Vasopressors in Trauma: A Never Event?

Vasopressor use in severely injured trauma patients is discouraged due to concerns that vasoconstriction will worsen organ perfusion and result in increased mortality and organ failure in hypotensive trauma patients. Hypotensive resuscitation is advocated based on limited data that lower systolic blood pressure and mean arterial pressure will result in improved mortality. It is classically taught that hypotension and hypovolemia in trauma are associated with peripheral vasoconstriction. However, the pathophysiology of traumatic shock is complex and involves multiple neurohormonal interactions that are ultimately manifested by an initial sympathoexcitatory phase that attempts to compensate for acute blood loss and is characterized by vasoconstriction, tachycardia, and preserved mean arterial blood pressure. The subsequent hypotension observed in hemorrhagic shock reflects a sympathoinhibitory vasodilation phase. The objectives of hemodynamic resuscitation in hypotensive trauma patients are restoring adequate intravascular volume with a balanced ratio of blood products, correcting pathologic coagulopathy, and maintaining organ perfusion. Persistent hypotension and hypoperfusion are associated with worse coagulopathy and organ function. The practice of hypotensive resuscitation would appear counterintuitive to the goals of traumatic shock resuscitation and is not supported by consistent clinical data. In addition, excessive volume resuscitation is associated with adverse clinical outcomes. Therefore, in the resuscitation of traumatic shock, it is necessary to target an appropriate balance with intravascular volume and vascular tone. It would appear logical that vasopressors may be useful in traumatic shock resuscitation to counteract vasodilation in hemorrhage as well as other clinical conditions such as traumatic brain injury, spinal cord injury, multiple organ dysfunction syndrome, and vasodilation of general anesthetics. The purpose of this article is to discuss the controversy of vasopressors in hypotensive trauma patients and advocate for a nuanced approach to vasopressor administration in the resuscitation of traumatic shock.

Regional perfusion monitoring in shock.

PURPOSE OF REVIEW: Despite restoration of adequate systemic blood flow in patients with shock, single organs may remain hypoperfused. In this review, we summarize the results of a literature research on methods to monitor single organ perfusion in shock. We focused on methods to measure heart, brain, kidney, and/or visceral organ perfusion. Furthermore, only methods that can be used in real-time and at the bedside were included. RECENT FINDINGS: We identified studies on physical examination techniques, electrocardiography, echocardiography, contrast-enhanced ultrasound, near-infrared spectroscopy, and Doppler sonography to assess single organ perfusion. SUMMARY: Physical examination techniques have a reasonable negative predictive value to exclude single organ hypoperfusion but are nonspecific to detect it. Technical methods to indirectly measure myocardial perfusion include ECG and echocardiography. Contrast-enhanced ultrasound can quantify myocardial perfusion but has so far only been used to detect regional myocardial hypoperfusion. Near-infrared spectroscopy and transcranial Doppler sonography can be used to assess cerebral perfusion and determine autoregulation thresholds of the brain. Both Doppler and contrast-enhanced ultrasound techniques are novel methods to evaluate renal and visceral organ perfusion. A key limitation of most techniques is the inability to determine adequacy of organ blood flow to meet the organs' metabolic demands.

A comparative study on adequate anesthesia depth: clinical judgement and the Narcotrend® measurement.

