Extremes of shock index predicts death in trauma patients

Traumatic brain injury and variants of shock index

Traumatic Brain Injury is a major cause of death and long-term disability. The early identification of patients at high risk of mortality is important for both management and prognosis. Although many modified scoring systems have been developed for improving the prediction accuracy in patients with trauma, few studies have focused on prediction accuracy and application in patients with traumatic brain injury. The shock index (SI) which was first introduced in the 1960s has shown to strongly correlate degree of circulatory shock with increasing SI. In this editorial we comment on a publication by Carteri et al wherein they perform a retrospective analysis studying the predictive potential of SI and its variants in populations with severe traumatic brain injury.

Prehospital Shock Index Multiplied by the Alert/Verbal/Painful/Unresponsive Score as a Predictor of Clinical Outcomes in Traumatic Injury

OBJECTIVE

Various prediction scores have been developed to predict mortality in trauma patients, such as the shock index (SI), modified SI (mSI), age-adjusted SI (aSI), and the shock index (SI) multiplied by the alert/verbal/painful/unresponsive (AVPU) score (SIAVPU). The SIAVPU is a novel scoring system but its prediction accuracy for trauma outcomes remains in need of further validation. Therefore, we investigated the accuracy of four scoring systems, including SI, mSI, aSI, and SIAVPU, in predicting mortality, admission to the intensive care unit (ICU), and prolonged hospital length of stay ≥ 30 days (LOS).

METHODS

This retrospective multicenter study used data from the Tzu Chi Hospital trauma database. The area under the receiver operating characteristic curve (AUROC) was determined for each outcome to assess their discrimination capabilities and comparing by Delong's test. Subgroup analyses were conducted to investigate the prediction accuracy of the SIAVPU in different patient populations.

RESULTS

In total, 5355 patients were included in the analysis. The median of SIAVPU were significantly higher among patients at those with major injury (1.47 vs 0.63), those admitted to the ICU (0.73 vs 0.62), those with prolonged hospital LOS≥ 30 days (0.83 vs 0.64), and those with mortality (1.08 vs 0.64). The AUROC of the SIAVPU was significantly higher than that of the SI, mSI, and aSI for 24-h mortality (AUROC: 0.845 vs 0.533, 0.540, and 0.678), 3-day mortality (AUROC: 0.803 vs 0.513, 0.524, and 0.688), 7-day mortality (AUROC: 0.755 vs 0.494, 0.505, and 0.648), in-hospital mortality (AUROC: 0.722 vs 0.510, 0.524, and 0.667), ICU admission (AUROC: 0.635 vs 0.547, 0.551, and 0.563). At the optimal cutoff value of 0.9, the SIAVPU had an accuracy of 82.2% for predicting 24-h mortality, 82.8% for predicting 3-day mortality, of 82.8% for predicting 7-day mortality, of 82.5% for predicting in-hospital mortality, of 73.9% for predicting Intensive Care Unit (ICU) admission, and of 81.7% for predicting prolonged hospital LOS ≥30 days.

CONCLUSIONS

Our results reveal that SIAVPU has better accuracy than the SI, mSI, and aSI for predicting 24-h, 3-day, 7-day, and in-hospital mortality; ICU admission; and prolonged hospital LOS ≥30 days among patients with traumatic injury.

Early Abnormal Vital Signs Predict Poor Outcomes in Normotensive Patients Following Penetrating Trauma

INTRODUCTION

Because trauma patients in class II shock (blood loss of 15%-30% of total blood volume) arrive normotensive, this makes the identification of shock and subsequent prognostication of outcomes challenging. Our aim was to identify early predictive factors associated with worse outcomes in normotensive patients following penetrating trauma. We hypothesize that abnormalities in initial vital signs portend worse outcomes in normotensive patients following penetrating trauma.

METHODS

A retrospective review was performed from 2006 to 2021 using our trauma database and included trauma patients presenting with penetrating trauma with initial normotensive blood pressures (systolic blood pressure ≥90 mmHg). We compared those with a narrow pulse pressure (NPP ≤25% of systolic blood pressure), tachycardia (heart rate ≥100 beats per minute), and elevated shock index (SI ≥ 0.8) to those without. Outcomes included mortality, intensive care unit admission, and ventilator use. Chi-squared, Mann-Whitney tests, and regression analyses were performed as appropriate.

