% CI 0.50 to 0.62)] and mortality (adjusted odds ratio from pooled observational studies 0.54, 95% CI 0.45 to 0.65), though based on low certainty evidence. There was an uncertain effect on adverse events (RR from pooled RCTs 0.80, 95% CI 0.48 to 1.33, very low certainty) and heparin induced thrombocytopenia [RR from pooled RCTs 0.26 (95% CI 0.03 to 2.38, very low certainty)].

CONCLUSIONS

Among adult trauma patients, LMWH is superior to UFH for deep vein thrombosis and VTE prevention and may additionally reduce pulmonary embolism and mortality. The impact on adverse events and heparin induced thrombocytopenia is uncertain.

Utilization and Efficacy of Resuscitation Endpoints in Trauma and Burn Patients: A Review Article

Shock is a sequelae in trauma and burn patients that substantially increases the risk for morbidity and mortality. The use of resuscitation endpoints allows for improved management of these patients, with the potential to prevent further morbidity/mortality. We conducted a review of the current literature on the efficacy of hemodynamic, metabolic, and regional resuscitation endpoints for use in trauma and burn patients. Hemodynamic endpoints included mean arterial pressure (MAP), heart rate (HR), urinary output (UO), compensatory reserve index (CRI), intrathoracic blood volume, and stroke volume variation (SVV). Metabolic endpoints measure cellular responses to decreased oxygen delivery and include serum lactic acid (LA), base deficit (BD), bicarbonate, anion gap, apparent strong ion difference, and serum pH. Mean arterial pressure, HR, UO, and LA are the most established markers of trauma and burn resuscitation. The evidence suggests LA is a superior metabolic endpoint marker. Newer resuscitation endpoint technologies such as point-of-care ultrasound (PoCUS), thromboelastography (TEG), and rotational thromboelastometry (ROTEM) may improve patient outcomes; however, additional research is needed to establish the efficacy in trauma and burn patients. The endpoints discussed have situational strengths and weaknesses and no single universal resuscitation endpoint has yet emerged. This review may increase knowledge and aid in guideline development. We recommend clinicians continue to integrate multiple endpoints with emphasis on MAP, HR, UO, LA, and BD. Future investigation should aim to standardize endpoints for each clinical presentation. The search for universal and novel resuscitation parameters in trauma and burns should also continue.

Thrombin Generation Kinetics are Predictive of Rapid Transfusion in Trauma Patients Meeting Critical Administration Threshold

INTRODUCTION

We hypothesize that a patient (pt) with accelerated thrombin generation, time to peak height (ttPeak), will have a greater odds of meeting critical administration threshold (CAT) criteria (> 3 packed red blood cell [pRBC] transfusions [Tx] per 60 min interval), within the first 24 h after injury, independent of international normalized ratio (INR).

METHODS

In a prospective cohort study, trauma patients were enrolled over a 4.5-year period and serial blood samples collected at various time points. We retrospectively stratified pts into three categories: CAT+, CAT- but receiving some pRBC Tx, receiving no Tx within the first 24 h. Blood collected prior to Tx was analyzed for thrombin generation parameters and prothrombin time (PT)/INR.

RESULTS

A total of 484 trauma pts were analyzed: injury severity score = 13 [7,22], age = 48 [28, 64] years, and 73% male. Fifty pts met criteria for CAT+, 64 pts CAT-, and 370 received no Tx. Risk factors for meeting CAT+: decreased arrival systolic blood pressure (OR 2.82 [2.17, 3.67]), increased INR (OR 2.09, [1.66, 2.62]) and decreased time to peak OR 2.27 [1.74, 2.95]). These variables remained independently associated with increased risk of requiring Tx in a multivariable logistic model, after adjusting for sex and trauma type.

CONCLUSIONS

Pts in hemorrhagic shock, who meet CAT+ criteria, are characterized by accelerated thrombin generation. In our multivariable analysis, both ttPeak and PT/INR have a complementary role in predicting those injured patients who will require a high rate of Tx.