PURPOSE: To compare the clinical judgement of electroencephalogram (EEG)-naïve anesthesiologists with an EEG-based measurement of anesthetic depth (AD) using the Narcotrend® monitor. METHODS: In this prospective cohort study including 600 patients, AD during stable anesthesia was assessed by clinical judgement of the attending, EEG-blinded anesthesiologist (using a scale staging the AD as mid-adequate, adequate but fairly deep, or adequate but fairly light) and by simultaneously recorded Narcotrend measurements. RESULTS: In 42% of patients (n = 250), the anesthesiologist's clinical judgement was in agreement with anesthetic levels as measured by the Narcotrend monitor. In 46% of patients (n = 274), the anesthesiologist's judgement and the Narcotrend monitor differed by one AD level (minor discordance). Major discordance was observed in 76 (13%) measurements (judged deeper than measured, n = 29 [5%]; judged lighter than measured, n = 47 [8%]). In 7% of patients (n = 44), the Narcotrend index was outside the limits of adequate AD (too deep, n = 28 [5%]; too superficial, n = 16 [3%]). The overall level of agreement between the anesthesiologist's judgement and the Narcotrend monitor was not statistically significant (Cohen's kappa, -0.039; P = 0.17). Using a random forests algorithm, age, mean blood pressure, the American Society of Anesthesiologists classification, body mass index, and frailty were the variables with the highest relative feature importance to predict the level of agreement. CONCLUSION: These results suggest that clinical judgement of AD during stable anesthesia was not in agreement with EEG-based assessment of anesthetic depth in 58% of cases. Nevertheless, this finding could be influenced by the lack of validated scales to clinically judge AD. TRIAL REGISTRATION: www.clinicaltrials.gov (NCT02766894); registered 10 May, 2016.

RéSUMé: OBJECTIF: Notre objectif était de comparer le jugement clinique d'anesthésiologistes n'ayant pas accès à un électroencéphalogramme (EEG) à une mesure de la profondeur anesthésique (PA) fondée sur l'EEG utilisant le moniteur Narcotrend®. MéTHODE: Dans cette étude de cohorte prospective de 600 patients, la PA a été évaluée pendant la phase de maintien stable de l'anesthésie selon le jugement clinique de l'anesthésiologiste traitant, qui n'avait pas accès à l'EEG (sur une échelle évaluant la PA comme étant adéquate, adéquate mais relativement profonde ou adéquate mais relativement légère) et par des mesures simultanément enregistrées par le Narcotrend. RéSULTATS: Chez 42 % des patients (n = 250), le jugement clinique de l'anesthésiologiste concordait aux niveaux anesthésiques tels que mesurés par le moniteur Narcotrend. Chez 46 % des patients (n = 274), le jugement de l'anesthésiologiste et le moniteur Narcotrend différaient d'un niveau de PA (discordance mineure). Une discordance majeure a été observée dans 76 (13 %) mesures (jugées plus profondes que mesurées, n = 29 [5 %], jugées plus légères que mesurées, n = 47 [8 %]). Chez 7 % des patients (n = 44), l'indice Narcotrend était situé au-delà des limites d'une PA adéquate (trop profond, n = 28 [5 %]; trop superficiel, n = 16 [3 %]). Le niveau global de concordance entre le jugement de l'anesthésiologiste et le moniteur Narcotrend n'était pas significatif d'un point de vue statistique (kappa de Cohen, -0,039; P = 0,17). En se fondant sur un algorithme de forêt d'arbres décisionnels (random forests algorithm), l'âge, la tension artérielle moyenne, la classification selon l'American Society of Anesthesiologists, l'indice de masse corporelle et l'index de fragilité ont été identifiés comme les variables ayant la plus grande importance relative pour prédire le niveau de concordance. CONCLUSION: Ces résultats suggèrent que, dans 58 % des cas, le jugement clinique de la PA ne concordait pas à l'évaluation par EEG de la profondeur anesthésique pendant une phase de maintien stable de l'anesthésie. Toutefois, ces résultats pourraient être influencés par l'absence d'échelles validées pour juger la PA d'un point de vue clinique. ENREGISTREMENT DE L'éTUDE: www.clinicaltrials.gov (NCT02766894); enregistrée le 10 mai 2016.

