Comparison of out of hospital cardiac arrest due to acute brain injury vs other causes.

BACKGROUND: Acute brain injury (ABI) can cause out of hospital cardiac arrest (OHCA). The aim of this study was to compare clinical features, mortality and potential for organ donation in patients with OHCA due to ABI vs other causes. METHODS: From January 2017 to December 2018, all adult patients presenting to ED for OHCA were considered for the study. Two physicians established the definitive cause of OHCA, according to clinical, laboratory, diagnostic imaging and autoptic findings. Clinical features in patients with OHCA due to ABI or other causes were compared. RESULTS: 280 patients were included in the analysis. ABI was the third most frequent cause of OHCA (21, 7.5%); ABIs were 8 subarachnoid hemorrhage, 8 intracerebral hemorrhage, 2 ischemic stroke, 2 traumatic spinal cord injury and 1 status epilepticus respectively. Neurological prodromes such as seizure, headache and focal neurological signs were significantly more frequent in patients with OHCA due to ABI (OR 5.34, p = 0.03; OR 12.90, p = 0.02; and OR 66.53, p < 0.01 respectively) while among non-neurological prodromes chest pain and dyspnea were significantly more frequent in patients with OHCA due to other causes (OR 14.5, p < 0.01; and OR 10.4, p = 0.02 respectively). Anisocoria was present in 19% of patients with OHCA due to ABI vs 2.7% due to other causes (OR 8.47, p < 0.01). In 90.5% of patients with ABI and in 53.1% of patients with other causes the first cardiac rhythm was non shockable (OR 8.1; p = 0.05). Multivariate logistic regression analysis revealed that older age, active smoking, post-traumatic OHCA, neurological prodromes, anisocoria at pupillary examination were independently associated with OHCA due to ABI. Patients with ABI showed a higher mortality compared with the other causes group (19 pts., 90.5% versus 167 pts., 64.5%; p = 0.015). Potential organ donors were more frequent among ABI than other causes group (10 pts., 47.6% vs 75 pts., 28.9%) however the difference did not reach the statistical significance (p = 0.07). CONCLUSIONS: ABI is the third cause of OHCA. Neurological prodromes, absence of chest pain and dyspnea before cardiac arrest, anisocoria and initial non-shockable rhythm might suggest a neurological etiology of the cardiac arrest. Patients with OHCA due to ABI has an unfavorable outcome, however, they could be candidate to organ donation.

Diagnosis and management of acute aortic syndromes in the emergency department.

Acute aortic syndromes (AASs) are deadly cardiovascular emergencies involving the thoracic aorta. AASs are relatively rare conditions, have unspecific signs and symptoms (including truncal pain, syncope, neurologic deficit and limb ischemia) and require contrast-enhanced tomography angiography (CTA) of the chest and abdomen for conclusive diagnosis and subsequent therapeutic planning. In the Emergency Department (ED), most patients with potential signs/symptoms of AASs are finally found affected by other alternative diagnoses. Hence, misdiagnosis and delayed diagnosis of AASs are major concerns. In critically ill patients, decision to perform CTA is usually straightforward, as exam benefits largely outweigh risks. In patients with ST-tract elevation on ECG, suspected primary ischemic stroke and in stable patients (representing the most prevalent ED scenarios), proper selection of patients necessitating CTA is cumbersome, due to concurrent risks of misdiagnosis and over-testing. Available studies support an algorithm integrating clinical probability assessment, bedside echocardiography and D-dimer (if the clinical probability is not high). Therapeutic management includes medical therapy for all patients including an opioid and anti-impulse drugs (a beta-blocker and a vasodilator), targeting a heart rate of 60 bpm and systolic blood pressure of 100-120 mmHg. Patients with AASs involving the ascending aorta are likely candidate for urgent surgery, and complicated type B AASs (severe aortic dilatation, impending or frank rupture, organ malperfusion, refractory pain, severe hypertension) necessitate evaluation for urgent endovascular treatment. For uncomplicated type B AASs, optimal medical therapy is the current standard of care.

Transesophageal echocardiography (TEE) in cardiac arrest: results of a hands-on training for a simplified TEE protocol.

