In patients complaining common symptoms such as chest/abdominal/back pain or syncope, acute aortic syndromes (AAS) are rare underlying causes. AAS diagnosis requires urgent advanced aortic imaging (AAI), mostly computed tomography angiography. However, patient selection for AAI poses conflicting risks of misdiagnosis and overtesting. We assessed the safety and efficiency of a diagnostic protocol integrating clinical data with point-of-care ultrasound (POCUS) and d-dimer (single/age-adjusted cutoff), to select patients for AAI. This prospective study involved 12 Emergency Departments from 5 countries. POCUS findings were integrated with a guideline-compliant clinical score, to define the integrated pre-test probability (iPTP) of AAS. If iPTP was high, urgent AAI was requested. If iPTP was low and d-dimer was negative, AAS was ruled out. Patients were followed for 30 days, to adjudicate outcomes. Within 1979 enrolled patients, 176 (9 %) had an AAS. POCUS led to net reclassification improvement of 20 % (24 %/-4 % for events/non-events, P < 0.001) over clinical score alone. Median time to AAS diagnosis was 60 min if POCUS was positive vs 118 if negative (P = 0.042). Within 941 patients satisfying rule-out criteria, the 30-day incidence of AAS was 0 % (95 % CI, 0-0.41 %); without POCUS, 2 AAS were potentially missed. Protocol rule-out efficiency was 48 % (95 % CI, 46-50 %) and AAI was averted in 41 % of patients. Using age-adjusted d-dimer, rule-out efficiency was 54 % (difference 6 %, 95 % CI, 4-9 %, vs standard cutoff). The integrated algorithm allowed rapid triage of high-probability patients, while providing safe and efficient rule-out of AAS. Age-adjusted d-dimer maximized efficiency. Clinicaltrials.gov, NCT04430400.

Studies on frequency and underlying diseases causing binocular diplopia in patients presenting to the emergency department (ED) are lacking. To evaluate the prevalence of different diseases causing diplopia and the role of medical history, clinical examination, and unenhanced head computed tomography (UHCT) in the identification of secondary diplopia. Diplopic patients presenting to the ED were enrolled prospectively. Cardiovascular risk factors and associated neurological signs and symptoms were reported. UHCT was performed in the ED. Secondary diplopia was diagnosed in 93 of 260 (35.8%) diplopic patients. Among patients with secondary diplopia, the most frequent diagnoses were stroke (45.2%), multiple sclerosis (18.3%), brain tumors (11.8%), and cerebral aneurysms (7.5%). The prevalence of cardiovascular risk factors was similar in primary and secondary diplopia. Among the 118 (45.4%) patients without associated neurological signs or symptoms (isolated diplopia), secondary diplopia was diagnosed in 13 (11%); UHCT was negative in all 13 cases, with a derived null sensitivity. Eighty of 142 (56.3%) patients with associated signs or symptoms had secondary diplopia. The presence of signs or symptoms associated with diplopia showed a sensitivity of 87% [95% confidence interval (CI): 80-92%] and a specificity of 63% (95% CI: 59-66%) for the diagnosis of secondary diplopia. In this group, UHCT identified 30 of 80 (37.5%) cases, increasing the specificity to 98% (95% CI: 96-99%). One-third of diplopic patients had secondary diplopia. In patients with isolated diplopia, UHCT does not increase diagnostic sensitivity. In patients with associated neurological signs or symptoms, the prevalence of secondary diplopia was high and UHCT showed incremental diagnostic value.

Acute vertigo is defined as the perception of movement of oneself or the surroundings in the absence of actual motion and it is a frequent cause for emergency department admissions. The utilization of medical resources and the duration of hospital stay for this kind of symptom is high. Furthermore, the efficiency of brain imaging in the acute phase is low, considering the limited sensitivity of both CT and MRI for diagnosing diseases that are the causes of central type of vertigo. Relying on imaging tests can provide false reassurance in the event of negative results or prolong the in-hospital work-up improperly. On the other hand, clinical examinations, notably the assessment of nystagmus’ features, have proven to be highly accurate and efficient when performed by experts. Literature data point out that emergency physicians often do not employ these skills or use them incorrectly. Several clinical algorithms have been introduced in recent years with the aim of enhancing the diagnostic accuracy of emergency physicians when evaluating this specific pathology. Both the ‘HINTS and ‘STANDING’ algorithms have undergone external validation in emergency physician hands, showing good diagnostic accuracy. The objective of this consensus document is to provide scientific evidence supporting the clinical decisions made by physicians assessing adult patients with acute vertigo in the emergency department, particularly in cases without clear associated neurological signs. The document aims to offer a straightforward and multidisciplinary approach. At the same time, it tries to delineate benchmarks for the formulation of local diagnostic and therapeutic pathways, as well as provide a base for the development of training and research initiatives.

In acute aortic syndromes (AAS), organ malperfusion represents a key event impacting both on diagnosis and outcome. Increased levels of plasma lactate dehydrogenase (LDH), a biomarker of malperfusion, have been reported in AAS, but the performance of LDH for the diagnosis of AAS and the relation of LDH with outcome in AAS have not been evaluated so far.This was a bi-centric prospective diagnostic accuracy study and a cohort outcome study. From 2008 to 2014, patients from 2 Emergency Departments suspected of having AAS underwent LDH assay at presentation. A final diagnosis was obtained by aortic imaging. Patients diagnosed with AAS were followed-up for in-hospital mortality.One thousand five hundred seventy-eight consecutive patients were clinically eligible, and 999 patients were included in the study. The final diagnosis was AAS in 201 (20.1%) patients. Median LDH was 424 U/L (interquartile range [IQR] 367-557) in patients with AAS and 383 U/L (IQR 331-460) in patients with alternative diagnoses (P < 0.001). Using a cutoff of 450 U/L, the sensitivity of LDH for AAS was 44% (95% confidence interval [CI] 37-51) and the specificity was 73% (95% CI 69-76). Overall in-hospital mortality for AAS was 23.8%. Mortality was 32.6% in patients with LDH ≥ 450 U/L and 16.8% in patients with LDH < 450 U/L (P = 0.006). Following stratification according to LDH quartiles, in-hospital mortality was 12% in the first (lowest) quartile, 18.4% in the second quartile, 23.5% in the third quartile, and 38% in the fourth (highest) quartile (P = 0.01). LDH ≥ 450 U/L was further identified as an independent predictor of death in AAS both in univariate and in stepwise logistic regression analyses (odds ratio 2.28, 95% CI 1.11-4.66; P = 0.025), in addition to well-established risk markers such as advanced age and hypotension. Subgroup analysis showed excess mortality in association with LDH ≥ 450 U/L in elderly, hemodynamically stable and in nonsurgically treated patients.Plasma LDH constitutes a biomarker of poor outcome in patients with AAS. LDH is a rapid and universally available assay that could be used to improve risk stratification and to individualize treatment in patient groups where options are controversial.