Identifying patients at imminent risk of death is critical in the management of trauma patients. This study measures the vital sign thresholds associated with death among trauma patients.

This study included data from patients ≥15 years of age in the American College of Surgeons Trauma Quality Improvement Program (TQIP) database. Patients with vital signs of zero were excluded. Documented prehospital and emergency department (ED) vital signs included systolic pressure, heart rate, respiratory rate, and calculated shock index (SI). The area under the receiver operator curves (AUROC) was used to assess the accuracy of these variables for predicting 24-hour survival. Optimal thresholds to predict mortality were identified using Youden’s Index, 90% specificity, and 90% sensitivity. Additional analyses examined patients 70+ years of age.

There were 1,439,221 subjects in the 2019-2020 datasets that met inclusion for this analysis with <0.1% (10,270) who died within 24 hours. The optimal threshold for prehospital systolic pressure was 110, pulse rate was 110, SI was 0.9, and respiratory rate was 15. The optimal threshold for the ED systolic was 112, pulse rate was 107, SI was 0.9, and respiratory rate was 21. Among the elderly sub-analysis, the optimal threshold for prehospital systolic was 116, pulse rate was 100, SI was 0.8, and respiratory rate was 21. The optimal threshold for ED systolic was 121, pulse rate was 95, SI was 0.8, and respiratory rate was 21.

Systolic blood pressure (SBP) and SI offered the best predictor of mortality among trauma patients. The SBP values predictive of mortality were significantly higher than the traditional 90mmHg threshold. This dataset highlights the need for better methods to guide resuscitation as initial vital signs have limited accuracy in predicting subsequent mortality.

We aimed to compare the prognostic accuracy of shock indexes in terms of mortality in patients hospitalized with coronavirus disease 2019 (COVID-19) pneumonia.

Hospitalized patients whose COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR) test results were positive, had thoracic computed tomography (CT) scan performed, and had typical thoracic CT findings for COVID-19 were included in the study.

Eight hundred one patients were included in the study. Chronic obstructive pulmonary disease, congestive heart failure, chronic neurological diseases, chronic renal failure, and a history of malignancy were found to be chronic diseases that were significantly associated with mortality in patients with COVID-19 pneumonia. White blood cell, neutrophil, lymphocyte, C reactive protein, creatinine, sodium, aspartate aminotransferase, alanine aminotransferase, total bilirubin, high sensitive troponin, d-dimer, hemoglobin, and platelet had a statistically significant relationship with in-hospital mortality in patients with COVID-19 pneumonia. The area under the curve (AUC) values of shock index (SI), age shock index (aSI), diastolic shock index (dSI), and modified shock index (mSI) calculated to predict mortality were 0.772, 0.745, 0.737, 0.755, and Youden Index J (YJI) values were 0.523, 0.396, 0.436, 0.452, respectively.

The results of this study show that SI, dSI, mSI, and aSI are effective in predicting in-hospital mortality.

The object of this study was to examine the accuracy in prehospital shock index (SI) for predicting intensive care unit (ICU) requirement and 30-d mortality among from coronavirus disease 2019 (COVID-19) patients transported to the hospital by ambulance.

All consecutive patients who were the age ≥18 y, transported to the emergency department (ED) by ambulance with a suspected or confirmed COVID-19 in the prehospital frame were included in the study. Four different cutoff points were compared (0.7, 0.8, 0.9, and 1.0) to examine the predictive performance of both the mortality and ICU requirement of the SI. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) was used to evaluate each cut-off value discriminatory for predicting 30-d mortality and ICU admission.

The total of 364 patients was included in this study. The median age in the study population was 69 y (range, 55-80 y), of which 196 were men and 168 were women. AUC values for 30-d mortality outcome were calculated as 0.672, 0.674, 0.755, and 0.626, respectively, for threshold values of 0.7, 0.8, 0.9 and 1.0. ICU admission was more likely for the patients with prehospital SI > 0.9. Similarly, the mortality rate was higher in patients with prehospital SI > 0.9.

Early triage of COVID-19 patients will ensure efficient use of health-care resources. The SI could be a helpful, fast, and powerful tool for predicting mortality status and ICU requirements of adult COVID-19 patients. It was concluded that the most useful threshold value for the shock index in predicting the prognosis of COVID-19 patients is 0.9.

