Detection Of Aortic Dissection Research Articles

Deep learning algorithm for detection of aortic dissection on non-contrast-enhanced CT.

To develop a deep learning-based algorithm to detect aortic dissection (AD) and evaluate the diagnostic ability of the algorithm compared with those of radiologists. Included in the study were 170 patients (85 with AD and 85 without AD). An AD detection algorithm was developed using a convolutional neural network with Xception architecture. Of the patient data, 80% were used for training and validation and 20% were used for testing. Fivefold cross-validation was performed to evaluate the method. An average of 6688 non-contrast-enhanced CT images (slice thickness, 5 mm) were used for training. A radiologist reviewed both contrast-enhanced and non-contrast-enhanced images and identified the slices of AD. The identified slices were used as ground truth. Receiver operating characteristic curve and area under the curve (AUC) analysis was performed. Five radiologists independently evaluated the images. The accuracy, sensitivity, and specificity of the algorithm and those of the radiologists were compared. The AUC of the developed algorithm was 0.940, and a cutoff value of 0.400 provided accuracy of 90.0%, sensitivity of 91.8%, and specificity of 88.2%. For the radiologists, median (range) accuracy, sensitivity, and specificity were 88.8 (83.5-94.1)%, 90.6 (83.5-94.1)%, and 94.1 (72.9-97.6)%, respectively. There was no significant difference in performance in terms of accuracy, sensitivity, or specificity between the algorithm and the average performance of the radiologists (p > 0.05). The developed algorithm showed comparable diagnostic performance to radiologists for detecting AD, which suggests the potential of the proposed method to support clinical practice by reducing missed ADs. • A deep learning-based algorithm for detecting aortic dissection was developed using the non-contrast-enhanced CT images of 170 patients. • The algorithm had an AUC of 0.940 for detecting aortic dissection. • The accuracy, sensitivity, and specificity of the algorithm were comparable to those of radiologists.

A deep learning algorithm using contrast-enhanced computed tomography (CT) images for segmentation and rapid automatic detection of aortic dissection

Aortic dissection (AD) is one of the most common aortic diseases, where blood enters the aortic wall through the aortic intimal rift and causes separation of the arterial wall. Any delay or misdiagnosis can have severe consequences for patients with aortic dissection and even lead to higher mortality rates. Therefore, rapid and accurate detection of aortic dissection saves patients valuable time and provides assistance for the selection of clinical treatment options. This paper describes a deep learning algorithm that uses contrast-enhanced CT images for segmentation and automatic detection of aortic dissection. First, we construct a U-Net based semantic segmentation architecture and apply it to contrast-enhanced CT images to segment the aortic true lumen. Then, we use the segmentation results for aortic circularity analysis to obtain slice-level detection results. Finally, we aggregated the slice-level results to present patient-level detection results. We tested our algorithm on 20 contrast-enhanced CT datasets, of which 10 were aortic dissections. In terms of temporal performance, we have achieved millisecond prediction on sliced images. At the same time, we achieved 85.00% accuracy, 90.00% sensitivity and 80.00% specificity in patient-level testing.

What is the distribution of Aortic Dissection Detection Risk Score in an undifferentiated emergency department chest pain population?

To determine the distribution of Aortic Dissection Detection Risk Score (ADDRS) in undifferentiated chest pain patients. Prospective observational study of adult patients presenting to the ED with non-traumatic chest pain. Of 139 patients studied, more than 75% of patients has an ADDRS ≥1, mainly because of the report of severe pain. There were no aortic dissections. In patients with non-specific chest pain, testing driven by the ADDRS protocol would have seen a 280% increase in d-dimer testing and 2200% increase in computed tomography aortogram rates. Widespread use of the ADDRS and its investigation protocol cannot be supported.

Detection, segmentation, simulation and visualization of aortic dissections: A review.