BACKGROUND: Integration of transesophageal echocardiography (TEE) with Focused Cardiac Ultrasound (FoCUS) can impact decision-making, assist in the diagnosis of reversible etiologies and help guiding resuscitation of patients with cardiac arrest. OBJECTIVE: To evaluate the ability of emergency physicians (EPs) to obtain and maintain skills in performing resusTEE after a course with clinical training in the cardiac surgery theatre. METHODS: Ten EPs without previous TEE experience underwent a resusTEE course, based on a 2-h workshop and an 8-h hands-on training. The training was performed in a cardiac surgery theatre tutored by cardiovascular anesthesiologists. The six taught views were mid-esophageal four-chamber (ME4CH), mid-esophageal long axis (MELAX), mid-esophageal two-chamber (ME2CH), mid-esophageal bicaval view (MEbicaval), transgastric short axis (TGSAX) and aorta view (AOview). The EPs were evaluated by a cardiovascular anesthesiologist at the end of the course as well as after 12 weeks according to a standardized evaluation method. Once the course was completed, resusTEE exams, performed by EPs in Emergency Department (ED), were monitored for a 12-week period. RESULTS: The average assessment of the ten EPs by the tutors was higher than 4 points out of 5, both at the end of the course and after 12 weeks. Probe insertion, acquisition and interpretation of the different views scored on average more than 4 points out of 5 except for TGSAX that showed worsening after 12 weeks. Trainees performed twelve resusTEE exams in ED in patients with out-of-hospital cardiac arrest (OHCA) over 12 weeks after the course. EPs used only four out of six taught views in clinical practice, in the following order of frequency: ME4CH, AOview, MEbicaval and MELAX. CONCLUSIONS: EPs, after a course with clinical training in the cardiac surgery theatre, can successfully acquire and maintain the skills needed to perform resusTEE. However, among the six views learned in the course, EPs used only four of them (ME4CH, MEbicaval, MELAX and AOview).

Integration of transthoracic focused cardiac ultrasound in the diagnostic algorithm for suspected acute aortic syndromes.

AIMS: The diagnosis of acute aortic syndromes (AASs) is challenging and requires integrated strategies. Transthoracic focused cardiac ultrasound (FoCUS) is endorsed by guidelines as a first-line/triage tool allowing rapid bedside assessment of the aorta. However, the performance of FoCUS in the European Society of Cardiology-recommended workup of AASs awaits validation. METHODS AND RESULTS: This was a prespecified subanalysis of the ADvISED multicentre prospective study. Patients with suspected AAS underwent FoCUS for detection of direct/indirect signs of AAS. Clinical probability assessment was performed with the aortic dissection detection risk score (ADD-RS). Case adjudication was based on advanced imaging, surgery, autopsy, or 14-day follow-up. An AAS was diagnosed in 146 (17.4%) of 839 patients. Presence of direct FoCUS signs had a sensitivity and specificity of 45.2% [95% confidence interval (CI) 37-53.6%] and 97.4% (95% CI 95.9-98.4%), while presence of any FoCUS sign had a sensitivity and specificity of 89% (95% CI 82.8-93.6%) and 74.5% (95% CI 71-77.7%) for AAS. The additive value of FoCUS was most evident within low clinical probability (ADD-RS ≤1). Herein, direct FoCUS signs were identified in 40 (4.8%) patients (P < 0.001), including 29 with AAS. ADD-RS ≤1 plus negative FoCUS for AAS rule-out had a sensitivity of 93.8% (95% CI 88.6-97.1%) and a failure rate of 1.9% (95% CI 0.9-3.6%). Addition of negative D-dimer led to a failure rate of 0% (95% CI 0-1.2%). CONCLUSION: FoCUS has additive value in the workup of AASs. Direct FoCUS signs can rapidly identify patients requiring advanced imaging despite low clinical probability. In integrated bundles, negative FoCUS is useful for rule-out of AASs.

Appropriate use of laboratory test requests in the emergency department: a multilevel intervention.

