The risk of misdiagnosis in acute thoracic aortic dissection: a review of current guidelines

Improvement of Early Outcomes in Type A Acute Aortic Syndrome After an Aorta Code Implementation

BACKGROUND

Reduction of variability through process reengineering can improve surgical results for patients with type A acute aortic syndrome. We compare short-term results before and after implementation of an Aorta Code for patients with type A acute aortic syndrome who underwent surgery.

METHODS

The Aorta Code was implemented in a 5-hospital healthcare network in 2019. This critical pathway was based on a simple diagnostic algorithm, ongoing training, immediate patient transfer, and treatment by an expert multidisciplinary team. We retrospectively compared all patients operated on in our center before (2005-2018) and after (January 2019 to February 2023) its implementation.

RESULTS

One hundred two and 70 patients underwent surgery in the precode and code periods, respectively. In the code period the number of patients operated on per year increased (from 7.3 to 16.8), and the median elapsed time until diagnosis (6.5 hours vs 4.2 hours), transfer (4 hours vs 2.2 hours), and operating room (2.7 hours vs 1.8 hours) were significantly shorter (P < .05). Aortic root repair and total arch replacement were more frequent (66.7% vs 82.9% [P = .003] and 20.6% vs 40% [P = .001]). Cardiopulmonary bypass and ischemia times were also shorter (179.7 minutes vs 148.2 minutes [P = .001] and 105 minutes vs 91.2 minutes [P = .022]). Incidence of prolonged mechanical ventilation (53.9% vs 34.3%, P = .011), major stroke (17.7% vs 7.1%, P = .047), and 30-day mortality (27.5% vs 7.1%, P = .001) decreased significantly.

CONCLUSIONS

An Aorta Code can be successfully implemented by using a standardized protocol within a hospital network. The number of cases increased; time to diagnosis, transfer, and operating room were reduced; and 30- day mortality significantly decreased.

Acute Aortic Syndromes from Diagnosis to Treatment-A Comprehensive Review

This work aims to provide a comprehensive description of the characteristics of a group of acute aortic diseases that are all potentially life-threatening and are collectively referred to as acute aortic syndromes (AASs). There have been recent developments in the care and diagnostic plan for AAS. A substantial clinical index of suspicion is required to identify AASs before irreversible fatal consequences arise because of their indefinite symptoms and physical indicators. A methodical approach to the diagnosis of AAS is addressed. Timely and suitable therapy should be started immediately after diagnosis. Improving clinical outcomes requires centralising patients with AAS in high-volume centres with high-volume surgeons. Consequently, the management of these patients benefits from the increased use of aortic centres, multidisciplinary teams and an "aorta code". Each acute aortic entity requires a different patient treatment strategy; these are outlined below. Finally, numerous preventive strategies for AAS are discussed. The keys to good results are early diagnosis, understanding the natural history of these disorders and, where necessary, prompt surgical intervention. It is important to keep in mind that chest pain does not necessarily correspond with coronary heart disease and to be alert to the possible existence of aortic diseases because once antiplatelet drugs are administered, a blocked coagulation system can complicate aortic surgery and affect prognosis. The management of AAS in "aortic centres" improves long-term outcomes and decreases mortality rates.

Sizing the Frozen Elephant Trunk Based on Aortic Pathology and the Importance of Pre-Operative Imaging

The frozen elephant trunk is a formidable tool for the aortovascular surgeon. An appreciation of how to size the graft in different pathologies is key in achieving optimal results. Herein, we demonstrate worked examples of how imaging can be used to plan for a frozen elephant trunk and discuss the nuisances and uncertainties of sizing using three index cases: Type A aortic dissection, distal thoracic aortic aneurysm and chronic dissection.

Improvement in the management of suspected acute aortic syndrome in the emergency room through a clinical algorithm and study of predictive factors

BACKGROUND AND OBJECTIVE

Acute aortic syndrome (AAS) is uncommon and difficult to diagnose, with great variability in clinical presentation. To develop a computerized algorithm, or clinical decision support system (CDSS), for managing and requesting imaging in the emergency department, specifically computerized tomography of the aorta (CTA), when there is suspicion of AAS, and to determine the effect of implementing this system. To determine the factors associated with a positive radiological diagnosis that improve the predictive capacity of CTA findings.