RESULTS

We identified 7618 patients with penetrating injuries and normotension on initial trauma bay assessment. On univariate analysis, NPP, tachycardia, and elevated SI were associated with increases in mortality compared to those without. On multivariable logistic regression, only NPP and tachycardia were independently associated with mortality. Tachycardia and an elevated SI were both independently associated with intensive care unit admission. Only an elevated SI had an independent association with ventilator requirements, while an NPP and tachycardia did not.

CONCLUSIONS

Immediate trauma bay NPP and tachycardia are independently associated with mortality and adverse outcomes and may provide an opportunity for improved prognostication in normotensive patients following penetrating trauma.

Prehospital shock index predicts 24-h mortality in trauma patients with a normal shock index upon emergency department arrival

BACKGROUND

The shock index (heart rate divided by systolic blood pressure) of trauma patients upon emergency department arrival predicts blood loss and death. However, some patients with normal shock indices (0.4 < shock index <0.9) upon emergency department arrival also have poor prognoses. This study aimed to determine whether abnormal prehospital shock indices in trauma patients with normal shock indices upon emergency department arrival were predictors of a high risk of mortality.

METHODS

We conducted a retrospective cohort study of emergency department-admitted trauma patients from 2004 to 2017. The study included 89,495 consecutive trauma patients aged ≥16 years, with Abbreviated Injury Scale score of ≥3, who were transported to the emergency department directly from the field and had a normal shock index upon emergency department arrival. According to the prehospital shock index scores, the patients were categorized into low shock index (≤ 0.4), normal shock index, and high shock index (≥0.9) groups. Odds ratios and 95% confidence intervals were calculated using logistic regression analysis.

RESULTS

The 89,495 patients had a median age of 64 (interquartile range: 43-79) years, and 55,484 (62.0%) of the patients were male. There were 1350 (1.5%) 24-h deaths in total; 176/4263 (4.1%), 1017/78,901 (1.3%), and 157/6331 (2.5%) patients were in the low, normal, and high prehospital shock index groups, respectively. The adjusted odds ratios for 24-h mortality compared with the normal shock index group were 1.63 (95% confidence interval: 1.34-1.99) in the low shock index group and 1.62 (95% confidence interval: 1.31-1.99) in the high shock index group.

CONCLUSION

Trauma patients with abnormal prehospital shock indices but normal shock indices upon emergency department arrival are at a higher risk of 24-h mortality. Identifying these indices could improve triage and targeted care for patients.

Discriminant ability of the shock index, modified shock index, and reverse shock index multiplied by the Glasgow coma scale on mortality in adult trauma patients: a PATOS retrospective cohort study

BACKGROUND

The shock index (SI) predicts short-term mortality in trauma patients. Other shock indices have been developed to improve discriminant accuracy. The authors examined the discriminant ability of the SI, modified SI (MSI), and reverse SI multiplied by the Glasgow Coma Scale (rSIG) on short-term mortality and functional outcomes.

METHODS

The authors evaluated a cohort of adult trauma patients transported to emergency departments. The first vital signs were used to calculate the SI, MSI, and rSIG. The areas under the receiver operating characteristic curves and test results were used to compare the discriminant performance of the indices on short-term mortality and poor functional outcomes. A subgroup analysis of geriatric patients with traumatic brain injury, penetrating injury, and nonpenetrating injury was performed.

RESULTS

A total of 105 641 patients (49±20 years, 62% male) met the inclusion criteria. The rSIG had the highest areas under the receiver operating characteristic curve for short-term mortality (0.800, CI: 0.791-0.809) and poor functional outcome (0.596, CI: 0.590-0.602). The cutoff for rSIG was 18 for short-term mortality and poor functional outcomes with sensitivities of 0.668 and 0.371 and specificities of 0.805 and 0.813, respectively. The positive predictive values were 9.57% and 22.31%, and the negative predictive values were 98.74% and 89.97%. rSIG also had better discriminant ability in geriatrics, traumatic brain injury, and nonpenetrating injury.