Aortic dissection (AD) is a condition of the main artery of the human body, resulting in the formation of a new flow channel, or false lumen. The disease is usually diagnosed with a computed tomography angiography scan during the acute phase. A better understanding of the causes of AD requires knowledge of the aortic geometry (segmentation), including the true and false lumina, which is very time-consuming to reconstruct when performed manually on a slice-by-slice basis. Hence, different automatic and semi-automatic medical image analysis approaches have been proposed for this task over the last years. In this review, we present and discuss these computing techniques used to segment dissected aortas, also in regard to the detection and visualization of clinically relevant information and features from dissected aortas for customized patient-specific treatments.

P122: The evaluation of various point of care ultrasound features in Stanford type A aortic dissections

Introduction: Type A aortic dissection(AD) is one of the most lethal diseases in medicine. Its mortality rate increases 1-2% per hour from the onset of symptoms to treatment. Timely diagnoses of ADs, therefore, are crucial to improve survival and decrease morbidity. There are various proposed clinical guidelines to help emergency physicians decide when a CTA is urgently needed with most widely quoted being the validated Aortic Dissection Detection Risk Score(ADD-RS) recommended by the American Heart Association. The addition of D-Dimer for further risk stratification has also been entertained. A recent article published in the American Journal of Emergency recommends using point of care ultrasound(POCUS) to expedite diagnosis. With the rising use of POCUS in the emergency department, it can be the missing link to timely AD diagnoses. This project aims to elucidate the prevalence of positive POCUS findings (pericardial effusion and dilated aortic root) in type A AD via a retrospective chart review. Methods: This study is a retrospective chart review of 200 patients with the diagnosis of AD treated at Southlake Regional Hospital. We included patients diagnosed with type A AD and excluded those diagnosed with type B AD. We collected data on their demographics, ADD-RS scores, investigation results, treatments, and clinical outcomes. The main focus of the chart review was on the presence of pericardial effusion or dilated aortic root on echocardiograms. Binomial statistical analysis was used to analyze the collected data. Results: We identified 126 patients with type A AD out of 200 charts reviewed. Thirteen (14% CI 8-23%, n = 93 p = 0.05) had wide mediastinum on their chest X-rays; twenty (95% CI 75-100%, n = 21 P = 0.05) had elevated D-dimer levels; and ninety-one (72% CI 64-80%, n = 126 p = 0.05) had positive ADD-RS. Only 88 out of 126 AD cases had documented echocardiograms. Sixty-eight (77% CI 67-86%, n = 88 p = 0.05) had either pericardial effusions or dilated aortic roots on their echocardiograms. Eighty-one (92% CI 84-95%, n = 88 p = 0.05) had either positive ADD-RS or positive echocardiogram findings, which is 20 (23% CI 14-33%, n = 88 P = 0.05) more cases than ADD-RS would have picked up alone. Conclusion: The absence of both pericardial effusion and dilated aortic root on echocardiogram in combination with a negative ADD-RS has a high sensitivity for ruling out type A AD. Our data support further research into the use of POCUS to expedite the diagnosis of type A AD in the emergency department.

Systematic Review of Aortic Dissection Detection Risk Score Plus D-dimer for Diagnostic Rule-out Of Suspected Acute Aortic Syndromes.