MATERIALS AND METHODS

After developing and implementing an evidence-based algorithm, we studied suspected cases of AAS. Chi-squared test was used to analyze the association between the variables included in the algorithm and radiological diagnosis, with 3 categories: no relevant findings, positive for AAS, and alternative diagnoses.

RESULTS

130 requests were identified; 19 (14.6%) had AAS and 34 (26.2%) had a different acute pathology. Of the 19 with AAS, 15 had been stratified as high risk and 4 as intermediate risk. The probability of AAS was 3.4 times higher in patients with known aortic aneurysm (P = .021, 95% CI 1.2-9.6) and 5.1 times higher in patients with a new aortic regurgitation murmur (P = .019, 95% CI 1.3-20.1). The probability of having an alternative severe acute pathology was 3.2 times higher in patients with hypotension or shock (P = .02, 95% CI 1.2-8.5).

CONCLUSION

The use of a CDSS in the emergency department can help optimize AAS diagnosis. The presence of a known aortic aneurysm and new-onset aortic regurgitation were shown to significantly increase the probability of AAS. Further studies are needed to establish a clinical prediction rule.

Risk assessment and disease burden of extreme precipitation on hospitalizations for acute aortic dissection in a subtropical coastal Chinese city

Background

Extreme precipitation events are becoming more frequent due to climate change. The present study aimed to explore the impacts of extreme precipitation on hospitalizations for acute aortic dissection (AAD) and to identify susceptible populations and quantify the corresponding disease burden.

Methods

The present study used a distributed lag nonlinear model (DLNM) with a quasi-Poisson function to investigate the association between extreme precipitation (≥95th percentile) and the risk of hospitalizations for AAD from 2015 to 2020 in Shantou, Guangdong Province, China.

Results

The significant adverse effects of extreme precipitation (relative to no precipitation) on daily AAD hospitalizations lasted from lag 5 [relative risk (RR): 1.0318, 95% confidence interval (CI): 1.0067-1.0575] to lag 9 (RR: 1.0297, 95% CI: 1.0045-1.0555) and reached its maximum at lag 7 (RR: 1.0382, 95% CI: 1.0105-1.0665). Males and older adult individuals (≥60 years) were more susceptible to extreme precipitation. A total of 3.68% (118 cases) of AAD hospitalizations were due to extreme precipitation.

Conclusion

Extreme precipitation was significantly correlated with AAD hospitalizations. Government departments should actively implement extreme precipitation intervention measures to strengthen the protection of males and the older adult (≥60 years) and effectively reduce AAD hospitalizations.

68Ga-labeled WVP peptide as a novel PET probe for molecular biological diagnosis of unstable thoracic aortic aneurysm and early dissection: an animal study

Objective

Type IV collagen (Col-IV) is a prospective biomarker for diagnosing and treating of unstable thoracic aortic aneurysm and dissection (TAAD). This study aims to evaluate the feasibility of ⁶⁸Ga-labeled WVP peptide (⁶⁸Ga-DOTA-WVP) as a novel Col-IV-targeted probe for TAAD biological diagnosis using PET/CT.

Methods

WVP peptide was modified with bifunctional chelator DOTA for ⁶⁸Ga radiolabeling. Immunohistochemical staining was used to evaluate the expression and location of Col-IV and elastin in aortas treated with 3-aminopropionitrile fumarate (BAPN) at different time points (0, 2, and 4 weeks). The imaging performance of ⁶⁸Ga-DOTA-WVP was investigated using Micro-PET/CT in a BAPN-induced TAAD mouse model. The relationship between ⁶⁸Ga-DOTA-WVP uptake in aortic lesions and the serum levels of TAAD-related biomarkers including D-dimer, C-reactive protein (CRP), and serum soluble suppression of tumorigenicity-2 (sST2) was also analyzed.

Results

⁶⁸Ga-DOTA-WVP was readily prepared with high radiochemical purity and stability in vitro. ⁶⁸Ga-DOTA-WVP Micro-PET/CT could detect Col-IV exposure of unstable aneurysms and early dissection in BAPN-induced TAAD mice, but little ⁶⁸Ga-DOTA-WVP uptake was shown in the control group at each imaging time point. The differences of Col-IV expression and distribution of ⁶⁸Ga-DOTA-WVP both in TAAD and control groups further verified the imaging efficiency of ⁶⁸Ga-DOTA-WVP PET/CT. Additionally, a higher sST2 level was found in the imaging positive (n = 14) than the negative (n = 8) group (9.60 ± 1.14 vs. 8.44 ± 0.52, P = 0.014).