A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predicts hospital mortality in children with acute infections residing in low- and middle-income countries, using age and other variables collected at hospital admission. DESIGN: Post hoc analysis of a single-center, prospective, before-and-after feasibility trial. SETTING: Rural district hospital in Rwanda, a low-income country in Sub-Sahara Africa. PATIENTS: Infants and children greater than 28 days and less than 18 years of life hospitalized because of an acute infection. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Age, vital signs (heart rate, respiratory rate, and temperature) capillary refill time, altered mental state collected at hospital admission, as well as survival status at hospital discharge were extracted from the trial database. This information was collected for 1,579 adult and pediatric patients admitted to a regional referral hospital with an acute infection in rural Rwanda. Nine-hundred forty-nine children were included in this analysis. We predicted survival in study subjects using random forests, a machine learning algorithm. Five prediction models, all including age plus two to five other variables, were tested. Three distinct optimization criteria of the algorithm were then compared. The in-hospital mortality was 1.5% (n = 14). All five models could predict in-hospital mortality with an area under the receiver operating characteristic curve ranging between 0.69 and 0.8. The model including age, respiratory rate, capillary refill time, altered mental state exhibited the highest predictive value area under the receiver operating characteristic curve 0.8 (95% CI, 0.78-0.8) with the lowest possible number of variables. CONCLUSIONS: A machine learning-based algorithm could reliably predict hospital mortality in a Sub-Sahara African population of 949 children with an acute infection using easily collected information at admission which includes age, respiratory rate, capillary refill time, and altered mental state. Future studies need to evaluate and strengthen this algorithm in larger pediatric populations, both in high- and low-/middle-income countries.

Increasing Evidence-Based Interventions in Patients with Acute Infections in a Resource-Limited Setting: A Before-and-After Feasibility Trial in Gitwe, Rwanda.

OBJECTIVE: To evaluate whether a focused education program and implementation of a treatment bundle increases the rate of early evidence-based interventions in patients with acute infections. DESIGN: Single-center, prospective, before-and-after feasibility trial. SETTING: Emergency department of a sub-Saharan African district hospital. PATIENTS: Patients > 28 days of life admitted to the study hospital for an acute infection. INTERVENTIONS: The trial had three phases (each of four months). Interventions took place during the second (educational program followed by implementation of the treatment bundle) and third (provision of resources to implement treatment bundle) phases. MEASUREMENTS AND MAIN RESULTS: Demographic, clinical, and laboratory data were collected at study enrollment; 24, 48, and 72 hours after hospital admission; and at discharge. A total of 1,594 patients were enrolled (pre-intervention, n = 661; intervention I, n = 531; intervention II, n = 402). The rate of early evidence-based interventions per patient during Intervention Phase I was greater than during the pre-intervention phase (74 ± 17 vs. 79 ± 15%, p < 0.001). No difference was detected when data were compared between Intervention Phases I and II (79 ± 15 vs. 80 ± 15%, p = 0.58). No differences in the incidence of blood transfusion (pre-intervention, 6%; intervention I, 7%; intervention II, 7%) or severe adverse events in the first 24 hours (allergic reactions: pre-intervention, 0.2%; intervention I, 0%; intervention II, 0%; respiratory failure: pre-intervention, 2%; intervention I, 2%; intervention II, 2%; acute renal failure: pre-intervention, 2%; intervention I, 2%; intervention II, 1%) were observed. CONCLUSIONS: Our results indicate that a focused education program and implementation of an infection treatment bundle in clinical practice increased the rate of early evidence-based interventions in patients with acute infections (mostly malaria) admitted to a sub-Saharan African district hospital. Provision of material resources did not further increase this rate. While no safety issues were detected, this could be related to the very low disease severity of the enrolled patient population (www.clinicaltrials.gov: NCT02697513).

Vasopressin in Cardiac Surgery: A Meta-analysis of Randomized Controlled Trials.

OBJECTIVE: To summarize the results of randomized controlled trials on the use of vasopressin as a vasopressor agent in cardiac surgery. DESIGN: Meta-analysis. PARTICIPANTS: Six-hundred-twenty-five adult patients undergoing elective or emergency cardiac surgery. INTERVENTIONS: Arginine vasopressin infusion (n = 313) or control/standard therapy (n = 312). MEASUREMENTS AND MAIN RESULTS: The rates of perioperative complications and postoperative mortality were used as primary and secondary endpoints, respectively. Fixed and/or random effects models were used to compare pooled odds ratios. Arginine vasopressin reduced the pooled odds ratio (OR) of perioperative complications (OR, 0.33; 95% confidence interval [CI], 0.2-0.54; p < 0.0001). A sensitivity analysis excluding the largest trial showed an unchanged reduction in perioperative complications (OR, 0.35; 95% CI, 0.18-0.69; p = 0.002). When analyzing each perioperative complication separately, vasopressin reduced the pooled OR of vasodilatory shock (OR, 0.4; 95% CI, 0.16-0.97; p = 0.04) and new-onset atrial fibrillation (OR, 0.42; 95% CI, 0.21-0.82; p = 0.01). The pooled OR of postoperative death was not different between patients treated with arginine vasopressin and those receiving standard therapy or placebo (OR, 0.83; 95% CI, 0.45-1.53; p = 0.55). The funnel plot for the primary endpoint suggested a relevant publication bias. All included trials suffered from a high risk of bias. CONCLUSION: Our meta-analysis suggests that arginine vasopressin may reduce the rate of perioperative complications in patients undergoing elective or emergency cardiac surgery. No difference in postoperative mortality was observed. An adequately powered multicenter trial is required for reliable estimation of the effects of arginine vasopressin on perioperative complication rates and mortality in cardiac surgical patients.