OBJECTIVE: Laboratory test requests in the emergency department (ED) are increasing worldwide. We evaluated whether a multilevel intervention on the basis of the optimization of test profiles and educational meetings with physicians could reduce the number of tests ordered. PATIENTS AND METHODS: In a single-center before and after study design, the 8-month intervention period was compared with the 8-month preintervention period. Laboratory test profiles were reduced from 6 to 2 and the number of tests in each profile was reduced by 50%. All physicians received education about the costs and appropriate use of the tests. Primary outcomes were the number of laboratory blood tests and their costs, with a focus on high-cost tests. Secondary outcomes were ED and laboratory performances (patients' waiting time, number of deaths in ED, re-entry, laboratory turn-around time, and add-on tests). RESULTS: Overall, 61 976 and 61 154 patients were evaluated, respectively, during the intervention and the preintervention period. Laboratory blood test requests were decreased by 207 637 (-36.3%) in the intervention period (P < 0.05), which corresponds to a reduction of 337.3 tests/100 patients. Costs were decreased by 608 079&OV0556; ( - 29.6%, P < 0.05), leading to a cost reduction of 981.2&OV0556;/100 patients. High-cost test requests decreased by 11 457 ( - 27.3%) and contributed toward the overall reduction in costs with 197 206&OV0556; ( - 30.5%). No significant differences were found in ED and laboratory performances between intervention and preintervention periods. CONCLUSIONS: Optimization of test profiles and education on the costs and appropriate use of the tests significantly reduced laboratory test ordering and costs without affecting ED and laboratory performances.

Management of patients presenting with haemoptysis to a Tertiary Care Italian Emergency Department: the Florence Haemoptysis Score (FLHASc).

We analysed the clinical features and diagnostic workup of patients presenting with haemoptysis to an Italian teaching hospital to derive an easy-to-use clinical score to guide risk stratification and initial management in the emergency department (ED). We retrospectively reviewed clinical records of consecutive patients with haemoptysis over 1 year. A pre-specified set of variables, including demographic data, vital signs, type of expectorate (pure blood vs. blood-streaked sputum), comorbidities, and diagnostic tests and treatments was originally registered. The primary outcome was a composite of any of the following: death from any cause, invasive or non-invasive ventilation, Intensive Care Unit admission, blood transfusions or invasive haemostatic procedures. We investigated associations between the pre-specified clinical variables and the primary outcome using a logistic regression analysis. Finally, we derived a score (the Florence Haemoptysis Score, FLHASc) giving a proportional weight to each variable according to the Odds Ratios (OR). We included 197 patients with a median age of 60 years. The first radiological study was a plain chest X-ray in 128 patients (65%). For 33 (17%) patients, a chest computer tomography (CT scan) was the first radiological study. The most common diagnosis was lung malignancy (19% of cases). The diagnosis remained undetermined in one-third of patients. The primary outcome was met by 11.2% of the study population. Systolic blood pressure <100 mmHg (OR 9.7), a history of malignancy (OR 3), the expectoration of pure blood (OR 2.8), and more than 2 episodes of haemoptysis in the prior 24 h (OR 2.5) are found as independent predictors of the primary outcome. The FLHASc ranges from 0 to 6 with a prognostic accuracy of 78% (IC 95%, 68-88%). The primary outcome incidence is 2.4% (IC 95%, 0.2-8.2%) in patients with a FLHASc equal to zero (n = 85, 43%) versus 13.4% (IC 95% 7.8-21.1%) in patients with a FLHASc > 0 (p < 0.01). Among patients with a FLHASc equal to zero, a negative chest X-ray study identifies patients who may be safely discharged. Patients who presented to the ED with haemoptysis experience a heterogeneous management. We derive a simple clinical prognostic score that may rationalize their diagnostic workup.

Diagnostic Accuracy of the Aortic Dissection Detection Risk Score Plus D-Dimer for Acute Aortic Syndromes: The ADvISED Prospective Multicenter Study.