Conclusion

⁶⁸Ga-DOTA-WVP could trace the exposure and abnormal deposition of Col-IV in enlarged and early injured aortas, showing a potential for biological diagnosis, whole-body screening, and progression monitoring of TAAD.

Acute Lung Injury in aortic dissection : new insights in anesthetic management strategies

Acute aortic dissection (AAD) is a severe cardiovascular disease characterized by rapid progress and a high mortality rate. The incidence of acute aortic dissection is approximately 5 to 30 per 1 million people worldwide. In clinical practice, about 35% of AAD patients are complicated with acute lung injury (ALI). AAD complicated with ALI can seriously affect patients' prognosis and even increase mortality. However, the pathogenesis of AAD combined with ALI remains largely unknown. Given the public health burden of AAD combined with ALI, we reviewed the anesthetic management advances and highlighted potential areas for clinical practice.

Management of chronic Stanford type A aortic dissection combined with Neri type C coronary occlusion: a case report and literature review

While there are many reports on partial aortic root remodelling, it is rarely performed for chronic aortic dissection of the coronary artery. This case report describes a 71-year-old male patient with chronic aortic dissection who was admitted to hospital due to repeated palpitations and chest distress. He had a long-term occlusion of the right coronary artery and an abnormal origin of the left vertebral artery. A carefully planned surgical strategy was arranged for this patient, and the surgical experience is described and discussed herein. Briefly, the patient was treated by aortic root repair plus ascending aorta replacement plus Sun's procedure plus left vertebral artery graft implantation plus coronary artery bypass graft (right coronary artery to saphenous vein to innominate artery). At approximately 6 months following surgery, the patient had returned to normal living conditions without any reports of discomfort.

Diagnosis of Acute Aortic Syndromes on Non-Contrast CT Images with Radiomics-Based Machine Learning

We aimed to detect acute aortic syndromes (AAS) on non-contrast computed tomography (NCCT) images using a radiomics-based machine learning model. A total of 325 patients who underwent aortic CT angiography (CTA) were enrolled retrospectively from 2 medical centers in China to form the internal cohort (230 patients, 60 patients with AAS) and the external testing cohort (95 patients with AAS). The internal cohort was divided into the training cohort (n = 135), validation cohort (n = 49), and internal testing cohort (n = 46). The aortic mask was manually delineated on NCCT by a radiologist. Least Absolute Shrinkage and Selection Operator regression (LASSO) was used to filter out nine feature parameters; the Support Vector Machine (SVM) model showed the best performance. In the training and validation cohorts, the SVM model had an area under the curve (AUC) of 0.993 (95% CI, 0.965–1); accuracy (ACC), 0.946 (95% CI, 0.877–1); sensitivity, 0.9 (95% CI, 0.696–1); and specificity, 0.964 (95% CI, 0.903–1). In the internal testing cohort, the SVM model had an AUC of 0.997 (95% CI, 0.992–1); ACC, 0.957 (95% CI, 0.945–0.988); sensitivity, 0.889 (95% CI, 0.888–0.889); and specificity, 0.973 (95% CI, 0.959–1). In the external testing cohort, the ACC was 0.991 (95% CI, 0.937–1). This model can detect AAS on NCCT, reducing misdiagnosis and improving examinations and prognosis.