CONCLUSION

The rSIG with a cutoff of 18 was accurate for short-term mortality in Asian adult trauma patients. Moreover, rSIG discriminates poor functional outcomes better than the commonly used SI and MSI.

Shock index, modified shock index, age shock index score, and reverse shock index multiplied by Glasgow Coma Scale predicting clinical outcomes in traumatic brain injury: Evidence from a 10-year analysis in a single center

OBJECTIVES

Early identification of traumatic brain injury (TBI) patients at a high risk of mortality is very important. This study aimed to compare the predictive accuracy of four scoring systems in TBI, including shock index (SI), modified shock index (MSI), age-adjusted shock index (ASI), and reverse shock index multiplied by the Glasgow Coma Scale (rSIG).

PATIENTS AND METHODS

This is a retrospective analysis of a registry from the Taipei Tzu Chi trauma database. Totally, 1,791 patients with TBI were included. We investigated the accuracy of four major shock indices for TBI mortality. In the subgroup analysis, we also analyzed the effects of age, injury mechanism, underlying diseases, TBI severity, and injury severity.

RESULTS

The predictive accuracy of rSIG was significantly higher than those of SI, MSI, and ASI in all the patients [area under the receiver operating characteristic curve (AUROC), 0.710 vs. 0.495 vs. 0.527 vs. 0.598], especially in the moderate/severe TBI (AUROC, 0.625 vs. 0.450 vs. 0.476 vs. 0.529) and isolated head injury populations (AUROC 0.689 vs. 0.472 vs. 0.504 vs. 0.587). In the subgroup analysis, the prediction accuracy of mortality of rSIG was better in TBI with major trauma [Injury Severity Score (ISS) ≥ 16], motor vehicle collisions, fall injury, and healthy and cardiovascular disease population. rSIG also had a better prediction effect, as compared to SI, MSI, and ASI, both in the non-geriatric (age < 65 years) and geriatric (age ≥ 65 years).

CONCLUSION

rSIG had a better prediction accuracy for mortality in the overall TBI population than SI, MSI, and ASI. Although rSIG have better accuracy than other indices (ROC values indicate poor to moderate accuracy), the further clinical studies are necessary to validate our results.

Shock index as a predictor for mortality in trauma patients: a systematic review and meta-analysis

PURPOSE

The primary aim was to determine whether a shock index (SI) ≥ 1 in adult trauma patients was associated with increased in-hospital mortality compared to an SI < 1.

METHODS

This systematic review including a meta-analysis was performed in accordance with the PRISMA guidelines. EMBASE, MEDLINE, and Cochrane Library were searched, and two authors independently screened articles, performed the data extraction, and assessed risk of bias. Studies were included if they reported in-hospital, 30-day, or 48-h mortality, length of stay, massive blood transfusion or ICU admission in trauma patients with SI recorded at arrival in the emergency department or trauma center. Risk of bias was assessed using the Newcastle-Ottawa Scale, and the strength and quality of the body of evidence according to GRADE. Data were pooled using a random effects model. Inter-rater reliability was assessed with Cohen's kappa.

RESULTS

We screened 1350 citations with an inter-rater reliability of 0.90. Thirty-eight cohort studies were included of which 14 reported the primary outcome. All studies reported a significant higher in-hospital mortality in adult trauma patients with an SI ≥ 1 compared to those having an SI < 1. Twelve studies involving a total of 348,687 participants were included in the meta-analysis. The pooled risk ratio (RR) of in-hospital mortality was 4.15 (95% CI 2.96-5.83). The overall quality of evidence was low.

CONCLUSIONS

This systematic review found a fourfold increased risk of in-hospital mortality in adult trauma patients with an initial SI ≥ 1 in the emergency department or trauma center.

Shock index as a predictor for short-term mortality in helicopter emergency medical services: A registry study

BACKGROUND

The value of shock-index has been demonstrated in hospital triage, but few studies have evaluated its prehospital use. The aim of our study was to evaluate the association between shock-index in prehospital critical care and short-term mortality.

METHODS

We analyzed data from the national helicopter emergency medical services database and the Population Register Centre. The shock-index was calculated from the patients' first measured parameters. The primary outcome measure was 1- and 30-day mortality.

