Mental health and the effects on methylation of stress-related genes in front-line versus other health care professionals during the second wave of COVID-19 pandemic: an Italian pilot study.

Healthcare workers experienced high degree of stress during COVID-19. Purpose of the present article is to compare mental health (depressive and Post-Traumatic-Stress-Disorders-PTSD-symptoms) and epigenetics aspects (degree of methylation of stress-related genes) in front-line healthcare professionals versus healthcare working in non-COVID-19 wards. Sixty-eight healthcare workers were included in the study: 39 were working in COVID-19 wards (cases) and 29 in non-COVID wards (controls). From all participants, demographic and clinical information were collected by an ad-hoc questionnaire. Depressive and PTSD symptoms were evaluated by the Patient Health Questionnaire-9 (PHQ-9) and the Impact of Event Scale-Revised (IES-R), respectively. Methylation analyses of 9 promoter/regulatory regions of genes known to be implicated in depression/PTSD (ADCYAP1, BDNF, CRHR1, DRD2, IGF2, LSD1/KDM1A, NR3C1, OXTR, SLC6A4) were performed on DNA from blood samples by the MassARRAY EpiTYPER platform, with MassCleave settings. Controls showed more frequent lifetime history of anxiety/depression with respect to cases (χ2 = 5.72, p = 0.03). On the contrary, cases versus controls presented higher PHQ-9 (t = 2.13, p = 0.04), PHQ-9 sleep item (t = 2.26, p = 0.03), IES-R total (t = 2.17, p = 0.03), IES-R intrusion (t = 2.46, p = 0.02), IES-R avoidance (t = 1.99, p = 0.05) mean total scores. Methylation levels at CRHR1, DRD2 and LSD1 genes was significantly higher in cases with respect to controls (p < 0.01, p = 0.03 and p = 0.03, respectively). Frontline health professionals experienced more negative effects on mental health during COVID-19 pandemic than non-frontline healthcare workers. Methylation levels were increased in genes regulating HPA axis (CRHR1) and dopamine neurotransmission (DRD2 and LSD1), thus supporting the involvement of these biological processes in depression/PTSD and indicating that methylation of these genes can be modulated by stress conditions, such as working as healthcare front-line during COVID-19 pandemic.

Prospective comparison of AMB, GAP AND START scores and triage nurse clinical judgement for predicting admission from an ED: a single-centre prospective study.

BACKGROUND: It is postulated that early determination of the need for admission can improve flow through EDs. There are several scoring systems which have been developed for predicting patient admission at triage, although they have not been directly compared. In addition, it is not known if these scoring systems perform better than clinical judgement. Therefore, the aim of this study was to validate existing tools in predicting hospital admission during triage and then compare them with the clinical judgement of triage nurses. METHODS: To conduct this prospective, single-centre observational study, we enrolled consecutive adult patients who presented between 30 September 2019 and 25 October 2019 at the ED of a large teaching hospital in Milan, Italy. For each patient, triage nurses recorded all of the variables needed to perform Ambulatory (AMB), Glasgow Admission Prediction (GAP) and Sydney Triage to Admission Risk Tool (START) scoring. The probability of admission was estimated by the triage nurses using clinical judgement and expressed as a percentage from 0 to 100 with intervals of 5. Nurse estimates were dichotomised for analysis, with ≥50% likelihood being a prediction of admission. Receiver operating characteristic curves were generated for accuracy of the predictions. Area under the curve (AUC) with 95% CI for each of the scores and for the nursing judgements was also calculated. RESULTS: A total of 1710 patients (844 men; median age, 54 years (IQR: 34-75)) and 35 nurses (15 men; median age, 37 years (IQR: 33-48)) were included in this study. Among these patients, 310 (18%) were admitted to hospital from the ED. AUC values for AMB, GAP and START scores were 0.77 (95% CI: 0.74 to 0.79), 0.72 (95% CI: 0.69 to 0.75) and 0.61 (95% CI: 0.58 to 0.64), respectively. The AUC for nurse clinical judgement was 0.86 (95% CI: 0.84 to 0.89). CONCLUSION: AMB, GAP and START scores provided moderate accuracy in predicting patient admission. However, all of the scores were significantly worse than the clinical judgement of the triage nurses.