Thermoresponsive Hemostatic Hydrogel with a Biomimetic Nanostructure Constructed from Aggregated Collagen Nanofibers

Uncontrollable bleeding poses considerable fatality risks by large-volume blood losses. Current emergency antibleeding handlings including either compression with gauze or "passive" blood transfusion are thus far from ideal, while most recently developed hemostatic agents still share common limitations without considering the subsequent tissue repairing and antibacterial activity after treatment. Herein, we introduce a novel bioinspired aggregated collagen nanofiber-based biocompatible and efficient hemostatic hydrogel material (TS-Gel-Ag-col) prepared by the integration of multifunctional compounds of muco-mimetic poloxamer, polyvinylpyrrolidone, and dencichine/chitosan dialdehyde synergistic crosslinked aggregated collagen nanofibers decorated with silver nanoparticles. Comprehensive material characterization and in vitro and in vivo studies of TS-Gel-Ag-col demonstrate that these materials possess effective antihemorrhagic and antibacterial wound protection effects. Moreover, TS-Gel-Ag-col can facilitate the tissue repairing of skin wounds by promoting revascularization. TS-Gel-Ag-col holds great promise for next-generation collagen-based absorbable hemostatic materials and for the development of smart artificial skins.

Early identification of the need for major intervention in patients with traumatic hemorrhage: development and internal validation of a simple bleeding score

BACKGROUND

Failure to rapidly identify bleeding in trauma patients leads to substantial morbidity and mortality. We aimed to develop and validate a simple bedside score for identifying bleeding patients requiring escalation of care beyond initial resuscitation.

METHODS

We included patients with major blunt or penetrating trauma, defined as those with an Injury Severity Score greater than 12 or requiring trauma team activation, at The Ottawa Hospital from September 2014 to September 2017. We used logistic regression for derivation. The primary outcome was a composite of the need for massive transfusion, embolization or surgery for hemostasis. We prespecified clinical, laboratory and imaging predictors using findings from our prior systematic review and survey of Canadian traumatologists. We used an AIC-based stepdown procedure based on the Akaike information criterion and regression coefficients to create a 5-variable score for bedside application. We used bootstrap internal validation to assess optimism-corrected performance.

RESULTS

We included 890 patients, of whom 133 required a major intervention. The main model comprised systolic blood pressure, clinical examination findings suggestive of hemorrhage, lactate level, focused assessment with sonography in trauma (FAST) and computed tomographic imaging. The C statistic was 0.95, optimism-corrected to 0.94. A simplified Canadian Bleeding (CAN-BLEED) score was devised. A score cut-off of 2 points yielded sensitivity of 97.7% (95% confidence interval [CI] 93.6 to 99.5) and specificity 73.2% (95% CI 69.9 to 76.3). An alternative version that included mechanism of injury rather than CT had lower discriminative ability (C statistic = 0.89).

CONCLUSION

A simple yet promising bleeding score is proposed to identify highrisk patients in need of major intervention for traumatic bleeding and determine the appropriateness of early transfer to specialized trauma centres. Further research is needed to evaluate the performance of the score in other settings, define interrater reliability and evaluate the potential for reduction of time to intervention.

Prognostic Accuracy of Massive Transfusion, Critical Administration Threshold, and Resuscitation Intensity in Assessing Mortality in Traumatic Patients with Severe Hemorrhage: a Meta-Analysis

BACKGROUND

The aim of this study was to assess the prognostic value of massive transfusion (MT), critical administration threshold (CAT), and resuscitation intensity (RI) for the mortality of trauma patients with severe hemorrhage.

METHODS

Seventeen relevant articles were obtained by searching the PubMed databases through February 15, 2019. The estimated mortality rates and injury severity scores were obtained through a meta-analysis. In addition, diagnostic test accuracy (DTA) reviews were conducted to obtain the sensitivity, specificity, diagnostic odds ratio, and the summary receiver operating characteristic curve.

