During mass-casualty incidents (MCIs), prehospital triage is performed to identify which patients most urgently need medical care. Formal MCI triage tools exist, but their performance is variable. The Shock Index (SI; heart rate [HR] divided by systolic blood pressure [SBP]) has previously been shown to be an efficient screening tool for identifying critically ill patients in a variety of in-hospital contexts. The primary objective of this study was to assess the ability of the SI to identify trauma patients requiring urgent life-saving interventions in the prehospital setting.

Clinical data captured in the Alberta Trauma Registry (ATR) were used to determine the SI and the “true” triage category of each patient using previously published reference standard definitions. The ATR is a provincial trauma registry that captures clinical records of eligible patients in Alberta, Canada. The primary outcome was the sensitivity of SI to identify patients classified as “Priority 1 (Immediate),” meaning they received urgent life-saving interventions as defined by published consensus-based criteria. Specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated as secondary outcomes. These outcomes were compared to the performance of existing formal MCI triage tools referencing performance characteristics reported in a previously published study.

Of the 9,448 records that were extracted from the ATR, a total of 8,650 were included in the analysis. The SI threshold maximizing Youden’s index was 0.72. At this threshold, SI had a sensitivity of 0.53 for identifying “Priority 1” patients. At a threshold of 1.00, SI had a sensitivity of 0.19.

The SI has a relatively low sensitivity and did not out-perform existing MCI triage tools at identifying trauma patients who met the definition of “Priority 1” patients.

Vital signs are an essential component of the prehospital assessment of patients encountered in an emergency response system and during mass-casualty disaster events. Limited data exist to define meaningful vital sign ranges to predict need for advanced care.

The aim of this study was to identify vital sign ranges that were maximally predictive of requiring a life-saving intervention (LSI) among adults cared for by Emergency Medical Services (EMS).

A retrospective study of adult prehospital encounters that resulted in hospital transport by an Advanced Life Support (ALS) provider in the 2022 National EMS Information System (NEMSIS) dataset was performed. The outcome was performance of an LSI, a composite measure incorporating critical airway, medication, and procedural interventions, categorized into eleven groups: tachydysrhythmia, cardiac arrest, airway, seizure/sedation, toxicologic, bradycardia, airway foreign body removal, vasoactive medication, hemorrhage control, needle decompression, and hypoglycemia. Cut point selection was performed in a training partition (75%) to identify ranges for heart rate (HR), respiratory rate (RR), systolic blood pressure (SBP), oxygen saturation, and Glasgow Coma Scale (GCS) by using an approach intended to prioritize specificity, keeping sensitivity constrained to at least 25%.

Of 18,259,766 included encounters (median age 63 years; 51.8% male), 6.3% had at least one LSI, with the most common being airway interventions (2.2%). Optimal ranges for vital signs included 47-129 beats/minute for HR, 8-30 breaths/minute for RR, 96-180mmHg for SBP, >93% for oxygen saturation, and >13 for GCS. In the test partition, an abnormal vital sign had a sensitivity of 75.1%, specificity of 66.6%, and positive predictive value (PPV) of 12.5%. A multivariable model encompassing all vital signs demonstrated an area under the receiver operator characteristic curve (AUROC) of 0.78 (95% confidence interval [CI], 0.78-0.78). Vital signs were of greater accuracy (AUROC) in identifying encounters needing airway management (0.85), needle decompression (0.84), and tachydysrhythmia (0.84) and were lower for hemorrhage control (0.52), hypoglycemia management (0.68), and foreign body removal (0.69).

Optimal ranges for adult vital signs in the prehospital setting were statistically derived. These may be useful in prehospital protocols and medical alert systems or may be incorporated within prediction models to identify those with critical illness and/or injury for patients with out-of-hospital emergencies.

Involuntary admissions to psychiatric hospitals are on the rise. If patients at elevated risk of involuntary admission could be identified, prevention may be possible. Our aim was to develop and validate a prediction model for involuntary admission of patients receiving care within a psychiatric service system using machine learning trained on routine clinical data from electronic health records (EHRs).

EHR data from all adult patients who had been in contact with the Psychiatric Services of the Central Denmark Region between 2013 and 2021 were retrieved. We derived 694 patient predictors (covering e.g. diagnoses, medication, and coercive measures) and 1134 predictors from free text using term frequency-inverse document frequency and sentence transformers. At every voluntary inpatient discharge (prediction time), without an involuntary admission in the 2 years prior, we predicted involuntary admission 180 days ahead. XGBoost and elastic net models were trained on 85% of the dataset. The models with the highest area under the receiver operating characteristic curve (AUROC) were tested on the remaining 15% of the data.