Multicentre external validation of the Canadian Syncope Risk Score to predict adverse events and comparison with clinical judgement.

BACKGROUND: The Canadian Syncope Risk Score (CSRS) has been proposed for syncope risk stratification in the emergency department (ED). The aim of this study is to perform an external multicenter validation of the CSRS and to compare it with clinical judgement. METHODS: Using patients previously included in the SyMoNE database, we enrolled subjects older than 18 years who presented reporting syncope at the ED. For each patient, we estimated the CSRS and recorded the physician judgement on the patients' risk of adverse events. We performed a 30-day follow-up. RESULTS: From 1 September 2015 to 28 February 2017, we enrolled 345 patients; the median age was 71 years (IQR 51-81), 174 (50%) were men and 29% were hospitalised. Serious adverse events occurred in 43 (12%) of the patients within 30 days. The area under the curve of the CSRS and clinical judgement was 0.75 (95% CI 0.68 to 0.81) and 0.68 (95% CI 0.61 to 0.74), respectively. The risk of adverse events of patients at low risk according to the CSRS and clinical judgement was 6.7% and 2%, with a sensitivity of 70% (95% CI 54% to 83%) and 95% (95% CI 84% to 99%), respectively. CONCLUSION: This study represents the first validation analysis of CSRS outside Canada. The overall predictive accuracy of the CSRS is similar to the clinical judgement. However, patients at low risk according to clinical judgement had a lower incidence of adverse events as compared with patients at low risk according to the CSRS. Further studies showing that the adoption of the CSRS improve patients' outcomes is warranted before its widespread implementation.

Variations in volume of emergency surgeries and emergency department access at a third level hospital in Milan, Lombardy, during the COVID-19 outbreak.

BACKGROUND: During the recent outbreak of COVID-19 (coronavirus disease 2019), Lombardy was the most affected region in Italy, with 87,000 patients and 15,876 deaths up to May 26, 2020. Since February 22, 2020, well before the Government declared a state of emergency, there was a huge reduction in the number of emergency surgeries performed at hospitals in Lombardy. A general decrease in attendance at emergency departments (EDs) was also observed. The aim of our study is to report the experience of the ED of a third-level hospital in downtown Milan, Lombardy, and provide possible explanations for the observed phenomena. METHODS: This retrospective, observational study assessed the volume of emergency surgeries and attendance at an ED during the course of the pandemic, i.e. immediately before, during and after a progressive community lockdown in response to the COVID-19 pandemic. These data were compared with data from the same time periods in 2019. The results are presented as means, standard error (SE), and 95% studentized confidence intervals (CI). The Wilcoxon rank signed test at a 0.05 significance level was used to assess differences in per-day ED access distributions. RESULTS: Compared to 2019, a significant overall drop in emergency surgeries (60%, p < 0.002) and in ED admittance (66%, p ≅ 0) was observed in 2020. In particular, there were significant decreases in medical (40%), surgical (74%), specialist (ophthalmology, otolaryngology, traumatology, and urology) (92%), and psychiatric (60%) cases. ED admittance due to domestic violence (59%) and individuals who left the ED without being seen (76%) also decreased. Conversely, the number of deaths increased by 196%. CONCLUSIONS: During the COVID-19 outbreak the volume of urgent surgeries and patients accessing our ED dropped. Currently, it is not known if mortality of people who did not seek care increased during the pandemic. Further studies are needed to understand if such reductions during the COVID-19 pandemic will result in a rebound of patients left untreated or in unwanted consequences for population health.

Machine Learning and Syncope Management in the ED: The Future Is Coming.

In recent years, machine learning (ML) has been promisingly applied in many fields of clinical medicine, both for diagnosis and prognosis prediction. Aims of this narrative review were to summarize the basic concepts of ML applied to clinical medicine and explore its main applications in the emergency department (ED) setting, with a particular focus on syncope management. Through an extensive literature search in PubMed and Embase, we found increasing evidence suggesting that the use of ML algorithms can improve ED triage, diagnosis, and risk stratification of many diseases. However, the lacks of external validation and reliable diagnostic standards currently limit their implementation in clinical practice. Syncope represents a challenging problem for the emergency physician both because its diagnosis is not supported by specific tests and the available prognostic tools proved to be inefficient. ML algorithms have the potential to overcome these limitations and, in the future, they could support the clinician in managing syncope patients more efficiently. However, at present only few studies have addressed this issue, albeit with encouraging results.