RESULTS

At 24 hours, the estimated mortality rates were 0.194, 0.126, and 0.168 in assessments using MT, CAT, and RI, respectively. In addition, the pooled sensitivity of CAT (0.89; 95% confidence interval [CI], 0.82-0.94) was significantly higher than that of MT (0.63; 95% CI, 0.57-0.68) and RI (0.69; 95% CI, 0.63-0.75). Overall, the pooled specificity of MT and CAT was 0.82 (95% CI, 0.80-0.83) and 0.85 (95% CI, 0.83-0.88), respectively, while the pooled sensitivity was 0.49 (95% CI, 0.44-0.54) and 0.50 (95% CI, 0.38-0.62), respectively.

CONCLUSION

CAT may be a more sensitive predictor for 24-hour mortality than other predictors. Furthermore, RI also appears to be a useful predictor for 24-hour mortality. Both MT and CAT showed high specificity for overall mortality.

Minute-to-minute urine flow rate variability: a retrospective survey of its ability to provide early warning of acute hypotension in critically ill multiple trauma patients

PURPOSE

Dynamic changes in urine output and neurological status are the recognized clinical signs of hemodynamically significant hemorrhage. In the present study, we analyzed the dynamic minute-to-minute changes in the UFR and also the changes in its minute-to-minute variability in a group of critically ill multiple trauma patients whose blood pressures were normal on admission to the ICU but who subsequently developed hypotension within the first few hours of their ICU admission.

PATIENTS AND METHODS

The study was retrospective and observational. Demographic and clinical data were extracted from the computerized register information systems initially; the clinical and laboratory data of 100 critically ill patients with multiple trauma who were admitted to the ICU during the study period were analyzed. Of this group, ten patients were eventually included in the study on the basis of the inclusion criteria.

RESULTS

The minute-to-minute urine flow rate (UFR) and urine flow rate variability (UFRV) both decreased significantly during the periods of hypotension (p values 0.001 and 0.006, respectively). Notably, the decrease in UFRV preceded by at least 30 min a corresponding decline in the systolic and mean arterial blood pressures, which manifested as a flattening of UFRV amplitude which was observed prior to the occurrence of the lowest recorded systolic and mean arterial blood pressures. Statistical analysis by the Pearson method demonstrated a strong direct correlation between the decrease in UFRV and the decrease in the MAP (R = 0.9, p = 0.001), and SBP (R = 0.86, p = 0.001) and the decreasing urine output per hour (R = 0.88, p < 0.001).

CONCLUSION

We found that changes in UFRV correlate strongly with systolic and mean arterial blood pressures. We feel that this parameter could potentially serve as an early signal of hemodynamic deterioration due to occult bleeding in critically ill trauma patients, and might also be able to identify the optimal end-point of hemodynamic resuscitative measures in these patients.

Accuracy of massive transfusion as a surrogate for significant traumatic bleeding in health administrative datasets

BACKGROUND

Due to the challenge of identifying need for intervention in bleeding patients, there is a growing interest in prediction modeling. Massive transfusion (MT; 10 or more packed red cells in 24 h) is the most commonly studied dependent variable, serving as a surrogate for severe bleeding and its prediction guides the need for intervention. The critical administration threshold (CAT; 3 packed red cells in 1 h) has been proposed as an alternative. In this study, we aim to compare the classification accuracy of these two surrogates for hemorrhage-related outcomes in health administrative datasets.

METHODS

We performed a secondary analysis of major trauma patients from the prospectively collected Ottawa Trauma Registry, from September 2014 to September 2017. We conducted a logistic regression analysis utilizing need for hemostasis or hemorrhagic death as dependent variables. We compared classification accuracy in terms of sensitivity, specificity, positive predictive value, negative predictive value and AUC. CAT + and MT + status is not mutually exclusive.

RESULTS

We studied 890 major trauma patients, including 145 CAT + and 48 MT + patients. CAT + demonstrated a superior association for the composite outcome of 24-hour hemorrhage-related mortality and need for hemostasis (AUC 0.815 vs. 0.644, p < 0.0001). This performance was driven by a substantial difference in sensitivity, noted to be 70.0% (95% CI 62.1-77.9%) for CAT + but only 30.0% (95% CI 22.1-37.9%) for MT+. CAT + and MT + demonstrated specificities of 92.9% (95% CI 91.1-94.7%) and 98.9% (98.1-99.6%) respectively.