The model was trained on 50 634 voluntary inpatient discharges among 17 968 patients. The cohort comprised of 1672 voluntary inpatient discharges followed by an involuntary admission. The best XGBoost and elastic net model from the training phase obtained an AUROC of 0.84 and 0.83, respectively, in the test phase.

A machine learning model using routine clinical EHR data can accurately predict involuntary admission. If implemented as a clinical decision support tool, this model may guide interventions aimed at reducing the risk of involuntary admission.

Medical professionals can use mass-casualty triage systems to assist them in prioritizing patients from mass-casualty incidents (MCIs). Correct triaging of victims will increase their chances of survival. Determining the triage system that has the best performance has proven to be a difficult question to answer. The Advanced Prehospital Triage Model (Modelo Extrahospitalario de Triaje Avanzado; META) and Sort, Assess, Lifesaving Interventions, Treatment/Transport (SALT) algorithms are the most recent triage techniques to be published. The present study aimed to evaluate the META and SALT algorithms’ performance and statistical agreement with various standards. The secondary objective was to determine whether these two MCI triage systems predicted patient outcomes, such as mortality, length-of-stay, and intensive care unit (ICU) admission.

This retrospective study used patient data from the trauma registry of an American College of Surgeons Level 1 trauma center, from January 1, 2018 through December 31, 2020. The sensitivity, specificity, and statistical agreement of the META and SALT triage systems to various standards (Revised Trauma Score [RTS]/Sort Triage, Injury Severity Score [ISS], and Lerner criteria) when applied using trauma patients. Statistical analysis was used to assess the relationship between each triage category and the secondary outcomes.

A total of 3,097 cases were included in the study. Using Sort triage as the standard, SALT and META showed much higher sensitivity and specificity in the Immediate category than for Delayed (Immediate sensitivity META 91.5%, SALT 94.9%; specificity 60.8%, 72.7% versus Delayed sensitivity 28.9%, 1.3%; specificity 42.4%, 28.9%). With the Lerner criteria, in the Immediate category, META had higher sensitivity (77.1%, SALT 68.6%) but lower specificity (61.1%) than SALT (71.8%). For the Delayed category, SALT showed higher sensitivity (META 61.4%, SALT 72.2%), but lower specificity (META 75.1%, SALT 67.2%). Both systems showed a positive, though modest, correlation with ISS. For SALT and META, triaged Immediate patients tended to have higher mortality and longer ICU and hospital lengths-of-stay.

Both META and SALT triage appear to be more accurate with Immediate category patients, as opposed to Delayed category patients. With both systems, patients triaged as Immediate have higher mortality and longer lengths-of-stay when compared to Delayed patients. Further research can help refine MCI triage systems and improve accuracy.

The early recognition of patients with sepsis is difficult and the initial assessment outside of hospitals is challenging for ambulance clinicians (ACs). Indicators that ACs can use to recognize sepsis early are beneficial for patient outcomes. Research suggests that elevated point-of-care (POC) plasma glucose and serum lactate levels may help to predict sepsis in the ambulance service (AS) setting.

The aim of this study was to test the hypothesis that the elevation of POC plasma glucose and serum lactate levels may help to predict Sepsis-3 in the AS.

A prospective observational study was performed in the AS setting of Gothenburg in Sweden from the beginning of March 2018 through the end of September 2019. The criteria for sampling POC plasma glucose and serum lactate levels in the AS setting were high or intermediate risk according to the Rapid Emergency Triage and Treatment System (RETTS), as red, orange, yellow, and green if the respiratory rate was >22 breaths/minutes. Sepsis-3 were identified retrospectively. A primary and secondary analyses were carried out. The primary analysis included patients cared for in the AS and emergency department (ED) and were hospitalized. In the secondary analysis, patients who were only cared for in the AS and ED without being hospitalized were also included. To evaluate the predictive ability of these biomarkers, the area under the curve (AUC), sensitivity, specificity, and predictive values were used.

A total of 1,057 patients were included in the primary analysis and 1,841 patients were included in the secondary analysis. In total, 253 patients met the Sepsis-3 criteria (in both analyses). The AUC for POC plasma glucose and serum lactate levels showed low accuracy in predicting Sepsis-3 in both the primary and secondary analyses. Among all hospitalized patients, regardless of Sepsis-3, more than two-thirds had elevated plasma glucose and nearly one-half had elevated serum lactate when measured in the AS.