Association of the Quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) Score With Excess Hospital Mortality in Adults With Suspected Infection in Low- and Middle-Income Countries.

Importance: The quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA) score has not been well-evaluated in low- and middle-income countries (LMICs). Objective: To assess the association of qSOFA with excess hospital death among patients with suspected infection in LMICs and to compare qSOFA with the systemic inflammatory response syndrome (SIRS) criteria. Design, Settings, and Participants: Retrospective secondary analysis of 8 cohort studies and 1 randomized clinical trial from 2003 to 2017. This study included 6569 hospitalized adults with suspected infection in emergency departments, inpatient wards, and intensive care units of 17 hospitals in 10 LMICs across sub-Saharan Africa, Asia, and the Americas. Exposures: Low (0), moderate (1), or high (≥2) qSOFA score (range, 0 [best] to 3 [worst]) or SIRS criteria (range, 0 [best] to 4 [worst]) within 24 hours of presentation to study hospital. Main Outcomes and Measures: Predictive validity (measured as incremental hospital mortality beyond that predicted by baseline risk factors, as a marker of sepsis or analogous severe infectious course) of the qSOFA score (primary) and SIRS criteria (secondary). Results: The cohorts were diverse in enrollment criteria, demographics (median ages, 29-54 years; males range, 36%-76%), HIV prevalence (range, 2%-43%), cause of infection, and hospital mortality (range, 1%-39%). Among 6218 patients with nonmissing outcome status in the combined cohort, 643 (10%) died. Compared with a low or moderate score, a high qSOFA score was associated with increased risk of death overall (19% vs 6%; difference, 13% [95% CI, 11%-14%]; odds ratio, 3.6 [95% CI, 3.0-4.2]) and across cohorts (P < .05 for 8 of 9 cohorts). Compared with a low qSOFA score, a moderate qSOFA score was also associated with increased risk of death overall (8% vs 3%; difference, 5% [95% CI, 4%-6%]; odds ratio, 2.8 [95% CI, 2.0-3.9]), but not in every cohort (P < .05 in 2 of 7 cohorts). High, vs low or moderate, SIRS criteria were associated with a smaller increase in risk of death overall (13% vs 8%; difference, 5% [95% CI, 3%-6%]; odds ratio, 1.7 [95% CI, 1.4-2.0]) and across cohorts (P < .05 for 4 of 9 cohorts). qSOFA discrimination (area under the receiver operating characteristic curve [AUROC], 0.70 [95% CI, 0.68-0.72]) was superior to that of both the baseline model (AUROC, 0.56 [95% CI, 0.53-0.58; P < .001) and SIRS (AUROC, 0.59 [95% CI, 0.57-0.62]; P < .001). Conclusions and Relevance: When assessed among hospitalized adults with suspected infection in 9 LMIC cohorts, the qSOFA score identified infected patients at risk of death beyond that explained by baseline factors. However, the predictive validity varied among cohorts and settings, and further research is needed to better understand potential generalizability.

Autoimmune Encephalitis at the Neurological Intensive Care Unit: Etiologies, Reasons for Admission and Survival.