Risk Prediction Models for Management of Patients following Acute Aortic Dissection

Risk prediction of adverse outcomes post aortic dissection is dependet not only on the postdissection-associated clinical factors but on the very foundation of the risk factors that lead up to the dissection itself. There are various such risk factors existing prior to the dissection which impact the postdissection outcomes. In this paper, we review the literature to critically analyze various risk models, burdened by their significant limitations, that attempt to stratify risk prediction based on postdissection patient characteristics. We further review several studies across the literature that investigate the diverse set of predissection risk factors impacting postdissection outcomes. We have discussed and appraised numerous studies which attempt to develop a tool to stratify risk prediction by incorporating the impacts of different factors: malperfusion, blood biochemistry, and perioperative outcomes. The well-validated Penn classification has clearly demonstrated in the literature the significant impact that malperfusion has on adverse outcomes postdissection. Other risk models, already severely hindered by their limitations, lack such validation. We further discuss additional alluded risk factors, including the impact of predissection aortic size, the syndromic and nonsyndromic natures of dissection, and the effects of family history and genetics, which collectively contribute to the risk of adverse outcomes postdissection and prognosis. To achieve the goal of a true risk model, there remains the vital need for appreciation and appropriate consideration for all such aforementioned factors, from before and after the dissection, as discussed in this paper. By being able to incorporate the value of true risk prediction for a patient into the decision-making framework, it will allow a new page of precision medical decision-making to be written.

Current Understanding of Aortic Dissection

The aorta is the largest artery in the body, delivering oxygenated blood from the left ventricle to all organs. Dissection of the aorta is a lethal condition caused by a tear in the intimal layer of the aorta, followed by blood loss within the aortic wall and separation of the layers to full dissection. The aorta can be affected by a wide range of causes including acute conditions such as trauma and mechanical damage; and genetic conditions such as arterial hypertension, dyslipidaemia, and connective tissue disorders; all increasing the risk of dissection. Both rapid diagnostic recognition and advanced multidisciplinary treatment are critical in managing aortic dissection patients. The treatment depends on the severity and location of the dissection. Open surgical repair is the gold standard of treatment for dissections located to the proximal part of the aorta and the arch, while endovascular interventions are recommended for most distal or type B aortic dissections. In this review article, we examine the epidemiology, pathophysiology, contemporary diagnoses, and management of aortic dissection.

The characteristics of thoracic aortic dissection in autopsy-diagnosed individuals: An autopsy study

Thoracic aortic dissection (TAD) is the most common cause of sudden cardiac death associated with aortic diseases. The age of TAD victims in forensic studies is significantly younger than hospitalized patients with TAD, while only a few studies have been conducted on autopsy-diagnosed TAD deceased. A retrospective study was conducted at the Medicolegal Center of Sun Yat-sen University from 1999 to 2019 to address the characteristics of TAD victims. A total of 200 deceased from spontaneous rupture of TAD were assessed, with 165 (82.5%) males and 175 (87.5%) Stanford type A deceased. Our main results showed that compared with patients with TAD diagnosed during their lifetime, individuals diagnosed with TAD until an autopsy showed an earlier onset (43.80 years old) and less accompanied hypertension (<50%). Sudden death was the initial symptom of 32 decedents. Instead of chest/back pain (40 decedents), abdominal pain (59 decedents) was the most common initial symptom, and 42 decedents presented with no accompanying pain. A higher proportion of abdominal pain and the painless symptom was associated with a higher risk of misdiagnosis. Women showed a more atypical clinical presentation and rapid progression than men. Younger decedents showed more pronounced left heart changes. The present study implicated the TAD individuals diagnosed until an autopsy as a particular entity, indicating the urgent need for further investigation on early diagnosis and pathogenesis of patients with TAD with atypical pain and painless or with younger age to reduce the burden of TAD-related sudden death.

C/EBPα-Mediated Transcriptional Activation of PIK3C2A Regulates Autophagy, Matrix Metalloproteinase Expression, and Phenotypic of Vascular Smooth Muscle Cells in Aortic Dissection

Purpose

To investigate the function of C/EBPα in the development of aortic dissection (AD) and the underlying mechanism.

Methods

Aortic vascular smooth muscle cells (VSMCs) were isolated, cultured, and identified from AD rats. Then, C/EBPα and PIK3C2A were knockdown or overexpressed by siRNA or plasmid transfection, respectively. Rapamycin or 3-MA was utilized to stimulate and restrain autophagy of VSMCs, respectively. Western blot was used to evaluate the expression levels of C/EBPα, PIK3C2A, LC3, Beclin-1, p62, MMP-2, MMP-9, α-SMA, SM-MHC, and OPN. The pathological status of aortic ring was evaluated by stretch stress, and ChIP assay was used to analyze the binding between C/EBPα and PIK3C2A. C/EBPα shRNA was injected into tail vein to observe the effect of C/EBPα knockdown in vivo on phenotype, autophagy of aortic vascular tissue by immunohistochemical staining and Western blot.