In patients at low clinical probability of acute aortic syndromes (AASs), decision on advanced aortic imaging is cumbersome. Integration of the aortic dissection detection risk score (ADD-RS) with D-dimer (DD) provides a potential pipeline for standardized diagnostic rule-out. We systematically reviewed and summarized supporting data. Cross-sectional studies assessing integration of ADD-RS with DD for diagnosis of AASs were identified on MEDLINE, EMBASE and Web Of Science databases. Two reviewers independently screened articles, assessed quality, and extracted data. The quality of design and reporting was evaluated with the QUADAS-2 and STARD tools. Individual patient data were obtained, to allow analysis of both conventional (500ng/mL) and age-adjusted (DDage-adj ) DD cutoffs. Data were summarized for four diagnostic strategies combining ADD-RS=0 or≤1, with DD<500ng/mL or<DDage-adj . The statistical heterogeneity of the diagnostic variables was estimated with Higgins' I2 . Pooled values were calculated for variables showing nonsignificant heterogeneity. After screening of 680 studies, four articles (including a total of 3,804 patients) met inclusion criteria. One prospective study provided a low risk of bias/applicability concerns, while methodologic limitations were found in the other three retrospective studies. Statistical heterogeneity was negligible for sensitivity and negative likelihood ratio (LR) values and significant for specificity and positive LR values of all diagnostic strategies. Pooled sensitivity was 99.9% (95% confidence interval [CI]=99.3% to 100%, I2 =0) for ADD-RS=0 and DD<500ng/mL or<DDage-adj , 98.9% (95% CI=97.9% to 99.9%, I2 =0) for ADD-RS≤1 and DD<500ng/mL, and 97.6% (95% CI=96.3% to 98.9%, I2 =0) for ADD-RS≤1 and DD<DDage-adj . Despite methodologic limitations, integration of ADD-RS=0 or≤1 with DD<500ng/mL shows negligible heterogeneity and consistently high sensitivity across studies, thus supporting reliability for diagnostic rule-out of AASs. Data supporting ADD-RS=0 plus DDage-adj appear preliminary and require further scrutiny.

Automatic Detection of Aortic Dissection Based on Morphology and Deep Learning

Aortic dissection (AD) is a kind of acute and rapidly progressing cardiovascular disease. In this work, we build a CTA image library with 88 CT cases, 43 cases of aortic dissection and 45 cases of health. An aortic dissection detection method based on CTA images is proposed. ROI is extracted based on binarization and morphology opening operation. The deep learning networks (InceptionV3, ResNet50, and DenseNet) are applied after the preprocessing of the datasets. Recall, F1-score, Matthews correlation coefficient (MCC) and other performance indexes are investigated. It is shown that the deep learning methods have much better performance than the traditional method. And among those deep learning methods, DenseNet121 can exceed other networks such as ResNet50 and InceptionV3.

Integrated Use of Conventional Chest Radiography Cannot Rule Out Acute Aortic Syndromes in Emergency Department Patients at Low Clinical Probability.

Guidelines recommend chest radiography (CR) in the workup of suspected acute aortic syndromes (AASs) if the pretest clinical probability is low. However, the diagnostic impact of CR integration for the rule-in and rule-out of AASs is unknown. We performed a secondary analysis of the ADvISED multicenter study. Emergency department outpatients were eligible if an AAS was clinically suspected. Clinical probability was defined with the aortic dissection detection risk score (ADD-RS). CR was evaluated blindly by a radiologist, who judged on mediastinum enlargement (ME) and other signs. In 2014 through 2016, a total of 1,129 patients were enrolled and 1,030 were analyzed, including 48 (4.7%) with AASs. ADD-RS/ME and ADD-RS/any CR sign (aCRs) integration were more accurate than ADD-RS alone (area under the curve= 0.8 and 0.78 vs. 0.66, p<0.001). The sensitivity and specificity of the integrated strategies were 66.7% (95% confidence interval [CI]= 51.5% to 79.9%) and 82.5% (95% CI= 79.9% to 84.8%) for ADD-RS/ME and 68.8% (95% CI= 53.6% to 80.9%) and 76.5% (95% CI= 73.7% to 79.1%) for ADD-RS/aCRs, respectively. The sensitivity and specificity of CR per se were 54.2% (95% CI= 39.2% to 68.6%) and 92.4% (95% CI= 90.5% to 93.9%) for ME and 60.4% (95% CI= 45.3% to 74.2%) and 85.2% (95% CI= 82.9% to 87.4%) for aCRs. The agreement (κ) between attending physicians and radiologists for ME was 0.44 (95% CI= 0.35 to 0.54). ADD-RS/ME rule-in (ADD-RS ≤ 1 and ME-present, or ADD-RS>1) applied to 204 versus 130 patients with ADD-RS>1, including 14 with AAS and 60 false-positives (FP). ADD-RS/aCRs rule-in (ADD-RS ≤ 1 and aCRs-present, or ADD-RS>1) applied to 264 patients, including 15 with AAS and 119 FP. ADD-RS/ME rule-out (ADD-RS ≤ 1 and ME-absent) applied to 826 (80.2%) patients, including 16 with AAS (33.3% of cases). ADD-RS/aCRs rule-out (ADD-RS ≤ 1 and aCRs-absent) applied to 766 patients (74.4%), including 15 with AAS (31.3% of cases). CR integration with clinical probability assessment showed modest rule-in efficiency and insufficient sensitivity for conclusive rule-out.