Syncope Time Frames for Adverse Events after Emergency Department Presentation: An Individual Patient Data Meta-Analysis.

Background and Objectives: Knowledge of the incidence and time frames of the adverse events of patients presenting syncope at the ED is essential for developing effective management strategies. The aim of the present study was to perform a meta-analysis of the incidence and time frames of adverse events of syncope patients. Materials and Methods: We combined individual patients' data from prospective observational studies including adult patients who presented syncope at the ED. We assessed the pooled rate of adverse events at 24 h, 72 h, 7-10 days, 1 month and 1 year after ED evaluation. Results: We included nine studies that enrolled 12,269 patients. The mean age varied between 53 and 73 years, with 42% to 57% females. The pooled rate of adverse events was 5.1% (95% CI 3.4% to 7.7%) at 24 h, 7.0% (95% CI 4.9% to 9.9%) at 72 h, 8.4% (95% CI 6.2% to 11.3%) at 7-10 days, 10.3% (95% CI 7.8% to 13.3%) at 1 month and 21.3% (95% CI 15.8% to 28.0%) at 1 year. The pooled death rate was 0.2% (95% CI 0.1% to 0.5%) at 24 h, 0.3% (95% CI 0.1% to 0.7%) at 72 h, 0.5% (95% CI 0.3% to 0.9%) at 7-10 days, 1% (95% CI 0.6% to 1.7%) at 1 month and 5.9% (95% CI 4.5% to 7.7%) at 1 year. The most common adverse event was arrhythmia, for which its rate was 3.1% (95% CI 2.0% to 4.9%) at 24 h, 4.8% (95% CI 3.5% to 6.7%) at 72 h, 5.8% (95% CI 4.2% to 7.9%) at 7-10 days, 6.9% (95% CI 5.3% to 9.1%) at 1 month and 9.9% (95% CI 5.5% to 17) at 1 year. Ventricular arrhythmia was rare. Conclusions: The risk of death or life-threatening adverse event is rare in patients presenting syncope at the ED. The most common adverse events are brady and supraventricular arrhythmias, which occur during the first 3 days. Prolonged ECG monitoring in the ED in a short stay unit with ECG monitoring facilities may, therefore, be beneficial.

Incremental Risk of Intracranial Hemorrhage After Mild Traumatic Brain Injury in Patients on Antiplatelet Therapy: Systematic Review and Meta-Analysis.

BACKGROUND: Mild traumatic brain injury (TBI) is a common event and antiplatelet therapy might represent a risk factor for bleeding. OBJECTIVE: The aim of this study was to evaluate the risk of intracranial hemorrhage (ICH) after mild TBI in patients on antiplatelet therapy through a systematic review and meta-analysis. METHODS: We conducted a systematic review and meta-analysis of prospective and retrospective observational studies on patients with mild TBI on antiplatelet therapy vs. those not on any antithrombotic therapy. The primary outcome was the risk of ICH in patients with mild TBI based on the first computed tomography scan. Secondary outcome was the risk of mortality and neurosurgery. RESULTS: Nine studies and 14,545 patients were included. The incidence of ICH ranged from 3.6% to 29.4% in the antiplatelet group and from 1.6% to 21.1% in the control group. Patients on antiplatelet therapy had a higher risk of ICH after a mild TBI compared with patients that were not on antithrombotic therapy (risk ratio 1.51; 95% confidence interval 1.21-1.88). No difference was found in the composite outcome of mortality and neurosurgery. CONCLUSIONS: Patients on antiplatelet therapy have an increased risk of ICH after mild TBI compared with patients not on antithrombotic therapy. However, the risk is just slightly increased, and the need to perform a computed tomography scan in patients on antiplatelet therapy after a mild TBI should be evaluated case by case, but always considered in patients with other risk factors.

Diagnostic accuracy of ICD-9 code 780.2 for the identification of patients with syncope in the emergency department.