As individual biomarkers, an elevated POC plasma glucose and serum lactate were not associated with an increased likelihood of Sepsis-3 when measured in the AS in this study. However, the high rate of elevation of these biomarkers before arrival in hospital highlights that their role in clinical decision making at this early stage needs further evaluation, including other endpoints than Sepsis-3.

Acute gastroenteritis (AGE) is one of the most common clinical diagnoses globally, and dehydration in severe AGE cases can cause severe morbidity and mortality. Depending on the metabolic acidosis that occurs in dehydration, the respiratory rate per minute is increased, and the carbon dioxide pressure in the arterial blood is decreased. This condition correlates with end-tidal carbon dioxide (ETCO2). Therefore, this study primarily aims to evaluate whether ETCO2 measurement has a role in detecting metabolic fluid deficit, dehydration level, and regression in dehydration level after fluid replacement and its correlation with Vena Cava Collapsibility Index (VCCI).

This study included spontaneously breathing patients admitted to the emergency department of a tertiary training and research hospital with symptoms of AGE and were thought to be moderately (6.0%-9.0%) and severely (>10.0%) dehydrated according to the Primary Options of Acute Care (POAC) Clinical Dehydration Scale. After the first evaluation, the patients’ vital signs, ETCO2 values, diameters of the inferior vena cava (IVC) in inspiration and expiration, and VCCI were measured and recorded. These measurements were repeated after intravenous (IV) fluid replacement, and finally, a comparison was made between the measurements.

A total of 49 patients, as 16 male (32.7%) and 33 female (67.3%), were included in the study. The mean fluid replacement value was calculated as 664.29 (SD = 259.41) ml. The mean increase in ETCO2 was 3.653 (SD = 2.554) mmHg (P <.001). The mean increase in inferior vena cava expirium (IVCexp) was calculated as 0.402 (SD = 0.280) cm (P <.001) and the mean increase in inferior vena cava inspirium (IVCinsp) as 0.476 (SD = 0.306) cm (P <.001). The VCCI (%) decreased by 12.556 (SD = 13.683) (P <.001). Post-replacement vital signs, ETCO2, and VCCI correlations of the patients were examined and no significant correlation was found between ETCO2 and VCCI (%). As a result of this study, a receiver operating characteristic (ROC) curve was established for the ETCO2 values predicting the level of dehydration and fluid response, and the area under the curve was calculated as 0.748. However, to classify the patient as moderately dehydrated, the ETCO2 cutoff value was determined as 28.5mmHg.

The sensitivity and specificity of ETCO2 levels were 71.43% and 74.29% in evaluating the level of dehydration, and no correlation was found with VCCI, which is known to have high sensitivity and specificity in previous studies in determining the level of dehydration and fluid response. Hence, VCCI measurement made through ultrasonography (USG) is a method that should be preferred more in determining the level of dehydration. Nevertheless, as per the results of this study, swift ETCO2 measurements may be helpful in monitoring the change in the degree of dehydration with treatment in patients who were admitted to the emergency department with dehydration findings and were administered IV fluid replacement therapy.

The European Society of Cardiology (ESC) 2020 guidelines propose an algorithm for in-hospital management of non-ST-elevation myocardial infarction (NSTEMI) based on risk stratification according to clinical, electrocardiographic, and biological data. However, out-of-hospital management is not codified.

The objective of the present study was to evaluate the role of high-sensitivity cardiac troponin-I in out-of-hospital management of NSTEMI by Emergency Medical Services (EMS).

This monocentric, retrospective, observational study analyzed the files of all patients having received a troponin assay in the EMS of Beaujon University Hospital, AP-HP (Paris region, France) from January 1, 2020 through December 31, 2020. Patients were classified as low risk, high risk, or very high risk according to the ESC 2020 algorithm at the time of their hospital treatment. The relationship between troponin in point-of-care and risk level according to time to onset of pain was analyzed using logistic regression. A search for predictors of risk level was performed using multivariate analysis. A P value <.05 was considered significant.

Out of 309 patients in the file, 233 were included. Men were 61% and the median age was 63 years. A positive troponin assay was associated with high-risk or very high-risk stratification regardless of the time to onset of pain (P <.0001). Predictive factors for being classified as high or very high risk in hospital were: a history of atrial fibrillation (P = .03), electrocardiogram (ECG) modifications such as negative T wave or ST-segment depression (P <.0001), and positive troponin (P <.0001).

The use of point-of-care troponin in EMS, combined with clinical and electrical criteria, allows risk stratification of NSTEMI patients from the prehospital management stage and optimization of referral to an appropriate care pathway. Patients classified as low risk should be referred to the emergency department (ED) and patients classified as high risk or very high risk to the cardiac intensive care unit or percutaneous coronary intervention (PCI) center.