Aortální disekce a jiné akutní aortální syndromy na urgentním příjmu

Acute aortic syndromes are emergent life-threatening conditions affecting the aorta, which actual incidence is difficult to determine. Mortality of untreated patients increases steadily over time, so early diagnosis and initiation of therapy are crucial. Management of patients in Czech Republic follow, similar as in other European countries, the European Society of Cardiology guidelines from 2014, which were updated in 2018. The basis for diagnosis consists of history, physical examination, ECG, determination of vital signs, hemodynamic status and stratification of dia-gnosis probability by ADD-RS (aortic dissection detection risk score). This is followed by a series of laboratory and imaging examinations, of which the D-dimer, CT aortography and echocardiography are the most important. Recent studies show the benefit of combination of ADD-RS with D-dimer or measurement of ascendant aorta diameter by echocardiography. New emerging biomarkers are currently under investigation. Thanks to advances in technology, magnetic resonance imaging could take place as emergent diagnostic tool in the future. Initial therapy depends on the hemodynamic status of the patient. It must be followed by definitive therapy. In this publication we summarize the approach to a patient with acute aortic syndrome in the emergency department focusing on aortic dissection as its most common type.

Numerical Simulation of Conductivity Changes in the Human Thorax Caused by Aortic Dissection

In case of an aortic dissection (AD), the aortic shape as well as the blood flow will be altered in the region concerned. Based on the thoracic electrical bioimpedance technique that allows to identify and quantify conductivity changes by measuring the impedance on the thorax, a numerical simulation model for investigating effects caused by ADs is proposed. In order to find a simple non-invasive method for the detection of ADs, the possibilities and limits of applying a bioimpedance technique are shown in this paper.

In Vivo Detection and Measurement of Aortic Aneurysm and Dissection in Mouse Models Using Microcomputed Tomography with Contrast Agent.

Objectives The aim of this study was to evaluate the potential of microcomputed tomography (micro-CT) using the intravascular contrast agent ExiTron nano 12000 for aorta imaging and monitoring the dynamic changing process of the aorta in mouse models with aortic aneurysm and dissection. Materials and Methods Experiments were performed on healthy mice and mice with aortic dissection. Mice that were developing aortic dissection and healthy mice underwent micro-CT imaging after injection of ExiTron nano 12000. Time-dependent signal enhancement (at 1, 2, 3, 6, and 12 hours after intravenous injection of the contrast agent, respectively) in the aorta of healthy mice was measured to confirm the optimal imaging time of aorta. Various contrast agent doses (70, 100, and 150 μl per 25 g mouse, respectively) were investigated to determine the optimal required dose for imaging of the aorta. The mice were scanned with micro-CT at 1, 14, and 28 days after onset of aneurysm and dissection to monitor the dynamic changing process of the aorta. Mouse aortas were stained with hematoxylin and eosin staining, and the diameter of the aorta was measured and compared with those obtained by micro-CT. Results Time-dependent signal enhancement in the aorta shows that the contrast agent has a long blood half-life of 6 hours, with a peak enhancement at 2 hours after injection. Injection of 100 μl ExiTron nano 12000 per 25 g mouse allows for effective visualization of the aorta. Micro-CT combined with contrast agent can monitor the changing process of the aorta in the mouse model of aortic aneurysm and dissection dynamically. The values of the diameter of the aortas obtained from the in vivo micro-CT imaging were compared with those obtained from histology and showed a significant correlation (R2 = 0.96). Conclusions These data demonstrate that in vivo micro-CT is an accurate and feasible technique to detect aortic aneurysm or dissection in a mouse model, and the micro-CT technique using the innovative contrast agent ExiTron nano 12000 allows for monitoring various processes dynamically such as aortic remodeling in longitudinal studies.