RESULTS

A total of 22 433 patients were included. The 1-day mortality was 7.5% and 30-day mortality was 16%. The median shock-index was 0.68 (0.55/0.84) for survivors and 0.67 (0.49/0.93) for non-survivors (P = .316) at 30-days. Association between shock-index and mortality followed a U-shaped curve in trauma (shock-index < 0.5: odds ratio 2.5 [95% confidence interval 1.8-3.4], shock-index > 1.3: odds ratio 4.4 [2.7-7.2] at 30 days). Patients with neurological emergencies with a low shock-index had an increased risk of mortality (shock-index < 0.5: odds ratio 1.8 [1.5-2.3]) whereas patients treated after successful resuscitation from out-of-hospital cardiac arrest, a higher shock-index was associated with higher mortality (shock-index > 1.3: odds ratio 3.5 [2.3-5.4). The association was similar for all ages, but older patients had higher mortality in each shock-index category.

CONCLUSION

The shock-index is associated with short time mortality in most critical patient categories in the prehospital setting. However, the marked overlap of shock-index in survivors and non-survivors in all patient categories limits its predictive value.

Automated remote decision-making algorithm as a primary triage system using machine learning techniques

OBJECTIVE

An objective and convenient primary triage procedure is needed for prioritizing patients who need help in mass casualty incident (MCI) situations, where there is a lack of medical staff and available resources. This study aimed to develop an automated remote decision-making algorithm that remotely categorize a patient's emergency level using clinical parameters that can be measured with a wearable device.

APPROACH

The algorithm was developed according to the following procedures. First, we used the National Trauma Data Bank data set, a large open trauma patient data set assembled by the American College of Surgeons (ACS). In addition, we performed pre-processing to exclude data when the vital sign or consciousness indicator value was missing or physiologically in an abnormal range. Second, we selected the T-RTS method, which classifies emergency levels into four classes (Delayed, Urgent, Immediate and Dead), as the primary outcome. Third, three machine learning methods widely used in the medical field, logistic regression, random forest, and deep neural network (DNN), were applied to build the algorithm. Finally, each method was evaluated using quantitative performance indicators including the macro-averaged f1 score, macro-averaged mean absolute error (MMAE), and the area under the receiver operating characteristic curve (AUC).

MAIN RESULTS

For total sets, the logistic regression had a macro-averaged f1 score of 0.673, an MMAE of 0.387 and an AUC value of 0.844 (95% CI, 0.843-0.845), while the random forest and DNN had macro-averaged f1 scores of 0.783 and 0.784, MMAEs of 0.297 and 0.298 and AUC values of 0.882 (95% CI, 0.881-0.883) and 0.883(95% CI, 0.881-0.884), respectively.

SIGNIFICANCE

In a comprehensive analysis of these results, our algorithm demonstrated a viable approach that could be practically adopted in an MCI. In addition, it can be employed to transfer patients and to redistribute available resources according to their priorities.

Equivalency between the shock index and subtracting the systolic blood pressure from the heart rate: an observational cohort study

Background

Although the shock index is known to predict mortality and other severe outcomes, deriving it requires complex calculations. Subtracting the systolic blood pressure from the heart rate may produce a simple shock index that would be a clinically useful substitute for the shock index. In this study, we investigated whether the simple shock index was equivalent to the shock index.

Methods

This observational cohort study was conducted at 2 tertiary care hospitals. Patients who were transported by ambulance were recruited for this study and were excluded if they were aged < 15 years, had experienced prehospital cardiopulmonary arrest, or had undergone inter-hospital transfer. Pearson’s product-moment correlation coefficient and regression equation were calculated, and two one-sided tests were performed to examine their equivalency.

Results

Among 5429 eligible patients, the correlation coefficient between the shock index and simple shock index was extremely high (0.917, 95% confidence interval 0.912 to 0.921, P < .001). The regression equation was estimated as sSI = 258.55 log SI. The two one-sided tests revealed a very strong equivalency between the shock index and the index estimated by the above equation using the simple shock index (mean difference was 0.004, 90% confidence interval 0.003 to 0.005).

Conclusion

The simple shock index strongly correlated with the shock index.