The aim of this study is to investigate the accuracy of shock index (SI) and modified shock index (mSI) in predicting the intensive care unit (ICU) requirement and in-hospital mortality among coronavirus disease (COVID-19) patients who are admitted to the emergency department (ED). Likewise, the effects of patients’ conditions such as age, gender, and comorbidity on prognosis will be analyzed.

The files were retrospectively scanned for all COVID-19 patients over the age of 18 years who were admitted to the ED and hospitalized between January 1, 2021, and March 15, 2021. The area under the receiver operating characteristic curve and the area under the curve (AUC) were used to assess each scoring system discriminatory for predicting in-hospital mortality and ICU admission.

There were 464 patients included in this study. The mean age of the patients was 62.4 ± 16.7, of which 245 were men and 219 were women. The most common comorbidity in patients was hypertension (200; 43.1%), followed by chronic obstructive pulmonary disease (174; 37.5%), and coronary artery disease (154; 33.2%). In terms of in-hospital mortality, the AUC of SI, and mSI were 0.719 and 0.739, respectively. In terms of an ICU requirement, the AUC of SI, and mSI were 0.704 and 0.729, respectively.

In this study, it was concluded that SI and mSI are useful in predicting in-hospital mortality and ICU requirement in COVID-19 patients. In addition, another important result of the study is that advanced age, male gender, and hypertension may be associated with a poor prognosis.

Shock is the leading cause of death in multi-trauma patients and must be detected at an early stage to improve prognosis. Many parameters are used to predict clinical condition and outcome in trauma. Computed tomography (CT) signs of hypovolemic shock in trauma patients are not clear yet, requiring further research. The flatness index of inferior vena cava (IVC) is a helpful method for this purpose.

This is a prospective, cross-sectional study which included adult multi-trauma patients (>18 years) who were admitted to the emergency department (ED) and underwent a thoraco-abdominal CT from 2017 through 2018. The main objective of this study was to investigate whether the flatness index of IVC can be used to determine the hypovolemic shock at an early stage in multi-trauma patients, and to establish its relations with shock parameters. The patients’ demographic features, trauma mechanisms, vitals, laboratory values, shock parameters, and clinical outcome within 24 hours of admission were recorded.

Total of 327 (229 males with an average age of 40.9 [SD = 7.93]) patients were included in the study. There was no significant difference in the flatness index of IVC within genders (P = .134) and trauma mechanisms (P = .701); however, the flatness index of IVC was significantly higher in hypotensive (systolic blood pressure [SBP] ≤90 mmHg and/or diastolic blood pressure [DBP] ≤60 mmHg; P = .015 and P = .019), tachycardic (P = .049), and hypoxic (SpO2 ≤%94; P <.001) patients. The flatness index of IVC was also higher in patients with lactate ≥ 2mmol/l (P = .043) and patients with Class III hemorrhage (P = .003). A positive correlation was determined between lactate level and the flatness index of IVC; a negative correlation was found between Glasgow Coma Scale (GCS) and Revised Trauma Score (RTS) with the flatness index of IVC (for each of them, P <.05).

The flatness index of IVC may be a useful method to determine the hypovolemic shock at an early stage in multi-trauma patients.

Traumatic brain injuries (TBIs) are an important cause of mortality and disability around the world. Early intervention and stabilization are necessary to obtain optimal outcomes, yet little is written on the topic in low- and middle-income countries (LMICs). The aim is to provide a descriptive analysis of patients with TBI treated by Service d’Aide Medicale Urgente (SAMU), the prehospital ambulance service in Kigali, Rwanda.

What is the incidence and nature of TBI seen on the ambulance in Kigali, Rwanda?

A retrospective descriptive analysis was performed using SAMU records captured on an electronic database from December 2012 through May 2016. Variables included demographic information, injury characteristics, and interventional data.

Patients with TBIs accounted for 18.0% (n = 2,012) of all SAMU cases. The incidence of TBIs in Kigali was 234 crashes per 100,000 people. The mean age was 30.5 (SD = 11.5) years and 81.5% (n = 1,615) were men. The most common mechanisms were road traffic incidents (RTIs; 78.5%, n = 1,535), assault (10.7%, n=216), and falls (7.8%, n=156). Most patients experienced mild TBI (Glasgow Coma Score [GCS] ≥ 13; 83.5%, n = 1,625). The most common interventions were provision of pain medications (71.0%, n = 1,429), placement of a cervical collar (53.6%, n = 1,079), and administration of intravenous fluids (48.7%, n = 979). In total, TBIs were involved in 67.0% of all mortalities seen by SAMU.