Results

The protein levels of C/EBPα, PIK3C2A, MMP-2, MMP-9, and LC3 in the aorta of AD rats were all upregulated significantly. C/EBPα and rapamycin promoted notable upregulation of the synthesized proteins (OPN), PIK3C2A, matrix metalloproteinases, LC3, and Beclin-1 in VSMCs, while suppressed contractile proteins (α-SMA and SM-MHC) and p62. The opposite results were observed in the C/EBPα-knockdown VSMCs, PIK3C2A-knockdown VSMCs, or VSMCs treated with 3-MA. C/EBPα, PIK3C2A, and LC3 were dramatically upregulated by the stimulation of 3 g and 5 g stretch stress. The downregulated contractile proteins, upregulated synthetic proteins, activated autophagy, and aggravated pathological state in 5 g stretch stress-treated aortic rings were significantly reversed by the knockdown of C/EBPα. ChIP results indicated that there was a binding site for C/EBPα in the promoter of PIK3C2A. C/EBPα also downregulated α-SMA level and upregulated OPN levels in AD rats in vivo.

Conclusion

Our data indicated that during the development of AD, C/EBPα regulated the transition of VSMC phenotype and extracellular matrix remodeling by activating autophagy through regulating the transcriptional activity of PIK3C2A promoter.

Misdiagnosis of Thoracic Aortic Emergencies Occurs Frequently Among Transfers to Aortic Referral Centers: An Analysis of Over 3700 Patients

Background

Acute aortic syndromes may be prone to misdiagnosis by nonreferral aortic centers with less diagnostic experience. We evaluated regional variability in these misdiagnosis trends among patients transferred to different regional quaternary care centers with presumed acute aortic syndromes.

Methods and Results

Two institutional aortic center databases were retrospectively reviewed for emergency transfers in patients diagnosed with acute aortic dissection, intramural hematoma, penetrating aortic ulcer, thoracic aortic aneurysm, or aortic pseudoaneurysm between 2008 and 2020. Transferring diagnoses versus actual diagnoses were reviewed using physician notes and radiology reports. Misdiagnoses were confirmed by a board‐certified cardiothoracic surgeon. A total of 3772 inpatient transfers were identified, of which 1762 patients were classified as emergency transfers. The mean age was 64 years (58% male). Patients were transferred from 203 medical centers by ground (51%) or air (49%). Differences in transfer diagnosis and actual diagnosis were identified in 188 (10.7%) patients. Of those, incorrect classification of Type A versus B dissections was identified among 23%, and 30% of patients with a referring diagnosis of an acute aortic dissection did not have one. In addition, 14% transferred for contained/impending rupture did not have signs of rupture. All misdiagnoses were secondary to misinterpretation of imaging, with motion artifacts (n=32, 17%) and postsurgical changes (n=44, 23%) being common sources of diagnostic error.

Conclusions

Misdiagnosis of acute aortic syndromes commonly occurred in patients transferred to 2 separate large aortic referral centers. Although diagnostic accuracy may be improving, there are opportunities for improved physician awareness through standardized web‐based imaging education.

The association between lymphocyte-monocyte ratio and postoperative acute kidney injury in patients with acute type A aortic dissection

BACKGROUND

The aim of this study was to investigate the relationship between baseline lymphocyte-monocyte ratio (LMR) and postoperative acute kidney injury (AKI) in patients with acute type A aortic dissection (ATAAD).

METHODS

ATAAD patients undergoing surgery in Nanjing First Hospital were enrolled from January 2019 to April 2021. Lymphocyte and monocyte were measured on admission. Multivariable logistic regression analyses were performed to explore the relationship between LMR and postoperative AKI. We also used receiver operating characteristic (ROC), net reclassification index (NRI) and integrated discrimination improvement (IDI) analyses to assess the predictive ability of LMR.