BACKGROUND: Early recognition and treatment of autoimmune encephalitis (AE) has become an essential issue in clinical practice. However, little is known about patients with deteriorating conditions and the need for intensive care treatment. Here, we aimed to characterize underlying aetiologies, clinical symptoms, reasons for intensive care admission, and mortality of critically ill patients with AE. METHODS: We conducted a retrospective chart review of all patients with "definite" or "probable" diagnoses of AE treated at our neurological intensive care unit between 2002 and 2015. We collected and analyzed clinical, paraclinical, laboratory findings and assessed the mortality at last follow-up based on patient records. RESULTS: Twenty-seven patients [median age 55 years (range 25-87), male = 16] were included. Thirteen (48%) had "definite" AE. The most common reasons for admission were status epilepticus (7/27, 26%) and delirium (4/27, 15%). One-year survival was 82%, all five deceased were male, and 3 (60%) of them had "probable" disease. The non-survivors (median follow-up 1 year) were more likely to have underlying cancer and higher need for respiratory support compared to the survivors (p < 0.041, and p = 0.004, respectively). CONCLUSIONS: Clinical presentations and outcomes in critically ill patients with AE are diverse, and the most common leading cause for intensive care unit admission was status epilepticus. The association of comorbid malignancy and the need for mechanical ventilation with mortality deserves further attention.

Management of potentially life-threatening emergencies at 74 primary level hospitals in Mongolia: results of a prospective, observational multicenter study.

BACKGROUND: While the capacities to care for and epidemiology of emergency and critically ill patients have been reported for secondary and tertiary level hospitals in Mongolia, no data exist for Mongolian primary level hospitals. METHODS: In this prospective, observational multicenter study, 74 primary level hospitals of Mongolia were included. We determined the capacities of these hospitals to manage medical emergencies. Furthermore, characteristics of patients presenting with potentially life-threatening emergencies to these hospitals were evaluated during a 6 month period. RESULTS: An emergency/resuscitation room was available in 62.2% of hospitals. One third of the study hospitals had an operation theatre (32.4%). No hospital ran an intensive care unit or had trained emergency/critical care physicians or nurses available. Diagnostic resources were inconsistently available (sonography, 59.5%; echocardiography, 0%). Basic emergency procedures (wound care, 97.3%; foreign body removal, 86.5%; oxygen application, 85.2%) were commonly but advanced procedures (advanced cardiac life support, 10.8%; airway management, 13.5%; mechanical ventilation, 0%; renal replacement therapy, 0%) rarely available. During 6 months, 14,545 patients were hospitalized in the 74 study hospitals, of which 8.7% [n = 1267; median age, 34 (IQR 18-53) years; male gender, 54.4%] were included in the study. Trauma (excl. brain trauma) (20.4%), acute abdomen (16.9%) and heart failure (9.6%) were the most common conditions. Five-hundred-thirty patients (41.8%) were transferred to a secondary level hospital. The hospital mortality of patients not transferred was 3.2%. CONCLUSIONS: Capacities of Mongolian primary level hospitals to manage life-threatening emergencies are highly limited. Trauma, surgical and medical conditions make up the most common emergencies. In view of the fact that almost half of the patients with a potentially life-threatening emergency were transferred to secondary level hospitals and the mortality of those hospitalized in primary level hospitals was 3.2%, room for improvement is clearly evident. Based on our findings, improvements could be obtained by strengthening inter-hospital transfer systems, training staff in emergency/critical care skills and by making mechanical ventilation and advanced life support techniques available at the emergency rooms of primary level hospitals.

Changes in Left Ventricular Torsion Early Postoperatively After Aortic Valve Replacement and at Long-Term Follow-up.