Currently, TBIs represent a large burden of disease managed in the prehospital setting of Kigali, Rwanda. These injuries are most often caused by RTIs and were observed in 67% of mortalities seen by SAMU. Rwanda has implemented several initiatives to reduce the incidence of TBIs with a specific emphasis on road safety. Further efforts are needed to better prevent these injuries. Countries seeking to develop prehospital care capacity should train providers to manage patients with TBIs.

In cases of mass-casualty incidents (MCIs), triage represents a fundamental tool for the management of and assistance to the wounded, which helps discriminate not only the priority of attention, but also the priority of referral to the most suitable center.

The objective of this study was to evaluate the capacity of different prehospital triage systems based on physiological parameters (Shock Index [SI], Glasgow-Age-Pressure Score [GAP], Revised Trauma Score [RTS], and National Early Warning Score 2 [NEWS2]) to predict early mortality (within 48 hours) from the index event for use in MCIs.

This was a longitudinal prospective observational multi-center study on patients who were attended by Advanced Life Support (ALS) units and transferred to the emergency department (ED) of their reference hospital. Collected were: demographic, physiological, and clinical variables; main diagnosis; and data on early mortality. The main outcome variable was mortality from any cause within 48 hours.

From April 1, 2018 through February 28, 2019, a total of 1,288 patients were included in this study. Of these, 262 (20.3%) participants required assistance for trauma and injuries by external agents. Early mortality within the first 48 hours due to any cause affected 69 patients (5.4%). The system with the best predictive capacity was the NEWS2 with an area under the curve (AUC) of 0.891 (95% CI, 0.84-0.94); a sensitivity of 79.7% (95% CI, 68.8-87.5); and a specificity of 84.5% (95% CI, 82.4-86.4) for a cut-off point of nine points, with a positive likelihood ratio of 5.14 (95% CI, 4.31-6.14) and a negative predictive value of 98.7% (95% CI, 97.8-99.2).

Prehospital scores of the NEWS2 are easy to obtain and represent a reliable test, which make it an ideal system to help in the initial assessment of high-risk patients, and to determine their level of triage effectively and efficiently. The Prehospital Emergency Medical System (PhEMS) should evaluate the inclusion of the NEWS2 as a triage system, which is especially useful for the second triage (evacuation priority).

Hemorrhage is the leading cause of preventable death in combat, although early recognition of hemorrhage is still challenging on the battlefield.

The objective of this study was to describe the shock index (SI) in a healthy military population, and to measure its variation during a controlled blood loss, simulated by blood donation.

A prospective observational study that enrolled military subjects, volunteers for blood donation, was conducted. Demographic and clinical information, concerning both the patient and the blood collection, were recorded. Baseline vital signs were measured, before and after donation, in a 45° supine position. Statistical analysis was performed after calculation of SI.

A total of 483 participants were included in the study. The mean blood donation volume was 473mL (SD = 44mL). The median pre- and post-blood donation SI were significantly different: 0.54 (IQR = 0.48-0.63) and 0.57 (IQR = 0.49-0.66), respectively (P = .002). Changes in pre-/post-donation blood pressure (BP) and heart rate (HR) also reached statistical difference but represented a clinically poor relevance. The multivariate analysis showed no significant associations between SI variations and age, sex, body mass index (BMI), sport activities, blood donation volume, and enteral volume replacement (EVR).

In this model of mild hemorrhage, SI exhibited significant variations but failed to reach clinical relevance. Further studies are needed to prove the benefit of SI calculation as a possible parameter for early recognition of hemorrhage in combat casualties at the point of injury.

Pasquier P, Duron S, Pouget T, Carbonnel AC, Boutonnet M, Malgras B, Barbier O, de Saint Maurice G, Sailliol A, Ausset S, Martinaud C. Use of shock index to identify mild hemorrhage: an observational study in military blood donors. Prehosp Disaster Med. 2019;34(3):303–307.