CONCLUSION

This study illustrates the concepts of survivorship and competing risk bias for massive transfusion. Utilizing a composite outcome of need for hemostasis and early hemorrhagic death, we demonstrate that CAT + is more accurate for identifying significantly bleeding patients.

Repeat lactate level predicts mortality better than rate of clearance

BACKGROUND

Lactate clearance has been developed into a marker of resuscitation in trauma, but no study has compared the predictive power of the various clearance calculations. Our objective was to determine which method of calculating lactate clearance best predicted 24-hour and in-hospital mortality after injury.

STUDY DESIGN

Retrospective chart review of patients admitted to a Level-1 trauma center directly from the scene of injury from 2010 to 2013 who survived >15min, had an elevated lactate at admission (≥3mmol/L), followed by another measurement within 24h of admission. Lactate clearance was calculated using five models: actual value of the repeat level, absolute clearance, relative clearance, absolute rate, and relative rate. Models were compared using the areas under the respective receiver operating curves (AUCs), with an endpoint of death at 24h and in-hospital mortality.

RESULTS

3910 patients had an elevated admission lactate concentration on admission (mean=5.6±3.0mmol/L) followed by a second measurement (2.7±1.8mmol/L). Repeat absolute measurement best predicted 24-hour (AUC=0.85, 95% CI: 0.84-0.86) and in-hospital death (AUC=0.77; 95% CI, 0.76-0.78). Relative clearance was the best model of lactate clearance (AUC=0.77, 95% CI: 0.75-0.78 and AUC=0.705, 95% CI: 0.69-72, respectively) (p<0.0001 for each). A sensitivity analysis using a range of initial lactate measures yielded similar results.

CONCLUSIONS

The absolute value of the repeat lactate measurement had the greatest ability to predict mortality in injured patients undergoing resuscitation.

Urine flow rate monitoring in hypovolemic multiple trauma patients

Background

The urine output is an important clinical parameter of renal function and blood volume status, especially in critically ill multiple trauma patients. In the present study, the minute-to-minute urine flow rate and its variability were analyzed in hypotensive multiple trauma patients during the first 6 h of their ICU (intensive care unit) stay. These parameters have not been previously reported.

Methods

The study was retrospective and observational. Demographic and clinical data were extracted from the computerized Register Information Systems. A total of 59 patients were included in the study. The patients were divided into two study groups. Group 1 consisted of 29 multiple trauma patients whose systolic blood pressure was greater than 90 mmHg on admission to the ICU and who were consequently deemed to be hemodynamically compromised. Group 2 consisted of 30 patients whose systolic blood pressure was less than 90 mmHg on admission to the ICU and who were therefore regarded as hemodynamically uncompromised.

Results

The urine output and urine flow rate variability during the first 6 h of the patients’ ICU stay was significantly lower in group 2 than in group 1 (p < 0.001 and 0.006 respectively). Statistical analysis by the Pearson method demonstrated a strong direct correlation between decreased urine flow rate variability and decreased urine output per hour (R = 0.17; P = 0.009), decreased mean arterial blood pressure (R = 0.24; p = 0.001), and increased heart rate (R = 0.205; p = 0.001).

Conclusion

These findings suggest that minute-to-minute urine flow rate variability is a reliable incipient marker of hypovolemia and that it should therefore take its place among the parameters used to monitor the hemodynamic status of critically ill multiple trauma patients.

Chitosan–PVA monodisperse millimeter-sized spheres prepared by electrospraying reduce the thromboembolic risk in hemorrhage control

Chitosan–PVA monodisperse millimeter-sized spheres are efficient in hemorrhage control and also reduce the risk of thromboembolic complication.