OBJECTIVE: In patients with aortic stenosis, left ventricular systolic torsion (pT) is increased to overcome excessive afterload. This study assessed left ventricular torsion before and immediately after surgical valve replacement and tested the instant effect of fluid loading. DESIGN: Prospective, clinical single-center study. SETTING: Intensive care unit of a university hospital. PARTICIPANTS: 12 patients undergoing elective aortic valve replacement for aortic stenosis. INTERVENTIONS: Echocardiography was performed on the day before surgery, within 18 hours after surgery including a fluid challenge, and after 2.5 years. MEASUREMENTS AND MAIN RESULTS: pT decreased early postoperatively by 21.2% (23.4° ± 5.6° to 18.4° ± 6.9°; p = 0.012) and reached preoperative values at 2.5 years follow-up (24 ± 7). Peak diastolic untwisting velocity occurred later early postoperatively (13% ± 8% to 21% ± 9.4%; p = 0.019) and returned toward preoperative values at follow-up (10.2 ± 4.7°). The fluid challenge increased central venous pressure (8 ± 4 mmHg to 11 ± 4 mmHg; p = 0.003) and reduced peak systolic torsion velocity (138.7 ± 37.6/s to 121.3 ± 32/s; p = 0.032). pT decreased in 3 and increased in 8 patients after fluid loading. Patients whose pT increased had higher early mitral inflow velocity postoperatively (p = 0.04) than those with decreasing pT. Patients with reduced pT after fluid loading received more fluids (p = 0.04) and had a higher positive fluid balance during the intensive care unit stay (p = 0.03). Torsion after fluid loading correlated with total fluid input (p = 0.001) and cumulative fluid balance (p = 0.002). CONCLUSIONS: pT decreased early after aortic valve replacement but remained elevated despite elimination of aortic stenosis. After 2.5 years, torsion had returned to preoperative levels.

The arterial blood pressure associated with terminal cardiovascular collapse in critically ill patients: a retrospective cohort study.

INTRODUCTION: Liberal and overaggressive use of vasopressors during the initial period of shock resuscitation may compromise organ perfusion and worsen outcome. When transiently applying the concept of permissive hypotension, it would be helpful to know at which arterial blood pressure terminal cardiovascular collapse occurs. METHODS: In this retrospective cohort study, we aimed to identify the arterial blood pressure associated with terminal cardiovascular collapse in 140 patients who died in the intensive care unit while being invasively monitored. Demographic data, co-morbid conditions and clinical data at admission and during the 24 hours before and at the time of terminal cardiovascular collapse were collected. The systolic, mean and diastolic arterial blood pressures immediately before terminal cardiovascular collapse were documented. Terminal cardiovascular collapse was defined as an abrupt (<5 minutes) and exponential decrease in heart rate (> 50% compared to preceding values) followed by cardiac arrest. RESULTS: The mean ± standard deviation (SD) values of the systolic, mean and diastolic arterial blood pressures associated with terminal cardiovascular collapse were 47 ± 12 mmHg, 35 ± 11 mmHg and 29 ± 9 mmHg, respectively. Patients with congestive heart failure (39 ± 13 mmHg versus 34 ± 10 mmHg; P = 0.04), left main stem stenosis (39 ± 11 mmHg versus 34 ± 11 mmHg; P = 0.03) or acute right heart failure (39 ± 13 mmHg versus 34 ± 10 mmHg; P = 0.03) had higher arterial blood pressures than patients without these risk factors. Patients with severe valvular aortic stenosis had the highest arterial blood pressures associated with terminal cardiovascular collapse (systolic, 60 ± 20 mmHg; mean, 46 ± 12 mmHg; diastolic, 36 ± 10 mmHg), but this difference was not significant. Patients with sepsis and patients exposed to sedatives or opioids during the terminal phase exhibited lower arterial blood pressures than patients without sepsis or administration of such drugs. CONCLUSIONS: The arterial blood pressure associated with terminal cardiovascular collapse in critically ill patients was very low and varied with individual co-morbid conditions (for example, congestive heart failure, left main stem stenosis, severe valvular aortic stenosis, acute right heart failure), drug exposure (for example, sedatives or opioids) and the type of acute illness (for example, sepsis).

Continuous Detection of Stimulus Brightness Differences Using Visual Evoked Potentials in Healthy Volunteers with Closed Eyes.