Aortic Dissection Detection Risk Score: A Clinical Decision Rule That Needs Some Parenting

Aortic Dissection Detection Risk Score: A Clinical Decision Rule That Needs Some Parenting

What Is the Specificity of the Aortic Dissection Detection Risk Score in a Low-prevalence Population?

Acute aortic syndrome (AAS) is a time-sensitive and difficult-to-diagnose aortic emergency. The American Heart Association (AHA) proposed the acute aortic dissection detection risk score (ADD-RS) as a means to reduce miss rate and improve time to diagnosis. Previous validation studies were performed in a high prevalence population of patients. We do not know how the rule will perform in a lower-prevalence population. This is important because application of a rule with low specificity would increase imaging rates and complications. Our goal was to assess if the diagnostic accuracy of the score would be maintained in a low-prevalence population that we are attempting to risk stratify in the emergency department (ED). Retrospective cohort of patients age 18 years old and older who presented to two tertiary care EDs from January 1, 2015, to December 31, 2015, and underwent a computed tomographic angiography to rule out AAS. Two trained reviewers extracted data using a standardized data collection form. AAS was defined according to accepted radiologic standards. The components of the AHA risk score were defined a priori. Agreement was measured using kappa statistic. Sensitivity, specificity, and positive and negative likelihood ratios with 95% confidence intervals (CIs) were calculated. Analysis was performed using SAS 9.4 University Edition. A total 370 patients underwent computed tomography for suspected AAS. Chief presenting symptoms were chest pain (207, 58%), back pain (26, 7%), abdominal pain (32, 8.6%), syncope (7, 2.6%), and symptoms of stroke (6, 1.6%). AAS was finally diagnosed in 12 (3.2%) patients: five (1.4%) type A aortic dissection, four (1%) type B aortic dissection, two (0.5%) an aortic intramural hematoma, no penetrating aortic ulcer, and one a ruptured abdominal aortic aneurysm. The presence of one or more ADD risk markers (ADD-RS ≥ 1) was associated with a sensitivity of 100% (95% CI= 73.5%-100%) and a specificity of 12.3% (95% CI= 9.1%-16.2%) for the diagnosis of AAS. The negative likelihood ratio was 0 and the positive likelihood ratio was 1.14 (95% CI= 1.1-1.2). Our study confirms that in North America the prevalence of AAS in those undergoing advanced imaging is low. The ADD-RS in this population has a low specificity. A lack of defined inclusion criteria and a low specificity limits the application of this rule in practice.