Shock Index as a Marker for Mortality Rates in Those Admitted to the Medical Intensive Care Unit from the Emergency Department

Objective

Shock index (SI) is defined as the heart rate divided by systolic blood pressure. Studies have shown a correlation between the shock index and mortality in trauma patients in prehospital settings and in the emergency department (ED). The objective of this study was to identify the utility of SI in predicting mortality in the medical intensive care unit (MICU) patients admitted from the ED and transfers from the floor to MICU. 

Design

We performed a retrospective analysis of adult patients admitted to the MICU at our urban trauma hospital between January 2015 through August 2015 using ED vital signs to calculate the shock index and identify inpatient deaths. Similar data were examined for inpatient transfers to the MICU.

Results

Nine hundred and fifty patients were included in the study; 743 had an SI ≤ 0.99 with a mortality rate of 15.9%. Two hundred and seven patients had a SI ≥ 1.00 with a mortality rate of 22.7%. A higher SI was significant for mortality. There was no statistical significance in SI and mortality rate for patients transferred from the medical floor to the ICU.

Conclusions

Patients with an SI ≥ 1.00 from initial ED vital signs correlated with a higher mortality rate. In patients transferred from the floor to MICU, SI ≥ 1.00 did not correlate with a higher mortality rate.

Pre-hospital modified shock index for prediction of massive transfusion and mortality in trauma patients

BACKGROUND

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.

METHODS

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).

RESULTS

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.

CONCLUSIONS

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.

Shock index in patients with traumatic solid organ injury as a predictor of massive blood transfusion protocol activation

Purpose

We aimed to assess the utility of shock index (SI) to predict the need for massive transfusion protocol (MTP) in patients with solid organ injury (SOI) in a Level 1 Trauma center.

Methods

We conducted a retrospective analysis for patients with SOI between 2011 and 2014. Patients were categorized according to on-admission SI into low (< 0.8) and high SI (≥0.8) group.

Results

A total of 4500 patients were admitted with trauma, of them 572 sustained SOIs (289 patients had SI ≥0.8). In comparison to low SI, patients with high SI were younger, had higher injury severity scores (ISS) and lower Trauma and Injury Severity Score (TRISS); (p < 0.001). The proportion of exploratory laparotomy (EXLap), blood transfusion (BT), MTP activation, sepsis and hospital mortality were significantly higher in patients with high SI. Serum lactate (r = 0.34), hematocrit (r = − 0.34), ABC score (r = 0.62), ISS (r = 0.35), and amount of transfused blood (r = 0.22) were significantly correlated with SI. On multivariable regression analysis using 9 relevant variables (age, sex, ISS, ED GCS, serum lactate, hematocrit, Abdomen AIS and Focused assessment with sonography in trauma (FAST) and SI), SI ≥ 0.8 was an independent predictor of BT (OR 2.80; 95%CI 1.56–4.95) and MTP (OR 2.81;95% CI 1.09–7.21) .

Conclusions

In patients with SOI, SI is a simple bedside predictor for BT and MTP activation. Further prospective studies are needed to support our findings.

Shock index in the emergency department: utility and limitations

Shock index (SI) is defined as the heart rate (HR) divided by systolic blood pressure (SBP). It has been studied in patients either at risk of or experiencing shock from a variety of causes: trauma, hemorrhage, myocardial infarction, pulmonary embolism, sepsis, and ruptured ectopic pregnancy. While HR and SBP have traditionally been used to characterize shock in these patients, they often appear normal in the compensatory phase of shock and can be confounded by factors such as medications (eg, antihypertensives, beta-agonists). SI >1.0 has been widely found to predict increased risk of mortality and other markers of morbidity, such as need for massive transfusion protocol activation and admission to intensive care units. Recent research has aimed to study the use of SI in patients immediately on arrival to the emergency department (ED). In this review, we summarize the literature pertaining to use of SI across a variety of settings in the management of ED patients, in order to provide context for use of this measure in the triage and management of critically ill patients.

Prognostic Role of Shock Index in Traumatic Pelvic Fracture: A Retrospective Analysis

BACKGROUND

We aimed to validate the utility of shock index (SI) in predicting the need of blood transfusion and outcomes in patients with traumatic pelvic fracture (TPF).