Background/Objectives: We defined the value of a machine learning algorithm to distinguish between the EEG response to no light or any light stimulations, and between light stimulations with different brightnesses in awake volunteers with closed eyelids. This new method utilizing EEG analysis is visionary in the understanding of visual signal processing and will facilitate the deepening of our knowledge concerning anesthetic research. Methods: X-gradient boosting models were used to classify the cortical response to visual stimulation (no light vs. light stimulations and two lights with different brightnesses). For each of the two classifications, three scenarios were tested: training and prediction in all participants (all), training and prediction in one participant (individual), and training across all but one participant with prediction performed in the participant left out (one out). Results: Ninety-four Caucasian adults were included. The machine learning algorithm had a very high predictive value and accuracy in differentiating between no light and any light stimulations (AUCROCall: 0.96; accuracyall: 0.94; AUCROCindividual: 0.96 ± 0.05, accuracyindividual: 0.94 ± 0.05; AUCROConeout: 0.98 ± 0.04; accuracyoneout: 0.96 ± 0.04). The machine learning algorithm was highly predictive and accurate in distinguishing between light stimulations with different brightnesses (AUCROCall: 0.97; accuracyall: 0.91; AUCROCindividual: 0.98 ± 0.04, accuracyindividual: 0.96 ± 0.04; AUCROConeout: 0.96 ± 0.05; accuracyoneout: 0.93 ± 0.06). The predictive value and accuracy of both classification tasks was comparable between males and females. Conclusions: Machine learning algorithms could almost continuously and reliably differentiate between the cortical EEG responses to no light or light stimulations using visual evoked potentials in awake female and male volunteers with eyes closed. Our findings may open new possibilities for the use of visual evoked potentials in the clinical and intraoperative setting.

Emergency critical care: closing the gap between onset of critical illness and intensive care unit admission.

Critical illness is an exquisitely time-sensitive condition and follows a disease continuum, which always starts before admission to the intensive care unit (ICU), in the majority of cases even before hospital admission. Reflecting the common practice in many healthcare systems that critical care is mainly provided in the confined areas of an ICU, any delay in ICU admission of critically ill patients is associated with increased morbidity and mortality. However, if appropriate critical care interventions are provided before ICU admission, this association is not observed. Emergency critical care refers to critical care provided outside of the ICU. It encompasses the delivery of critical care interventions to and monitoring of patients at the place and time closest to the onset of critical illness as well as during transfer to the ICU. Thus, emergency critical care covers the most time-sensitive phase of critical illness and constitutes one missing link in the chain of survival of the critically ill patient. Emergency critical care is delivered whenever and wherever critical illness occurs such as in the pre-hospital setting, before and during inter-hospital transfers of critically ill patients, in the emergency department, in the operating theatres, and on hospital wards. By closing the management gap between onset of critical illness and ICU admission, emergency critical care improves patient safety and can avoid early deaths, reverse mild-to-moderate critical illness, avoid ICU admission, attenuate the severity of organ dysfunction, shorten ICU length of stay, and reduce short- and long-term mortality of critically ill patients. Future research is needed to identify effective models to implement emergency critical care systems in different healthcare systems.

On sepsis, troponin and vasopressin: the bitter truth.

One of the rationales for the use of vasopressin in septic shock has been its potential cardioprotective mechanisms. Lower heart rates, higher arterial pressures, and fewer norepinephrine doses during vasopressin therapy were hypothesized to protect the heart from myocardial ischemia. In a prospective sub-study of the VASST (Vasopressin in Septic Shock Trial) project, Mehta and colleagues specifically evaluated this hypothesis but failed to find lower cardiac biomarkers or fewer ischemic electrocardiogram changes in patients receiving vasopressin compared with subjects receiving norepinephrine alone. After recent evidence of a lacking survival benefit, the present study results further challenge the future role of vasopressin as a vasopressor in septic shock.

Re-thinking resuscitation: leaving blood pressure cosmetics behind and moving forward to permissive hypotension and a tissue perfusion-based approach.

Definitions of shock and resuscitation endpoints traditionally focus on blood pressures and cardiac output. This carries a high risk of overemphasizing systemic hemodynamics at the cost of tissue perfusion. In line with novel shock definitions and evidence of the lack of a correlation between macro- and microcirculation in shock, we recommend that macrocirculatory resuscitation endpoints, particularly arterial and central venous pressure as well as cardiac output, be reconsidered. In this viewpoint article, we propose a three-step approach of resuscitation endpoints in shock of all origins. This approach targets only a minimum individual and context-sensitive mean arterial blood pressure (for example, 45 to 50 mm Hg) to preserve heart and brain perfusion. Further resuscitation is exclusively guided by endpoints of tissue perfusion irrespectively of the presence of arterial hypotension ('permissive hypotension'). Finally, optimization of individual tissue (for example, renal) perfusion is targeted. Prospective clinical studies are necessary to confirm the postulated benefits of targeting these resuscitation endpoints.