RESULTS

Among the 159 recruited patients, 47 (29.6%) were diagnosed with AKI. Univariate logistic regression analysis indicated that ATAAD patients with higher levels of LMR were prone to have lower risk to develop AKI (odds ratio [OR], 0.493; 95% confidence interval [CI] 0.284-0.650, P = 0.001). After adjustment for the potential confounders, LMR remained an independent related factor with postoperative AKI (OR 0.527; 95% CI 0.327-0.815, P = 0.006). The cutoff value for LMR to predict AKI was determined to be 2.67 in the ROC curve analysis (area under curve: 0.719). NRI and IDI further confirmed the predictive capability of LMR in postoperative AKI.

CONCLUSION

Elevated baseline LMR levels were independently associated with lower risk of postoperative AKI in ATAAD patients.

The diagnostic value of D-dimer in acute aortic dissection: a meta-analysis

Objective

This study aims to evaluate the diagnostic value of D-dimer for acute aortic dissection (AAD) by the method of meta-analysis.

Methods

PubMed, Cochrane Library, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), and Wanfang databases from the establishment of the databases to December 2020 were systematically searched, and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) system was used to evaluate the quality of the literature. STATA 15.0 software was applied to calculate the pooled sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (+LR), negative likelihood ratio (−LR) to draw summary receiver operating characteristics (SROC) curve and calculate the area under the curve (AUC). Meta-regression and subgroup analyses were used to explore the source of heterogeneity.

Results

A total of 16 clinical studies were enrolled in this study, including 1135 patients. The results of the meta-analysis showed that the pooled sensitivity was 0.96 (95% CI 0.91–0.98), the pooled specificity was 0.70 (95% CI 0.57–0.81), and the pooled DOR was 56.57 (95% CI 25.11–127.44), the pooled +LR was 3.25 (95% CI 2.18–4.85), the pooled −LR was 0.06 (95% CI 0.03–0.12), and the AUC was 0.94 (95% CI 0.91–0.95). Meta-regression and subgroup analysis results showed that publication year, sample size and cutoff value might be sources of heterogeneity. When the concentration of D-dimer was less than or equal to 500 ng/ml, the sensitivity significantly increased.

Conclusion

D-dimer has an excellent diagnostic value for AAD. It is a useful tool for detecting suspected AAD because of the excellent pooled sensitivity. D-dimer ≤ 500 ng/ml increases the potential to identify the suspected patients with AAD.

Misdiagnosis of Thoracic Aortic Disease Occurs Commonly in Emergency Transfers

BACKGROUND

Acute aortic syndromes (AAS) are prone to misdiagnosis by facilities with limited diagnostic experience. We assessed long-term trends in misdiagnosis among patients transferred to a tertiary care facility with presumed AAS.

METHODS

Our institutional transfer center database was queried for emergency transfers in patients with a diagnosis of acute aortic syndromes or thoracic aortic aneurysm between January 2008 and May 2018. 784 patients were classified as emergency transfer for presumed AAS. Transferring diagnosis and actual diagnosis were compared through a review of physician notes and radiology reports from referring facilities and our center.

RESULTS

Mean age was 62 years, with 61% (n=478) men. Differences in transferring diagnosis and actual diagnosis were identified in 89 (11.4%) patients. Among misdiagnosed patients, the wrong classification of Stanford Type A or Type B dissections was identified among 24 (27%) patients. Twenty-three (26%) patients with a referring diagnosis of aortic dissection were found to have no dissection. Eighteen patients (20%) transferred for contained/impending rupture did not have signs of rupture. All misdiagnoses were secondary to misinterpretation of radiographic imaging, with motion artifacts (n=14, 16%) and post-surgical changes (n=22, 25%) being common sources of diagnostic error. Sixty-four (72%) patients underwent repeat scans at our facility due to limited access or sub-optimal quality of outside imaging.

CONCLUSIONS

While AAS misdiagnosis rates appear to be improving from the prior decade, there are opportunities for improved physician awareness through campaigns such as "Think Aorta." Centralized web-based imaging may prevent the costly hazards of unnecessary emergency transfer.