Anomaly Detection Outperforms Logistic Regression in Predicting Outcomes in Trauma Patients

OBJECTIVE

Recent advancements in trauma resuscitation have shown a great benefit of early identification and control of hemorrhage, which is the most common cause of death in injured patients. We introduce a new analytical approach, anomaly detection (AD), as an alternative method to the traditional logistic regression (LR) method in predicting which injured patients receive transfusions, intensive care, and other interventions.

METHODS

We abstracted routinely collected prehospital vital sign data from patient records (adult patients who survived more than 15 minutes after being directly admitted to a level 1 trauma center). The vital signs of the study cohort were analyzed using both LR and AD methods. Predictions on blood transfusions generated by these approaches were compared with hospital records using the respective areas under the receiver operating characteristic curves (AUROC).

RESULTS

Of the patients seen at our trauma center between January 1, 2009, and December 31, 2010, 5,464 were included. AD significantly outperformed LR, identifying which patients would receive transfusions of uncrossmatched blood, transfusion of blood between the time of admission and 6 hours later, the need for intensive care, and in-hospital mortality (mean AUROC = 0.764 and 0.720, respectively). AD and LR provided similar predictions for the patients who would receive massive transfusion. Under the stratified 10 fold times 10 cross-validation test, AD also had significantly lower AUROC variance across subgroups than LR, suggesting AD is a more stable predictions model.

CONCLUSIONS

AD provides enhanced predictions for clinically relevant outcomes in the trauma patient cohort studied and may assist providers in caring for acutely injured patients in the prehospital arena.

Effect of hemorrhage rate on early hemodynamic responses in conscious sheep

Physiological compensatory mechanisms can mask the extent of hemorrhage in conscious mammals, which can be further complicated by individual tolerance and variations in hemorrhage onset and duration. We assessed the effect of hemorrhage rate on tolerance and early physiologic responses to hemorrhage in conscious sheep. Eight Merino ewes (37.4 ± 1.1 kg) were subjected to fast (1.25 mL/kg/min) and slow (0.25 mL/kg/min) hemorrhages separated by at least 3 days. Blood was withdrawn until a drop in mean arterial pressure (MAP) of >30 mmHg and returned at the end of the experiment. Continuous monitoring included MAP, central venous pressure, pulmonary artery pressure, pulse oximetry, and tissue oximetry. Cardiac output by thermodilution and arterial blood samples were also measured. The effects of fast versus slow hemorrhage rates were compared for total volume of blood removed and stoppage time (when MAP < 30 mmHg of baseline) and physiological responses during and after the hemorrhage. Estimated blood volume removed when MAP dropped 30 mmHg was 27.0 ± 4.2% (mean ± standard error) in the slow and 27.3 ± 3.2% in the fast hemorrhage (P = 0.47, paired t test between rates). Pressure and tissue oximetry responses were similar between hemorrhage rates. Heart rate increased at earlier levels of blood loss during the fast hemorrhage, but hemorrhage rate was not a significant factor for individual hemorrhage tolerance or hemodynamic responses. In 5/16 hemorrhages MAP stopping criteria was reached with <25% of blood volume removed. This study presents the physiological responses leading up to a significant drop in blood pressure in a large conscious animal model and how they are altered by the rate of hemorrhage.

Computer Modelling Using Prehospital Vitals Predicts Transfusion and Mortality

OBJECTIVE

Test computer-assisted modeling techniques using prehospital vital signs of injured patients to predict emergency transfusion requirements, number of intensive care days, and mortality, compared to vital signs alone.

METHODS

This single-center retrospective analysis of 17,988 trauma patients used vital signs data collected between 2006 and 2012 to predict which patients would receive transfusion, require 3 or more days of intensive care, or die. Standard transmitted prehospital vital signs (heart rate, blood pressure, shock index, and respiratory rate) were used to create a regression model (PH-VS) that was internally validated and evaluated using area under the receiver operating curve (AUROC). Transfusion records were matched with blood bank records. Documentation of death and duration of intensive care were obtained from the trauma registry.