PURPOSE: Syncope is a common condition that affects individuals of all ages and is responsible for 1-3% of all emergency department (ED) visits. Prospective studies on syncope are often limited by the exiguous number of subjects enrolled. A possible alternative approach would be to use of hospital discharge diagnoses from administrative databases to identify syncope subjects in epidemiological observational studies. We assessed the accuracy of the International Classification of Diseases, Ninth Revision (ICD-9) code 780.2 "syncope and collapse" to identify patients with syncope. METHODS: Patients in two teaching hospitals in Milan, Italy with a triage assessment for ED access that was possibly related to syncope were recruited in this study. We considered the index test to be the attribution of the ICD-9 code 780.2 at ED discharge and the reference standard to be the diagnosis of syncope by the ED physician. RESULTS: The sensitivity, specificity, positive and negative predictive values of the ICD-9 code 780.2 to identify patients with syncope were 0.63 (95% confidence interval [CI] 0.58-0.67), 0.98 (95% CI 0.98-0.99), 0.83 (95% CI 0.79-0.87) and 0.95 (95% CI 0.94-0.95), respectively. CONCLUSIONS: The moderate sensitivity of ICD-9 code 780.2 should be considered when the code is used to identify patients with syncope through administrative databases.

Neural networks as a tool to predict syncope risk in the Emergency Department.

AIMS: There is no universally accepted tool for the risk stratification of syncope patients in the Emergency Department. The aim of this study was to investigate the short-term predictive accuracy of an artificial neural network (ANN) in stratifying the risk in this patient group. METHODS AND RESULTS: We analysed individual level data from three prospective studies, with a cumulative sample size of 1844 subjects. Each dataset was reanalysed to reduce the heterogeneity among studies defining abnormal electrocardiogram (ECG) and serious outcomes according to a previous consensus. Ten variables from patient history, ECG, and the circumstances of syncope were used to train and test the neural network. Given the exploratory nature of this work, we adopted two approaches to train and validate the tool. One approach used 4/5 of the data for the training set and 1/5 for the validation set, and the other approach used 9/10 for the training set and 1/10 for the validation set. The sensitivity, specificity, and area under the receiver operating characteristic curve of ANNs in identifying short-term adverse events after syncope were 95% [95% confidence interval (CI) 80-98%], 67% (95% CI 62-72%), 0.69 with the 1/5 approach and 100% (95% CI 84-100%), 79% (95% CI 72-85%), 0.78 with the 1/10 approach. CONCLUSION: The results of our study suggest that ANNs are effective in predicting the short-term risk of patients with syncope. Prospective studies are needed in order to compare ANNs' predictive capability with existing rules and clinical judgment.

Assessment of endothelin and copeptin as biomarkers for vasovagal syncope.

BACKGROUND: The diagnosis of vasovagal syncope continues to be difficult despite the use of accurate histories, tilt testing and implantable loop recorders. A circulating biomarker might be useful to facilitate diagnoses. Both endothelin-1 and vasopressin are increased during positive tilt tests resulting in syncope. Copeptin is a stable cleavage product of vasopressin formation. We conducted a pilot study to assess the utility of endothelin-1 and copeptin as circulating biomarkers of vasovagal syncope. METHODS: Three populations were studied: syncope patients, epilepsy patients and controls. Vasovagal syncope diagnosis was ascertained with the Calgary Syncope Score and epilepsy diagnosis was confirmed with EEG. Plasma levels of endothelin-1 were measured using by ELISA and copeptin levels were determined using an EIA kit. RESULTS: Asymptomatic control subjects had mean age 35 ± 11 years (7/22 male); epileptic subjects had mean age 32 ± 7 years (4/15 male); and syncope subjects had mean age 33 ± 16 years (4 of 21 male). Circulating plasma levels of endothelin-1 and copeptin were no different among the three groups. Mean concentrations of endothelin-1 were as follows: syncope, 23 ± 32 pg/mL; controls, 21 ± 17 pg/mL; and epileptics, 18 ± 12 pg/mL. Mean concentrations of copeptin were as follows: syncope, 1·29 ± 0·79 ng/mL; controls, 1·25 ± 0·79 ng/mL; and seizures, 1·23 ± 0·45 ng/mL. There were no significant correlations between syncope frequency and copeptin or endothelin-1 levels. CONCLUSION: Circulating plasma endothelin-1 and copeptin levels are not significantly different among populations of controls, syncope patients and seizure patients.