Acute Aortic Syndrome Revisited: JACC State-of-the-Art Review

The purpose of this paper is to describe all available evidence on the distinctive features of a group of 4 life-threatening acute aortic pathologies gathered under the name of acute aortic syndrome (AAS). The epidemiology, diagnostic strategy, and management of these patients has been updated. The authors propose a new and simple diagnostic algorithm to support clinical decision making in cases of suspected AAS, thereby minimizing diagnostic delays, misdiagnoses, and unnecessary advanced imaging. AAS-related entities are reviewed, and a guideline to avoid imaging misinterpretation is provided. Centralization of patients with AAS in high-volume centers with high-volume surgeons is key to improving clinical outcomes. Thus, the role of multidisciplinary teams, an "aorta code" (streamlined emergent care pathway), and aortic centers in the management of these patients is boosted. A tailored patient treatment approach for each of these acute aortic entities is needed, and as such has been summarized. Finally, a set of prevention measures against AAS is discussed.

Plasma Lipidomics Identifies Unique Lipid Signatures and Potential Biomarkers for Patients With Aortic Dissection

Aortic dissection (AD) is a catastrophic cardiovascular emergency with a poor prognosis, and little preceding symptoms. Abnormal lipid metabolism is closely related to the pathogenesis of AD. However, comprehensive lipid alterations related to AD pathogenesis remain unclear. Moreover, there is an urgent need for new or better biomarkers for improved risk assessment and surveillance of AD. Therefore, an untargeted lipidomic approach based on ultra-high-performance liquid chromatograph-mass spectrometry was employed to unveil plasma lipidomic alterations and potential biomarkers for AD patients in this study. We found that 278 of 439 identified lipid species were significantly altered in AD patients (n = 35) compared to normal controls (n = 32). Notably, most lipid species, including fatty acids, acylcarnitines, cholesteryl ester, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, lysophosphatidylethanolamines, phosphatidylcholines, phosphatidylinositols, diacylglycerols, and triacylglycerols with total acyl chain carbon number ≥54 and/or total double bond number ≥4 were decreased, whereas phosphatidylethanolamines and triacylglycerols with total double bond number <4 accumulated in AD patients. Besides, the length and unsaturation of acyl chains in triacylglycerols and unsaturation of 1-acyl chain in phosphatidylethanolamines were decreased in AD patients. Moreover, lysophosphatidylcholines were the lipids with the largest alterations, at the center of correlation networks of lipid alterations, and had excellent performances in identifying AD patients. The area under the curve of 1.0 and accuracy rate of 100% could be easily obtained by lysophosphatidylcholine (20:0/0:0) or its combination with lysophosphatidylcholine (17:0/0:0) or lysophosphatidylcholine (20:1/0:0). This study provides novel and comprehensive plasma lipidomic signatures of AD patients, identifies lysophosphatidylcholines as excellent potential biomarkers, and would be beneficial to the pathogenetic study, risk assessment and timely diagnosis and treatment of AD.

Integrated analysis of lncRNA-miRNA-mRNA ceRNA network in human aortic dissection

Background

Many studies on long chain non-coding RNAs (lncRNAs) are published in recent years. But the roles of lncRNAs in aortic dissection (AD) are still unclear and should be further examined. The present work focused on determining the molecular mechanisms underlying lncRNAs regulation in aortic dissection on the basis of the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network.

Methods

This study collected the lncRNAs (GSE52093), mRNAs (GSE52093) and miRNAs (GSE92427) expression data within human tissue samples with aortic dissection group and normal group based on Gene Expression Omnibus (GEO) database.

Results

This study identified three differentially expressed lncRNAs (DELs), 19 differentially expressed miRNAs (DEmiRs) and 1046 differentially expressed mRNAs (DEGs) identified regarding aortic dissection. Furthermore, we constructed a lncRNA-miRNA-mRNA network through three lncRNAs (including two with up-regulation and one with down-regulation), five miRNAs (five with up-regulation), as well as 211 mRNAs (including 103 with up-regulation and 108 with down-regulation). Simultaneously, we conducted functional enrichment and pathway analyses on genes within the as-constructed ceRNA network. According to our PPI/ceRNA network and functional enrichment analysis results, four critical genes were found (E2F2, IGF1R, BDNF and PPP2R1B). In addition, E2F2 level was possibly modulated via lncRNA FAM87A-hsa-miR-31-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. The expression of IGF1R may be regulated by lncRNA FAM87A-hsa-miR-16-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p.

Conclusion

In conclusion, the ceRNA interaction axis we identified is a potentially critical target for treating AD. Our results shed more lights on the possible pathogenic mechanism in AD using a lncRNA-associated ceRNA network.