Prehospital ultrasound (PHUS) assessments by physicians and non-physicians are performed on medical and trauma patients with increasing frequency. Prehospital ultrasound has been shown to be of benefit by supporting interventions.

Which patients may benefit from PHUS has not been clearly identified.

A multi-variable logistic regression analysis was performed on a previously created retrospective dataset of five years of physician- and non-physician-performed ultrasound scans in a Canadian critical care Helicopter Emergency Medical Service (HEMS). For separate medical and trauma patient groups, the a-priori outcome assessed was patient characteristics associated with the outcome variable of “PHUS-supported intervention.”

Both models were assessed (Likelihood Ratio, Score, and Wald) as a good fit. For medical patients, the characteristics of heart rate (HR) and shock index (SI) were found to be most significant for an intervention being supported by PHUS. An extremely low HR was found to be the most significant (OR=15.86 [95% confidence interval (CI), 1.46-171.73]; P=.02). The higher the SI, the more likely that an intervention was supported by PHUS (SI 0.9 to<1.3: OR=9.15 [95% CI, 1.36-61.69]; P=.02; and SI 1.3+: OR=8.37 [95% CI, 0.69-101.66]; P=.09). For trauma patients, the characteristics of Prehospital Index (PHI) and SI were found to be most significant for PHUS support. The greatest effect was PHI, where increasing ORs were seen with increasing PHI (PHI 14-19: OR=13.36 [95% CI, 1.92-92.81]; P=.008; and PHI 20-24: OR=53.10 [95% CI, 4.83-583.86]; P=.001). Shock index was found to be similar, though, with lower impact and significance (SI 0.9 to<1.3: OR=9.11 [95% CI, 1.31-63.32]; P=.025; and SI 1.3+: OR=35.75 [95% CI, 2.51-509.81]; P=.008).

In a critical care HEMS, markers of higher patient acuity in both medical and trauma patients were associated with occurrences when an intervention was supported by PHUS. Prospective study with in-hospital follow-up is required to confirm these hypothesis-generating results.

O’DochartaighD, DoumaM, AlexiuC, RyanS, MacKenzieM. Utilization Criteria for Prehospital Ultrasound in a Canadian Critical Care Helicopter Emergency Medical Service: Determining Who Might Benefit. Prehosp Disaster Med. 2017;32(5):536–540.

Severe sepsis and septic shock are common, expensive and often fatal medical problems. The care of the critically sick and injured often begins in the prehospital setting; there is limited data available related to predictors and interventions specific to sepsis in the prehospital arena. The objective of this study was to assess the predictive effect of physiologic elements commonly reported in the out-of-hospital setting in the outcomes of patients transported with sepsis.

This was a cross-sectional descriptive study. Data from the years 2004-2006 were collected. Adult cases (≥18 years of age) transported by Emergency Medical Services to a major academic center with the diagnosis of sepsis as defined by ICD-9-CM diagnostic codes were included. Descriptive statistics and standard deviations were used to present group characteristics. Chi-square was used for statistical significance and odds ratio (OR) to assess strength of association. Statistical significance was set at the .05 level. Physiologic variables studied included mean arterial pressure (MAP), heart rate (HR), respiratory rate (RR) and shock index (SI).

Sixty-three (63) patients were included. Outcome variables included a mean hospital length of stay (HLOS) of 13.75 days (SD = 9.97), mean ventilator days of 4.93 (SD = 7.87), in-hospital mortality of 22 out of 63 (34.9%), and mean intensive care unit length-of-stay (ICU-LOS) of 7.02 days (SD = 7.98). Although SI and RR were found to predict intensive care unit (ICU) admissions, [OR 5.96 (CI, 1.49-25.78; P = .003) and OR 4.81 (CI, 1.16-21.01; P = .0116), respectively] none of the studied variables were found to predict mortality (MAP <65 mmHg: P = .39; HR >90: P = .60; RR >20 P = .11; SI >0.7 P = .35).

This study demonstrated that the out-of-hospital shock index and respiratory rate have high predictability for ICU admission. Further studies should include the development of an out-of-hospital sepsis score.

BaezAA, HanudelP, WilcoxSR. The Prehospital Sepsis Project: Out-of-Hospital Physiologic Predictors of Sepsis Outcomes. Prehosp Disaster Med. 2013;28(6):1-4.