MATERIALS AND METHODS

We conducted a retrospective analysis for patients who sustained TPF between 2012 and 2016 in a level 1 trauma center. Patients were categorized into patients with low versus high SI based on the cutoff obtained from the receiver operating characteristic curves to predict mortality.

RESULTS

A total of 966 patients sustained TPF (28.5% had SI ≥ 0.9 based on receiver operating characteristic curves) with a median age of 33 (IQR 25-47) y. Type B and C pelvic fractures significantly had higher SI. The frequency of blood transfusion use was greater in patients with high SI (P = 0.001). SI correlated significantly with Injury Severity Score (r = 0.32), Revised Trauma Score (r = -0.40), and transfused blood units (r = 0.35). Patients with high SI had prolonged hospital length of stay and higher mortality (P = 0.001). SI ≥ 0.9 showed high sensitivity and negative predictive value to identify the need of massive blood transfusion (77% and 86%, respectively) and mortality (73.5% and 98.1%, respectively). For hospital mortality, high SI had a sensitivity of 73.5%, specificity 74%, negative predictive value 98%, and negative likelihood ratio of 0.36. After adjustment for age, sex, Injury Severity Score, Glasgow Coma Scale, pelvis Abbreviated Injury Scale, blood transfusion, and Tile classification, the multivariate analysis models showed that high SI was an independent predictor of blood transfusion (odd ratio 5.6) and mortality (odd ratio 3.63).

CONCLUSIONS

SI is a potentially useful instant tool for the prediction of massive transfusion and mortality in patients with TPF. Further prospective studies are warranted to support our findings.

Predicting in-hospital mortality among non-trauma patients based on vital sign changes between prehospital and in-hospital: An observational cohort study

Objective

To prevent misjudgment of the severity of patients in the emergency department who initially seem non-severe but are in a critical state, methods that differ from the conventional viewpoint are needed. We aimed to determine whether vital sign changes between prehospital and in-hospital could predict in-hospital mortality among non-trauma patients.

Methods

This observational cohort study was conducted in two tertiary care hospitals. Patients were included if they were transported by ambulance for non-trauma-related conditions but were excluded if they experienced prehospital cardiopulmonary arrest, were pregnant, were aged <15 years, had undergone inter-hospital transfer, or had complete missing data regarding prehospital or in-hospital vital signs. The main outcome was in-hospital mortality, and the study variables were changes in vital signs, pulse pressure, and/or shock index between the prehospital and in-hospital assessments. Logistic regression analyses were performed to obtain adjusted odds ratios for each variable. Receiver operating characteristic curve analyses were performed to identify cut-off values that produced a positive likelihood ratio of ≥2.

Results

Among the 2,586 eligible patients, 170 died in the two hospitals. Significantly elevated risks of in-hospital mortality were associated with changes in the Glasgow Coma Scale (cut-off ≤–3), respiratory rate (no clinically significant cut-off), systolic blood pressure (cut-off ≥47 mmHg), pulse pressure (cut-off ≥55 mmHg), and shock index (cut-off ≥0.3).

Conclusions

Non-trauma patients who exhibit changes in some vital signs between prehospital and in-hospital have an increased risk of in-hospital mortality. Therefore, it is useful to incorporate these changes in vital signs to improve triaging and predict the occurrence of in-hospital mortality.

Systolic blood pressure lower than the heart rate indicates a poor outcome in patients with severe isolated traumatic brain injury: A cross-sectional study

BACKGROUND

A systolic blood pressure (SBP) lower than the heart rate (HR) could indicate a poor condition in trauma patients. In such scenarios, the reversed shock index (RSI) is < 1, as calculated by the SBP divided by the HR. This study aimed to clarify whether RSI could be used to identify high-risk adult patients with isolated traumatic brain injury (TBI).

METHODS

This retrospective study reviewed 1216 hospitalized adult patients with isolated TBI at a Level I trauma center between January 1, 2009 and December 31, 2015. The patients were grouped and analyzed according to RSI (<1 or ≥ 1). Subgroups of patients with severe TBI (Glasgow Coma Scale [GCS] ≤ 8) or non-severe TBI (GCS > 8) were also compared. The primary outcome was in-hospital mortality. The odds ratios (ORs) of categorical variables were calculated by chi-square tests with 95% confidence intervals (CIs). Mann-Whitney U-tests were used to analyze non-normally distributed continuous data.