A Deep-Learning Algorithm-Enhanced System Integrating Electrocardiograms and Chest X-rays for Diagnosing Aortic Dissection

BACKGROUND

Chest pain is the most common symptom of aortic dissection (AD), but it is often confused with other prevalent cardiopulmonary diseases. We aimed to develop deep-learning models (DLMs) with electrocardiography (ECG) and chest x-ray (CXR) features to detect AD and evaluate their performance.

METHODS

This study included 43,473 patients in the emergency department (ED) between July 2012 and December 2019 for retrospective DLM development. A development cohort including 49,071 ED records (120 AD type A and 64 AD type B) was used to train DLMs for ECG and CXR, and 9904 independent ED records (40 AD type A and 34 AD type B) were used to validate DLM performance. Human-machine competitions of ECG and CXR were conducted. Patient characteristics and laboratory results were used to enhance the diagnostic accuracy. The DLM-enabled AD diagnostic process was prospectively evaluated in 25,885 ED visits.

RESULTS

The area under the curves (AUCs) of the ECG and CXR models were 0.918 and 0.857 for detecting AD in a human-machine competition, respectively, which were better than those of the participating physicians. In the validation cohort, the AUCs of the integrated model were 0.882, 0.960, and 0.813 in all AD, AD type A, and AD type B patients, respectively, with a sensitivity of 100.0% and a specificity of 81.7% for AD type A. In patients with chest pain and D-dimer tests, the DLM could predict more precisely, achieving a positive predictive value of 62.5% in the prospective evaluation.

CONCLUSIONS

DLMs may serve as decision-supporting tools for identification of AD and facilitate differential diagnosis in patients with acute chest pain.

Non-contrast CT-based radiomic signature for screening thoracic aortic dissections: a multicenter study

OBJECTIVE

To develop a non-contrast CT-based radiomic signature to effectively screen for thoracic aortic dissections (ADs).

METHODS

We retrospectively enrolled 378 patients who underwent non-contrast chest CT scans along with CT angiography or MRI from 4 medical centers. The training and validation sets were from 3 centers, while the external test set was from a 4th center. Radiomic features were extracted from non-contrast CT images. The radiomic signature was created on the basis of selected features by a logistic regression algorithm. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were conducted to assess the predictive ability of radiomic signature.

RESULTS

The radiomic signature demonstrated AUCs of 0.91 (95% confidence interval [CI], 0.86-0.95) in the training set, 0.92 (95% CI, 0.86-0.98) in the validation set, and 0.90 (95% CI, 0.82-0.98) in the external test set. The predicted diagnosis was in good agreement with the probability of thoracic AD. In the external test group, the diagnostic accuracy, sensitivity, specificity, PPV, and NPV were 90.5%, 85.7%, 91.7%, 70.6%, and 96.5%, respectively.

CONCLUSIONS

A radiomic signature based on non-contrast CT images can effectively predict thoracic ADs. This method may serve as a potential screening tool for thoracic ADs.

KEY POINTS

• The non-contrast CT-based radiomic signature can effectively predict the thoracic aortic dissections. • This radiomic signature shows better predictive performance compared to the current clinical model. • This prediction method may be a potential tool for screening thoracic aortic dissections.

Exaggerated Autophagy in Stanford Type A Aortic Dissection: A Transcriptome Pilot Analysis of Human Ascending Aortic Tissues

Stanford type A aortic dissection (TAAD) is one of the most dangerous diseases of acute aortic syndrome. Molecular pathological studies on TAAD can aid in understanding the disease comprehensively and can provide insights into new diagnostic markers and potential therapeutic targets. In this study, we defined the molecular pathology of TAAD by performing transcriptome sequencing of human ascending aortic tissues. Pathway analysis revealed that activated inflammation, cell death and smooth muscle cell degeneration are the main pathological changes in aortic dissection. However, autophagy is considered to be one of the most important biological processes, regulating inflammatory reactions and degenerative changes. Therefore, we focused on the pathological role of autophagy in aortic dissection and identified 10 autophagy-regulated hub genes, which are all upregulated in TAAD. These results indicate that exaggerated autophagy participates in the pathological process of aortic dissection and may provide new insight for further basic research on TAAD.