Endoscopic Ultrasound Isolates Type B Aortic Dissection

An aortic dissection (AD) occurs when the inner layer of the aorta tears. ADs have a predilection toward men and those aged 60 to 70 [1]. Type A aortic dissections are more dangerous due to the tear situated in the ascending aorta whereas Type B is more rare with the tear limited to the descending aorta. Symptoms of aortic dissections such as chest pain are similar to other cardiovascular conditions, making aortic dissection detection tricky [1,2]. We report a 74 year old female with constant chest pain radiating from the right breast to the right upper quadrant after eating Chinese food for dinner. The pain was accompanied with non-radiating back pain and nausea. Physical examination was significant for a tender mass palpated in the right upper and lower quadrants. Right upper quadrant ultrasound showed choledocholithiasis with common bile duct dilation at 1.1cm, unchanged from 1 year prior, and sludge in the gallbladder but no cholecystitis. Her vitals were stable with mild hypertension (149/67 mmHg). Endoscopic ultrasound examination showed a gallbladder filled with stones and sludge as well as a thickened wall consistent with possible cholecystitis. Mild intrahepatic biliary dilation was present. The celiac axis, superior mesenteric vessels, splenic vessels and portal vein were normal. Type B Dissection of the thoracic aorta and aortic arch was identified in the endoscopic ultrasound. Traditionally, CTs with contrast dye, echocardiograms and MRIs are commonly used to diagnose AD [1]. Meanwhile, endoscopic ultrasound (EUS) provides clear images to facilitate the diagnosis of gastrointestinal conditions. Our case highlights that EUS can also be used to examine cardiovascular disorders. EUS offers complete visualization of the aortic valve, the mitral valve, ascending and descending aorta, pericardium, left atrial appendage, and interatrial septum [3]. The proximity of the aorta to the esophagus allows for a very detailed view of the aorta [2,3]. It is essential that every complete endoscopic ultrasound exam include an evaluation of the thoracic organs in order to capture critical incidental findings that would be otherwise missed.2139_A Figure 1. Type B aortic dissection as seen on endoscopic ultrasound.2139_B Figure 2. Type B aortic dissection as seen on endoscopic ultrasound.

Aortic dissection detection risk score has high sensitivity with moderate inter-rater reliability.

To retrospectively assess the accuracy and inter-rater reliability of the aortic dissection detection risk score (ADD-RS). Single-centre, observational, diagnostic accuracy study undertaken in a university-affiliated, tertiary hospital ED. Two hundred patients were enrolled. Five patients were diagnosed with acute aortic dissection and had an elevated ADD-RS >0. The ADD-RS was 100% sensitive with a negative and positive predictive values of 100% (if ADD-RS ≥1). Inter-rater reliability was moderate (Kappa = 0.55). The ADD-RS was highly sensitive in our cohort. Further work to evaluate the score prospectively and in combination with a D-Dimer is required.

Values of aortic dissection detection risk score combined with ascending aorta diameter >40 mm for the early identification of type A acute aortic dissection.

Type A acute aortic dissection (A-AAD), involving the ascending aorta, is a life-threatening disease. To detect A-AAD early and rapidly in patients with acute chest pain, especially in patients with acute myocardial infarction (AMI) secondary to A-AAD, we investigated values of combined use of the risk score and the ascending aorta diameter >40 mm for the early identification of A-AAD. Our study retrospectively encompassed 239 patients with acute chest pain on admission to our hospital between July 2010 and December 2016. The risk score was calculated according to the aortic dissection detection (ADD) risk score system, and the ascending aorta diameter was accurately obtained from the transthoracic echocardiography (TTE). A risk score ≥1 had an excellent sensitivity of 94.9% and a fair negative predictive value (NPV) of 77.8%, with a poor specificity of 8.7% and a positive predictive value (PPV) of 33.5% for the diagnosis of A-AAD. A risk score ≥2 had an excellent specificity of 91.3% and a fair NPV of 73.1%, whereas it had a lower sensitivity of 30.8% and a PPV of 63.2%. A risk score ≥1, combined with an ascending aorta diameter >40 mm, had a sensitivity, a specificity, a PPV, and an NPV of 84.6%, 87.6%, 76.7%, and 92.2% for the diagnosis of A-AAD, respectively. The combined use of a risk score ≥2 and an ascending aorta diameter >40 mm had an excellent specificity of 98.1% and a PPV of 86.4%, a fair NPV of 72.8%, and a poor sensitivity of 24.4% for the detection of A-AAD. Moreover, the omission diagnostic rate for A-AAD was significantly decreased from 33.3% to 7.4% using a risk score ≥1 combined with an ascending aorta diameter >40 mm in patients with AMI secondary to A-AAD. The combined use of an ADD risk score ≥1 and an ascending aorta diameter >40 mm was highly indicative of A-AAD in patients presenting with acute chest pain, especially in patients with AMI secondary to A-AAD, which urgently needed computed tomography angiography (CTA) or magnetic resonance imaging (MRI) to confirm the diagnosis of A-AAD.