RESULTS

Among patients with isolated TBI, those with an RSI <1 had higher mortality (44.7% vs. 7.1%, OR: 10.5, 95% CI: 5.36-20.75; P < 0.001) than those with an RSI ≥1. An RSI <1 indicated a higher risk of mortality (OR: 5.1, 95% CI: 2.08-12.49; P < 0.001) in patients with severe isolated TBI but not in patients with non-severe isolated TBI (OR: 3.6, 95% CI: 0.45-28.71; P = 0.267).

CONCLUSION

Patients with isolated TBI may be at risk for shock. In trauma patients with severe isolated TBI, an SBP lower than the HR indicates a poor outcome.

Delta Shock Index in the Emergency Department Predicts Mortality and Need for Blood Transfusion in Trauma Patients

Shock Index (SI = heart rate/systolic blood pressure) predicts outcomes among trauma patients. Studies have also shown that the change in SI between the field and Emergency Department (ED) arrival (Delta SI) predicts mortality in trauma. Given the lack of reliable prehospital data, Delta SI may more accurately prognosticate if used within the ED. All trauma patients arriving to our Level I trauma center in 2014 were reviewed. Patients were matched for age, gender, mechanism of injury, and injury severity score. SI and ED Delta SI were calculated. ED Delta SI >0.1 and ≤0.1 defined the study groups. Pregnant patients, pediatric patients, and patients with incomplete data were excluded. Outcomes included intensive care unit (ICU) length of stay, blood products, and mortality. A total of 2591 patients were identified (n = 1294 patients analyzed). After matching, patients with ED Delta SI >0.1 had greater mortality (6.6 vs 2.6%, P = 0.010), need for blood transfusion (1764 vs 565 cc, P < 0.001), and ICU length of stay (5.6 vs 3.8 days, P = 0.014) compared with patients with ED Delta SI ≤0.1. In conclusion, ED Delta SI >0.1 is associated with increased mortality, need for blood transfusion, and ICU length of stay. Delta SI may be superior to traditional SI for trauma outcome prognostication.

Muscle Oxygenation as an Early Predictor of Shock Severity in Trauma Patients

INTRODUCTION

We evaluated the potential utility of a new prototype noninvasive muscle oxygenation (MOx) measurement for the identification of shock severity in a population of patients admitted to the trauma resuscitation rooms of a Level I regional trauma center. The goal of this project was to correlate MOx with shock severity as defined by standard measures of shock: systolic blood pressure, heart rate, and lactate.

METHODS

Optical spectra were collected from subjects by placement of a custom-designed optical probe over the first dorsal interosseous muscles on the back of the hand. Spectra were acquired from trauma patients as soon as possible upon admission to the trauma resuscitation room. Patients with any injury were eligible for study. MOx was determined from the collected optical spectra with a multiwavelength analysis that used both visible and near-infrared regions of light. Shock severity was determined in each patient by a scoring system based on combined degrees of hypotension, tachycardia, and lactate. MOx values of patients in each shock severity group (mild, moderate, and severe) were compared using two-sample t tests.

RESULTS

In 17 healthy control patients, the mean MOx value was 91.0 ± 5.5%. A total of 69 trauma patients were studied. Patients classified as having mild shock had a mean MOx of 62.5 ± 26.2% (n = 33), those classified as in moderate shock had a mean MOx of 56.9 ± 26.9% (n = 25) and those classified as in severe shock had a MOx of 31.0 ± 17.1% (n = 11). Mean MOx for each of these groups was statistically different from the healthy control group (P < 0.05).Receiver operating characteristic analyses show that MOx and shock index (heart rate/systolic blood pressure) identified shock similarly well (area under the curves [AUC] = 0.857 and 0.828, respectively). However, MOx identified mild shock better than shock index in the same group of patients (AUC = 0.782 and 0.671, respectively).

CONCLUSIONS

The results obtained from this pilot study indicate that MOx correlates with shock severity in a population of trauma patients. Noninvasive and continuous MOx holds promise to aid in patient triage and to evaluate patient condition throughout the course of resuscitation.