RESULTS

During the course of their hospital stay, 720 of the 17,988 patients in the study population died (4%), 2,266 (12.6%) required at least a 3-day stay in the intensive care unit (ICU), 1,171 (6.5%) required transfusions, and 210 (1.2%) received massive transfusions. The PH-VS model significantly outperformed any individual vital sign across all outcomes (average AUROC = 0.82), The PH-VS model correctly predicted that 512 of 777 (65.9%) and 580 of 931 (62.3%) patients in the study population would receive transfusions within the first 2 and 6 hours of admission, respectively.

CONCLUSIONS

The predictive ability of individual vital signs to predict outcomes is significantly enhanced with the model. This could support prehospital triage by enhancing decision makers' ability to match critically injured patients with appropriate resources with minimal delays.

Prediction of critical haemorrhage following trauma: A narrative review

Introduction: Traumatic haemorrhagic shock can be difficult to diagnose. Models for predicting critical bleeding and massive transfusion have been developed to aid clinicians. The aim of this review is to outline the various available models and report on their performance and validation. Methods: A review of the English and non-English literature in Medline, PubMed and Google Scholar was conducted from 1990 to September 2015. We combined several terms for i) haemorrhage AND ii) prediction, in the setting of iii) trauma. We included models that had at least two data points. We extracted information about the models, their developments, performance and validation. Results: There were 36 different models identified that diagnose critical bleeding, which included a total of 36 unique variables. All models were developed retrospectively. The models performed with variable predictive abilities–the most superior with an area under the receiver operating characteristics curve of 0.985, but included detailed findings on imaging and was based on a small cohort. The most commonly included variable was systolic blood pressure, featuring in all but five models. Pattern or mechanism of injury were used by 16 models. Pathology results were used by 15 models, of which nine included base deficit and eight models included haemoglobin. Imaging was utilised in eight models. Thirteen models were known to be validated, with only one being prospectively validated. Conclusions: Several models for predicting critical bleeding exist, however none were deemed accurate enough to dictate treatment. Potential areas of improvement identified include measures of variability in vital signs and point of care imaging and pathology testing.

Predicting blood transfusion using automated analysis of pulse oximetry signals and laboratory values

BACKGROUND

Identification of hemorrhaging trauma patients and prediction of blood transfusion needs in near real time will expedite care of the critically injured. We hypothesized that automated analysis of pulse oximetry signals in combination with laboratory values and vital signs obtained at the time of triage would predict the need for blood transfusion with accuracy greater than that of triage vital signs or pulse oximetry analysis alone.

METHODS

Continuous pulse oximetry signals were recorded for directly admitted trauma patients with abnormal prehospital shock index (heart rate [HR] / systolic blood pressure) of 0.62 or greater. Predictions of blood transfusion within 24 hours were compared using Delong's method for area under the receiver operating characteristic (AUROC) curves to determine the optimal combination of triage vital signs (prehospital HR + systolic blood pressure), pulse oximetry features (40 waveform features, O2 saturation, HR), and laboratory values (hematocrit, electrolytes, bicarbonate, prothrombin time, international normalization ratio, lactate) in multivariate logistic regression models.

RESULTS

We enrolled 1,191 patients; 339 were excluded because of incomplete data; 40 received blood within 3 hours; and 14 received massive transfusion. Triage vital signs predicted need for transfusion within 3 hours (AUROC, 0.59) and massive transfusion (AUROC, 0.70). Pulse oximetry for 15 minutes predicted transfusion more accurately than triage vital signs for both time frames (3-hour AUROC, 0.74; p = 0.004) (massive transfusion AUROC, 0.88; p < 0.001). An algorithm including triage vital signs, pulse oximetry features, and laboratory values improved accuracy of transfusion prediction (3-hour AUROC, 0.84; p < 0.001) (massive transfusion AUROC, 0.91; p < 0.001).

CONCLUSION

Automated analysis of triage vital signs, 15 minutes of pulse oximetry signals, and laboratory values predicted use of blood transfusion during trauma resuscitation more accurately than triage vital signs or pulse oximetry analysis alone. Results suggest automated calculations from a noninvasive vital sign monitor interfaced with a point-of-care laboratory device may support clinical decisions by recognizing patients with hemorrhage sufficient to need transfusion.