The Value of the First Clinical Impression as Assessed by 18 Observations in Patients Presenting to the Emergency Department.

The first clinical impression of emergency patients conveys a myriad of information that has been incompletely elucidated. In this prospective, observational study, the value of the first clinical impression, assessed by 18 observations, to predict the need for timely medical attention, the need for hospital admission, and in-hospital mortality in 1506 adult patients presenting to the triage desk of an emergency department was determined. Machine learning models were used for statistical analysis. The first clinical impression could predict the need for timely medical attention [area under the receiver operating characteristic curve (AUC ROC), 0.73; p = 0.01] and hospital admission (AUC ROC, 0.8; p = 0.004), but not in-hospital mortality (AUC ROC, 0.72; p = 0.13). The five most important features informing the prediction models were age, ability to walk, admission by emergency medical services, lying on a stretcher, breathing pattern, and bringing a suitcase. The inability to walk at triage presentation was highly predictive of both the need for timely medical attention (p < 0.001) and the need for hospital admission (p < 0.001). In conclusion, the first clinical impression of emergency patients presenting to the triage desk can predict the need for timely medical attention and hospital admission. Important components of the first clinical impression were identified.

The value of a machine learning algorithm to predict adverse short-term outcome during resuscitation of patients with in-hospital cardiac arrest: a retrospective study.

Background and importance Guidelines recommend that hospital emergency teams locally validate criteria for termination of cardiopulmonary resuscitation in patients with in-hospital cardiac arrest (IHCA). Objective To determine the value of a machine learning algorithm to predict failure to achieve return of spontaneous circulation (ROSC) and unfavourable functional outcome from IHCA using only data readily available at emergency team arrival. Design Retrospective cohort study. Setting and participants Adults who experienced an IHCA were attended to by the emergency team. Outcome measures and analysis Demographic and clinical data typically available at the arrival of the emergency team were extracted from the institutional IHCA database. In addition, outcome data including the Cerebral Performance Category (CPC) score count at hospital discharge were collected. A model selection procedure for random forests with a hyperparameter search was employed to develop two classification algorithms to predict failure to achieve ROSC and unfavourable (CPC 3-5) functional outcomes. Main results Six hundred thirty patients were included, of which 390 failed to achieve ROSC (61.9%). The final classification model to predict failure to achieve ROSC had an area under the receiver operating characteristic curve of 0.9 [95% confidence interval (CI), 0.89-0.9], a balanced accuracy of 0.77 (95% CI, 0.75-0.79), an F1-score of 0.78 (95% CI, 0.76-0.79), a positive predictive value of 0.88 (0.86-0.91), a negative predictive value of 0.61 (0.6-0.63), a sensitivity of 0.69 (0.66-0.72), and a specificity of 0.84 (0.8-0.88). Five hundred fifty-nine subjects experienced an unfavourable outcome (88.7%). The final classification model to predict unfavourable functional outcomes from IHCA at hospital discharge had an area under the receiver operating characteristic curve of 0.93 (95% CI, 0.92-0.93), a balanced accuracy of 0.59 (95% CI, 0.57-0.61), an F1-score of 0.94 (95% CI, 0.94-0.95), a positive predictive value of 0.91 (0.9-0.91), a negative predictive value of 0.57 (0.48-0.66), a sensitivity of 0.98 (0.97-0.99), and a specificity of 0.2 (0.16-0.24). Conclusion Using data readily available at emergency team arrival, machine learning algorithms had a high predictive power to forecast failure to achieve ROSC and unfavourable functional outcomes from IHCA while cardiopulmonary resuscitation was still ongoing; however, the positive predictive value of both models was not high enough to allow for early termination of resuscitation efforts.