Triage - the sorting of patients according to urgency of need for clinical care - is an essential part of delivering effective and efficient emergency care. But when frequent over- or under-triaging occurs, finite time and resources are diverted away from those in greatest need of care and the entire Emergency Medical Services (EMS) system is strained. In resource-constrained settings, such as South Africa, poor triage in EMS only serves to compound other contextual challenges. This study examined the accuracy of dispatcher triage over a one-year period in the Western Cape Government (WCG) EMS system in South Africa.

A retrospective analysis of existing dispatch and EMS data to assess the accuracy of dispatch-assigned priorities was conducted. The mismatch between dispatcher-assigned call priority and triage levels determined by EMS personnel was analyzed via over- and under-triage rates, sensitivity and specificity, and positive and negative predictive values (PPVs and NPVs, respectively).

A total of 185,166 records from December 2016 through November 2017 were analyzed. Across all dispatch complaints, the over-triage rate was 67.6% (95% CI, 66.34-68.76) and the under-triage rate was 16.2% (95% CI, 15.44-16.90). Dispatch triage sensitivity for all included records was 49.2% (95% CI, 48.10-50.38), specificity 71.9% (95% CI, 71.00-72.92), PPV 32.5% (95% CI, 30.02-34.88), and NPV 83.8% (95% CI, 81.93-85.73).

This study provides the first evaluation of dispatch triage accuracy in the WCG EMS system, identifying that the system is suffering from both under- and over-triage. Despite variance across dispatch complaints, both under- and over-triage remained higher than widely accepted norms, and all rates were significantly above acceptable target metrics described in similar studies. Results of this study will be used to motivate the development of more rigorous training programs and resources for WCG EMS dispatchers, including improved dispatch protocols for conditions suffering from high over- and under-triage.

Chest pain is one of the most common reasons for 999 calls and transfers to the emergency department (ED). In these patients, acute myocardial infarction (AMI) is often the diagnosis that clinicians are seeking to exclude. However, only a minority of those patients have AMI, causing a substantial financial burden to health services. Cardiac troponin (cTn) is the reference standard biomarker for the diagnosis of AMI. Several commercially available point-of-care (POC) cTn assays are portable and could feasibly be used in an ambulance. The aim of this paper is to systematically review existing evidence for the use of POC cTn assays in the prehospital setting to rule out AMI.

A systematic search was conducted on EMBASE, MEDLINE, and CINAHL Plus databases, reference lists, and relevant grey literature, including combinations of the relevant terms. Papers published in English language since the year 2000 were eligible for inclusion. A narrative synthesis of the evidence was then undertaken.

The initial search and cross-referencing revealed a total of 350 papers, of which 243 were excluded. Seven papers were included in the systematic literature review.

Current evidence does not support the use of POC troponin assays to exclude AMI due to issues with diagnostic accuracy and insufficient high-quality evidence.

Emergency Medical Services (EMS) systems have developed protocols for prehospital activation of the cardiac catheterization laboratory for patients with suspected ST-elevation myocardial infarction (STEMI) to decrease first-medical-contact-to-balloon time (FMC2B). The rate of “false positive” prehospital activations is high. In order to decrease this rate and expedite care for patients with true STEMI, the American Heart Association (AHA; Dallas, Texas USA) developed the Mission Lifeline PreAct STEMI algorithm, which was implemented in Los Angeles County (LAC; California USA) in 2015. The hypothesis of this study was that implementation of the PreAct algorithm would increase the positive predictive value (PPV) of prehospital activation.

This is an observational pre-/post-study of the effect of the implementation of the PreAct algorithm for patients with suspected STEMI transported to one of five STEMI Receiving Centers (SRCs) within the LAC Regional System. The primary outcome was the PPV of cardiac catheterization laboratory activation for percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG). The secondary outcome was FMC2B.

A total of 1,877 patients were analyzed for the primary outcome in the pre-intervention period and 405 patients in the post-intervention period. There was an overall decrease in cardiac catheterization laboratory activations, from 67% in the pre-intervention period to 49% in the post-intervention period (95% CI for the difference, -14% to -22%). The overall rate of cardiac catheterization declined in post-intervention period as compared the pre-intervention period, from 34% to 30% (95% CI, for the difference -7.6% to 0.4%), but actually increased for subjects who had activation (48% versus 58%; 95% CI, 4.6%-15.0%). Implementation of the PreAct algorithm was associated with an increase in the PPV of activation for PCI or CABG from 37.9% to 48.6%. The overall odds ratio (OR) associated with the intervention was 1.4 (95% CI, 1.1-1.8). The effect of the intervention was to decrease variability between medical centers. There was no associated change in average FMC2B.