Implantable loop recorder versus conventional diagnostic workup for unexplained recurrent syncope.

BACKGROUND: The most recent syncope guideline recommends that implantable loop recorders (ILRs) are implanted in the early phase of evaluation of people with recurrent syncope of uncertain origin in the absence of high-risk criteria, and in high-risk patients after a negative evaluation. Observational and case-control studies have shown that loop recorders lead to earlier diagnosis and reduce the rate of unexplained syncopes, justifying their use in clinical practice. However, only randomised clinical trials with an emphasis on a primary outcome of specific ILR-guided diagnosis and therapy, rather than simply electrocardiogram (ECG) diagnosis, might change clinical practice. OBJECTIVES: To assess the incidence of mortality, quality of life, adverse events and costs of ILRs versus conventional diagnostic workup in people with unexplained syncope. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL, Issue 3, 2015), MEDLINE, EMBASE, ClinicalTrials.gov and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) Search Portal in April 2015. No language restriction was applied. SELECTION CRITERIA: We included all randomised controlled trials of adult participants (i.e. ≥ 18 years old) with a diagnosis of unexplained syncope comparing ILR with standard diagnostic workup. DATA COLLECTION AND ANALYSIS: Two independent review authors screened titles and abstracts of all potential studies we identified as a result of the literature search, extracted study characteristics and outcome data from included studies and assessed risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions. We contacted authors of trials for missing data. We analysed dichotomous data (all-cause mortality and aetiologic diagnosis) as risk ratios (RR) with 95% confidence intervals (CI). We used the Chi(2) test to assess statistical heterogeneity (with P < 0.1) and the I² statistic to measure heterogeneity among the trials. We created a 'Summary of findings' table using the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of a body of evidence as it relates to the studies which contribute data to the meta-analyses for the prespecified outcomes. MAIN RESULTS: We included four trials involving a total of 579 participants. With the limitation that only two studies reported data on mortality and none of them had considered death as a primary endpoint, the meta-analysis showed no evidence of a difference in the risk of long-term mortality between participants who received ILR and those who were managed conventionally at follow-up (RR 0.97, 95% CI 0.41 to 2.30; participants = 255; studies = 2; very low quality evidence) with no evidence of heterogeneity. No data on short term mortality were available. Two studies reported data on adverse events after ILR implant. Due to the lack of data on adverse events in one of the studies' arms, a formal meta-analysis was not performed for this outcome.Data from two trials seemed to show no difference in quality of life, although this finding was not supported by a formal analysis due to the differences in both the scores used and the way the data were reported. Data from two studies seemed to show a trend towards a reduction in syncope relapses after diagnosis in participants implanted with ILR. Cost analyses from two studies showed higher overall mean costs in the ILR group, if the costs incurred by the ILR implant were counted. The mean cost per diagnosis and the mean cost per arrhythmic diagnosis were lower for participants randomised to ILR implant.Participants who underwent ILR implantation experienced higher rates of diagnosis (RR (in favour of ILR) 0.61, 95% CI 0.54 to 0.68; participants = 579; studies = 4; moderate quality evidence), as compared to participants in the standard assessment group, with no evidence of heterogeneity. AUTHORS' CONCLUSIONS: Our systematic review shows that there is no evidence that an ILR-based diagnostic strategy reduces long-term mortality as compared to a standard diagnostic assessment (very low quality evidence). No data were available for short-term all-cause mortality. Moderate quality evidence shows that an ILR-based diagnostic strategy increases the rate of aetiologic diagnosis as compared to a standard diagnostic pathway. No conclusive data were available on the other end-points analysed.Further trials evaluating the effect of ILRs in the diagnostic strategy of people with recurrent unexplained syncope are warranted. Future research should focus on the assessment of the ability of ILRs to change clinically relevant outcomes, such as quality of life, syncope relapse and costs.

Syncope recurrence and mortality: a systematic review.