Identification of type IV collagen exposure as a molecular imaging target for early detection of thoracic aortic dissection.

Thoracic aortic dissection (TAD) is an aggressive and life-threatening vascular disease and there is no effective means of early diagnosis of dissection. Type IV collagen (Col-IV) is a major component of the sub-endothelial basement membrane, which is initially exposed followed by endothelial injury as early-stage event of TAD. So, we want to build a noninvasive diagnostic method to detect early dissection by identifying the exposed Col-IV via MRI.Methods: Col-IV-targeted magnetic resonance/ fluorescence dual probe (Col-IV-DOTA-Gd-rhodamine B; CDR) was synthesized by amide reaction and coordination reaction. Flow cytometry analysis was used to evaluate the cell viability of SMC treated with CDR and fluorescence assays were used to assess the Col-IV targeting ability of CDR in vitro. We then examined the sensitivity and specificity of CDR at different stages of TAD via MRI and bioluminescence imaging in vivo.Results: The localization of Col-IV (under the intima) was observed by histology images. CDR bound specifically to Col-IV-expressing vascular smooth muscle cells and BAPN-induced dissected aorta. The CDR signal was co-detected by magnetic resonance imaging (MRI) and bioluminescence imaging as early as 2 weeks after BAPN administration (pre-dissection stage). The ability to detect rupture of dissected aorta was indicated by a strong normalized signal enhancement (NSE) in vivo. Moreover, NSE was negatively correlated with the time of dissection rupture after BAPN administration (r2 = 0.8482).Conclusion: As confirmed by in vivo studies, the CDR can identify the exposed Col-IV in degenerated aorta to monitor the progress of aortic dissection from the early stage to the rupture via MRI. Thus, CDR-enhanced MRI proposes a potential method for dissection screening, and for monitoring disease progression and therapeutic response.

The impact of prehospital assessment and EMS transport of acute aortic syndrome patients

BackgroundThe quality of acute aortic syndrome (AAS) assessment by emergency medical service (EMS) and the incidence and prehospital factors associated with 1-month survival remain unclear. MethodsWe retrospectively analyzed the data collected for 94,468 patients with non-traumatic medical emergency excluding out-of-hospital cardiac arrest during the period of 2011–2014. ResultsOf these transported by EMS, 22,075 had any of the AAS-related symptoms, and 330 had an EMS-assessed risk for AAS; of these, 195 received an in-hospital AAS diagnosis. Of the remaining 21,745 patients without EMS-assessed risk, 166 were diagnosed with AAS. Therefore, the sensitivity and specificity of our EMS-risk assessment for AAS was 54.0% (195/361) and 99.4% (21,579/21,714), respectively. EMS assessed the risk less frequently when patients were elderly and presented with dyspnea and syncope/faintness. Sign of upper extremity ischemia was rarely detected (6.9%) and absence of this sign was associated with lack of EMS-assessed risk. The calculation of modified aortic dissection detection risk score revealed that rigorous assessment based on this score may increase the EMS sensitivity for AAS. The 1-month survival rate was significantly higher in patients admitted to core hospitals with surgical teams for AAS than in those admitted to all other hospitals [87.5% (210/240) vs 69.4% (84/121); P<0.01]. Multiple logistic regression analysis demonstrated that Stanford type A, Glasgow coma scale ≤14, and admission to core hospitals providing emergency cardiovascular surgery were associated with 1-month survival. ConclusionsImprovement of AAS survival is likely to be affected by rapid admission to appropriate hospitals providing cardiovascular surgery.

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

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. 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-. 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. Integration of ADD-RS (either ADD-RS=0 or ADD-RS ≤1) with DD may be considered to standardize diagnostic rule out of AAS. URL: https://www.clinicaltrials.gov. Unique identifier: NCT02086136.

364 Point-of-Care Ultrasound for the Detection of Aortic Dissections in the Emergency Department

364 Point-of-Care Ultrasound for the Detection of Aortic Dissections in the Emergency Department