The implementation of the PreAct algorithm in the LAC EMS system was associated with an overall increase in the PPV of cardiac catheterization laboratory activation.

Triaging plays an important role in providing suitable care to a large number of casualties in a disaster setting. A Pediatric Physiological and Anatomical Triage Score (PPATS) was developed as a new secondary triage method. This study aimed to validate the accuracy of the PPATS in identifying injured pediatric patients who are admitted at a high frequency and require immediate treatment in a disaster setting. The PPATS method was also compared with the current triage methods, such as the Triage Revised Trauma Score (TRTS).

A retrospective review of pediatric patients aged ≤15 years, registered in the Japan Trauma Data Bank (JTDB) from 2012 through 2016, was conducted and PPATS was performed. The PPATS method graded patients from zero to 22, and was calculated based on vital signs, anatomical abnormalities, and the need for life-saving interventions. It categorized patients based on their priority, and the intensive care unit (ICU)-indicated patients were assigned a PPATS ≥six. The accuracy of PPATS and TRTS in predicting the outcome of ICU-indicated patients was compared.

Of 2,005 pediatric patients, 1,002 (50%) were admitted to the ICU. The median age of the patients was nine years (interquartile range [IQR]: 6-13 years). The sensitivity and specificity of PPATS were 78.6% and 43.7%, respectively. The area under the receiver-operating characteristic (ROC) curve (AUC) was larger for PPATS (0.61; 95% confidence interval [CI], 0.59-0.63) than for TRTS (0.57; 95% CI, 0.56-0.59; P <.01). Regression analysis showed a significant correlation between PPATS and the Injury Severity Score (ISS; r2 = 0.353; P <.001), predicted survival rate (r2 = 0.396; P <.001), and duration of hospital stay (r2 = 0.252; P <.001).

The accuracy of PPATS for injured pediatric patients was superior to that of current secondary triage methods. The PPATS method is useful not only for identifying high-priority patients, but also for determining the priority ranking for medical treatments and evacuation.

Rapid identification of esophageal intubations is critical to avoid patient morbidity and mortality. Continuous waveform capnography remains the gold standard for endotracheal tube (ETT) confirmation, but it has limitations. Point-of-care ultrasound (POCUS) may be a useful alternative for confirming ETT placement. The objective of this study was to determine the accuracy of paramedic-performed POCUS identification of esophageal intubations with and without ETT manipulation.

A prospective, observational study using a cadaver model was conducted. Local paramedics were recruited as subjects and each completed a survey of their demographics, employment history, intubation experience, and prior POCUS training. Subjects participated in a didactic session in which they learned POCUS identification of ETT location. During each study session, investigators randomly placed an ETT in either the trachea or esophagus of four cadavers, confirmed with direct laryngoscopy. Subjects then attempted to determine position using POCUS both without and with manipulation of the ETT. Manipulation of the tube was performed by twisting the tube. Descriptive statistics and logistic regression were used to assess the results and the effects of previous paramedic experience.

During 12 study sessions, from March 2014 through December 2015, 57 subjects participated, evaluating a total of 228 intubations: 113 tracheal and 115 esophageal. Subjects were 84.0% male, mean age of 39 years (range: 22 - 62 years), with median experience of seven years (range: 0.6 - 39 years). Paramedics correctly identified ETT location in 158 (69.3%) cases without and 194 (85.1%) with ETT manipulation. The sensitivity and specificity of identifying esophageal location without ETT manipulation increased from 52.2% (95% confidence interval [CI], 43.0-61.0) and 86.7% (95% CI, 81.0-93.0) to 87.0% (95% CI, 81.0-93.0) and 83.2% (95% CI, 0.76-0.90) after manipulation (P<.0001), without affecting specificity (P=.45). Subjects correctly identified 41 previously incorrectly identified esophageal intubations. Paramedic experience, previous intubations, and POCUS experience did not correlate with ability to identify tube location.

Paramedics can accurately identify esophageal intubations with POCUS, and manipulation improves identification. Further studies of paramedic use of dynamic POCUS to identify inadvertent esophageal intubations are needed.

LemaPC, O’BrienM, WilsonJ, St. JamesE, LindstromH, DeAngelisJ, CaldwellJ, MayP, ClemencyB.Avoid the Goose! Paramedic Identification of Esophageal Intubation by Ultrasound. Prehosp Disaster Med.2018;33(4):406–410