AIMS: Data on adverse events and death rates following syncope are heterogeneous among studies, and knowledge of syncope prognosis could help to better define the correct management of patients. METHODS AND RESULTS: We performed a systematic review of literature by searching for prospective observational studies enrolling consecutive patients presenting to the Emergency Department because of syncope. The outcomes considered were syncope recurrence and short- and long-term mortality. Morbidity and a composite of morbidity and mortality were also assessed. Pooled event rates and 95% confidence intervals (CI) were calculated for each outcome using the random effects model. Twenty-five studies (11 158 patients) were included. The incidence of syncope relapse linearly increased from 0.3% at 30 days to 22% at 2 years follow-up. One-year mortality rate varied between 5.7 and 15.5%; the pooled estimate was 8.4% (95% CI: 6.7-10.2%). The incidence of adverse events (morbidity) varied between 6.1 and 25.2% at 10 days and 2 years, respectively. The short-term (10 days) pooled incidence of the composite of morbidity and mortality was 9.1% (95% CI: 6.6-12.5%). We found a high statistical heterogeneity between studies. CONCLUSION: This meta-analysis of prospective observational studies shows that the chance of being asymptomatic linearly progressively decreased over time after the first syncope. Short-term (10-30 days) mortality after syncope was <2% and that the overall 10-day rate of the composite endpoint of death and major events was ∼9%. The knowledge of syncope prognosis could help clinicians to understand syncope patients' prognosis and researchers to design future studies.

Priorities for emergency department syncope research.

STUDY OBJECTIVES: There is limited evidence to guide the emergency department (ED) evaluation and management of syncope. The First International Workshop on Syncope Risk Stratification in the Emergency Department identified key research questions and methodological standards essential to advancing the science of ED-based syncope research. METHODS: We recruited a multinational panel of syncope experts. A preconference survey identified research priorities, which were refined during and after the conference through an iterative review process. RESULTS: There were 31 participants from 7 countries who represented 10 clinical and methodological specialties. High-priority research recommendations were organized around a conceptual model of ED decisionmaking for syncope, and they address definition, cohort selection, risk stratification, and management. CONCLUSION: We convened a multispecialty group of syncope experts to identify the most pressing knowledge gaps and defined a high-priority research agenda to improve the care of patients with syncope in the ED.

A large language model-based clinical decision support system for syncope recognition in the emergency department: A framework for clinical workflow integration.

Differentiation of syncope from transient loss of consciousness can be challenging in the emergency department (ED). Natural Language Processing (NLP) enables the analysis of free text in the electronic medical records (EMR). The present paper aimed to develop a large language models (LLM) for syncope recognition in the ED and proposed a framework for model integration within the clinical workflow. Two models, based on both the Italian and Multilingual Bidirectional Encoder Representations from Transformers (BERT) language model, were developed using consecutive EMRs. The "triage" model was only based on notes contained in the "triage" section of the EMR. The "anamnesis" model added data contained in the "medical history" section. Interpretation and calibration plots were generated. The Italian and Multi BERT models were developed and tested on both 15,098 and 15,222 EMRs, respectively. The triage model had an AUC of 0·95 for the Italian BERT and 0·94 for the Multi BERT. The anamnesis model had an AUC of 0·98 for the Italian BERT and 0·97 for Multi BERT. The LLM identified syncope when not explicitly mentioned in the EMR and also recognized common prodromal symptoms preceding syncope. Both models identified syncope patients in the ED with a high discriminative capability from nurses and doctors' notes, thus potentially acting as a tool helping physicians to differentiate syncope from others transient loss of consciousness.

Syncope in the Emergency Department: A Practical Approach.

Syncope is a common condition encountered in the emergency department (ED), accounting for about 0.6-3% of all ED visits. Despite its high frequency, a widely accepted management strategy for patients with syncope in the ED is still missing. Since syncope can be the presenting condition of many diseases, both severe and benign, most research efforts have focused on strategies to obtain a definitive etiologic diagnosis. Nevertheless, in everyday clinical practice, a definitive diagnosis is rarely reached after the first evaluation. It is thus troublesome to aid clinicians' reasoning by simply focusing on differential diagnoses. With the current review, we would like to propose a management strategy that guides clinicians both in the identification of conditions that warrant immediate treatment and in the management of patients for whom a diagnosis is not immediately reached, differentiating those that can be safely discharged from those that should be admitted to the hospital or monitored before a final decision. We propose the mnemonic acronym RED-SOS: Recognize syncope; Exclude life-threatening conditions; Diagnose; Stratify the risk of adverse events; Observe; decide on the Setting of care. Based on this acronym, in the different sections of the review, we discuss all the elements that clinicians should consider when assessing patients with syncope.