BACKGROUND: Acute aortic syndromes (AASs) are rare and severe cardiovascular emergencies with unspecific symptoms. For AASs, both misdiagnosis and overtesting are key concerns, and standardized diagnostic strategies may help physicians to balance these risks. D-dimer (DD) is highly sensitive for AAS but is inadequate as a stand-alone test. Integration of pretest probability assessment with DD testing is feasible, but the safety and efficiency of such a diagnostic strategy are currently unknown. METHODS: In a multicenter prospective observational study involving 6 hospitals in 4 countries from 2014 to 2016, consecutive outpatients were eligible if they had ≥1 of the following: chest/abdominal/back pain, syncope, perfusion deficit, and if AAS was in the differential diagnosis. The tool for pretest probability assessment was the aortic dissection detection risk score (ADD-RS, 0-3) per current guidelines. DD was considered negative (DD-) if <500 ng/mL. Final case adjudication was based on conclusive diagnostic imaging, autopsy, surgery, or 14-day follow-up. Outcomes were the failure rate and efficiency of a diagnostic strategy for ruling out AAS in patients with ADD-RS=0/DD- or ADD-RS ≤1/DD-. RESULTS: A total of 1850 patients were analyzed. Of these, 438 patients (24%) had ADD-RS=0, 1071 patients (58%) had ADD-RS=1, and 341 patients (18%) had ADD-RS >1. Two hundred forty-one patients (13%) had AAS: 125 had type A aortic dissection, 53 had type B aortic dissection, 35 had intramural aortic hematoma, 18 had aortic rupture, and 10 had penetrating aortic ulcer. A positive DD test result had an overall sensitivity of 96.7% (95% confidence interval [CI], 93.6-98.6) and a specificity of 64% (95% CI, 61.6-66.4) for the diagnosis of AAS; 8 patients with AAS had DD-. In 294 patients with ADD-RS=0/DD-, 1 case of AAS was observed. This yielded a failure rate of 0.3% (95% CI, 0.1-1.9) and an efficiency of 15.9% (95% CI, 14.3-17.6) for the ADD-RS=0/DD- strategy. In 924 patients with ADD-RS ≤1/DD-, 3 cases of AAS were observed. This yielded a failure rate of 0.3% (95% CI, 0.1-1) and an efficiency of 49.9% (95% CI, 47.7-52.2) for the ADD-RS ≤1/DD- strategy. CONCLUSIONS: Integration of ADD-RS (either ADD-RS=0 or ADD-RS ≤1) with DD may be considered to standardize diagnostic rule out of AAS. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02086136.

Differential Diagnosis of Vertigo in the Emergency Department: A Prospective Validation Study of the STANDING Algorithm.

OBJECTIVE: We investigated the reliability and accuracy of a bedside diagnostic algorithm for patients presenting with vertigo/unsteadiness to the emergency department. METHODS: We enrolled consecutive adult patients presenting with vertigo/unsteadiness at a tertiary hospital. STANDING, the acronym for the four-step algorithm we have previously described, based on nystagmus observation and well-known diagnostic maneuvers includes (1) the discrimination between SponTAneous and positional nystagmus, (2) the evaluation of the Nystagmus Direction, (3) the head Impulse test, and (4) the evaluation of equilibrium (staNdinG). Reliability of each step was analyzed by Fleiss' K calculation. The reference standard (central vertigo) was a composite of brain disease including stroke, demyelinating disease, neoplasm, or other brain disease diagnosed by initial imaging or during 3-month follow-up. RESULTS: Three hundred and fifty-two patients were included. The incidence of central vertigo was 11.4% [95% confidence interval (CI) 8.2-15.2%]. The leading cause was ischemic stroke (70%). The STANDING showed a good reliability (overall Fleiss K 0.83), the second step showing the highest (0.95), and the third step the lowest (0.74) agreement. The overall accuracy of the algorithm was 88% (95% CI 85-88%), showing high sensitivity (95%, 95% CI 83-99%) and specificity (87%, 95% CI 85-87%), very high-negative predictive value (99%, 95% CI 97-100%), and a positive predictive value of 48% (95% CI 41-50%) for central vertigo. CONCLUSION: Using the STANDING algorithm, non-sub-specialists achieved good reliability and high accuracy in excluding stroke and other threatening causes of vertigo/unsteadiness.

Causes of diplopia in the emergency department: diagnostic accuracy of clinical assessment and of head computed tomography.

BACKGROUND: Studies on frequency and underlying diseases causing binocular diplopia in patients presenting to the emergency department (ED) are lacking. OBJECTIVE: 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. METHODS: 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. RESULTS: 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%). CONCLUSION: 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.