LEVEL OF EVIDENCE

Epidemiologic/prognostic study, level III.

Are the paradigms in trauma disease changing?

Despite an annual trauma mortality of 5 million people worldwide, resulting in countless physical disabilities and enormous expenses, there are no standardized guidelines on trauma organization and management. Over the last few decades there have been very notorious improvements in severe trauma care, though organizational and economical aspects such as research funding still need to be better engineered. Indeed, trauma lags behind other serious diseases in terms of research and organization. The rapid developments in trauma care have produced original models available for research projects, initial resuscitation protocols and radiological procedures such as CT for the initial management of trauma patients, among other advances. This progress underscores the need for a multidisciplinary approach to the initial management and follow-up of this complicated patient population, where intensivists play a major role in both the patient admission and subsequent care at the trauma unit.

Trauma resuscitation and monitoring: military lessons learned

Over the past 13 years, the military health care system has made improvements that are associated with an unprecedented survival rate for severely injured casualties. Monitoring for indications of deterioration as the critically injured patient moves across the continuum of care is difficult given the limitations of routinely used vital signs. Research by both military and civilian researchers is revolutionizing monitoring, with an increased focus on noninvasive, continuous, dynamic measurements to provide earlier, more sensitive indications of the patient's perfusion status.

Accuracy of continuous noninvasive hemoglobin monitoring for the prediction of blood transfusions in trauma patients

Early detection of hemorrhagic shock is required to facilitate prompt coordination of blood component therapy delivery to the bedside and to expedite performance of lifesaving interventions. Standard physical findings and vital signs are difficult to measure during the acute resuscitation stage, and these measures are often inaccurate until patients deteriorate to a state of decompensated shock. The aim of this study is to examine a severely injured trauma patient population to determine whether a noninvasive SpHb monitor can predict the need for urgent blood transfusion (universal donor or additional urgent blood transfusion) during the first 12 h of trauma patient resuscitation. We hypothesize that trends in continuous SpHb, combined with easily derived patient-specific factors, can identify the immediate need for transfusion in trauma patients. Subjects were enrolled if directly admitted to the trauma center, >17 years of age, and with a shock index (heart rate/systolic blood pressure) >0.62. Upon admission, a Masimo Radical-7 co-oximeter sensor (Masimo Corporation, Irvine, CA) was applied, providing measurement of continuous non-invasive hemoglobin (SpHb) levels. Blood was drawn and hemoglobin concentration analyzed and conventional pulse oximetry photopletysmograph signals were continuously recorded. Demographic information and both prehospital and admission vital signs were collected. The primary outcome was transfusion of at least one unit of packed red blood cells within 24 h of admission. Eight regression models (C1-C8) were evaluated for the prediction of blood use by comparing area under receiver operating curve (AUROC) at different time intervals after admission. 711 subjects had continuous vital signs waveforms available, to include heart rate (HR), SpHb and SpO2 trends. When SpHb was monitored for 15 min, SpHb did not increase AUROC for prediction of transfusion. The highest ROC was recorded for model C8 (age, sex, prehospital shock index, admission HR, SpHb and SpO2) for the prediction of blood products within the first 3 h of admission. When data from 15 min of continuous monitoring were analyzed, significant improvement in AUROC occurred as more variables were added to the model; however, the addition of SpHb to any of the models did not improve AUROC significantly for prediction of blood use within the first 3 h of admission in comparison to analysis of conventional oximetry features. The results demonstrate that SpHb monitoring, accompanied by continuous vital signs data and adjusted for age and sex, has good accuracy for the prediction of need for transfusion; however, as an independent variable, SpHb did not enhance predictive models in comparison to use of features extracted from conventional pulse oximetry. Nor was shock index better than conventional oximetry at discriminating hemorrhaging and prediction of casualties receiving blood. In this population of trauma patients, noninvasive SpHb monitoring, including both trends and absolute values, did not enhance the ability to predict the need for blood transfusion.