How to recognize pulmonary embolism in syncope patients: A simple rule.

BACKGROUND: Syncope can be the presenting symptom of Pulmonary Embolism (PE). It is not known wether using a standardized algorithm to rule-out PE in all patients with syncope admitted to the Emergency Departments (ED) is of value or can lead to overdiagnosis and overtreatment. METHODS: We tested if simple anamnestic and clinical parameters could be used as a rule to identify patients with syncope and PE in a multicenter observational study. The rule's sensitivity was tested on a cohort of patients that presented to the ED for syncopal episodes caused by PE. The clinical impact of the rule was assessed on a population of consecutive patients admitted for syncope in the ED. RESULTS: Patients were considered rule-positive in the presence of any of the following: hypotension, tachycardia, peripheral oxygen saturation ≤ 93 % (SpO2), chest pain, dyspnea, recent history of prolonged bed rest, clinical signs of deep vein thrombosis, history of previous venous thrombo-embolism and active neoplastic disease. The sensitivity of the rule was 90.3 % (95 % CI: 74.3 % to 98.0 %). The application of the rule to a population of 217 patients with syncope would have led to a 70 % reduction in the number of subjects needing additional diagnostic tests to exclude PE. CONCLUSIONS: Most patients with syncope due to PE present with anamnestic and clinical features indicative of PE diagnosis. A clinical decision rule can be used to identify patients who would benefit from further diagnostic tests to exclude PE, while reducing unnecessary exams that could lead to over-testing and over-diagnosis.

The environmental cost of unwarranted variation in the use of magnetic resonance imaging and computed tomography scans.

BACKGROUND: Pollution is a major threat to global health, and there is growing interest on strategies to reduce emissions caused by health care systems. Unwarranted clinical variation, i.e. variation in the utilization of health services unexplained by differences in patient illness or preferences, may be an avoidable source of CO2 when related to overuse. Our objective was to evaluate the CO2 emissions attributable to unwarranted variation in the use of MRI and CT scans among countries of the G20-area. METHODS: We selected seven countries of the G20-area with available data on the use of CT and MRI scans from the organization for Economic Co-operation and Development repository. Each nation's annual electric energy expenditure per 1000 inhabitants for such exams (T-Enex-1000) was calculated and compared with the median and lowest value. Based on such differences we estimated the national energy and corresponding tons of CO2 that could be potentially avoided each year. RESULTS: With available data we found a significant variation in T-Enex-1000 (median value 1782 kWh, range 1200-3079 kWh) and estimated a significant amount of potentially avoidable emissions each year (range 2046-175120 tons of CO2). In practical terms such emissions would need, in the case of Germany, 71900 and 104210 acres of forest to be cleared from the atmosphere, which is 1.2 and 1.7 times the size of the largest German forest (Bavarian National Forest). CONCLUSION: Among countries with a similar rate of development, unwarranted clinical variation in the use of MRI and CT scan causes significant emissions of CO2.

A Hybrid Model for 30-Day Syncope Prognosis Prediction in the Emergency Department.

Syncope is a challenging problem in the emergency department (ED) as the available risk prediction tools have suboptimal predictive performances. Predictive models based on machine learning (ML) are promising tools whose application in the context of syncope remains underexplored. The aim of the present study was to develop and compare the performance of ML-based models in predicting the risk of clinically significant outcomes in patients presenting to the ED for syncope. We enrolled 266 consecutive patients (age 73, IQR 58-83; 52% males) admitted for syncope at three tertiary centers. We collected demographic and clinical information as well as the occurrence of clinically significant outcomes at a 30-day telephone follow-up. We implemented an XGBoost model based on the best-performing candidate predictors. Subsequently, we integrated the XGboost predictors with knowledge-based rules. The obtained hybrid model outperformed the XGboost model (AUC = 0.81 vs. 0.73, p < 0.001) with acceptable calibration. In conclusion, we developed an ML-based model characterized by a commendable capability to predict adverse events within 30 days post-syncope evaluation in the ED. This model relies solely on clinical data routinely collected during a patient's initial syncope evaluation, thus obviating the need for laboratory tests or syncope experienced clinical judgment.