Diagnosis Of Abdominal Aortic Aneurysm Research Articles

Cancer Incidence After Diagnosis of Abdominal Aortic Aneurysm.

Epidemiological and mechanistic data support a potential causal link between cardiovascular disease (CVD) and cancer. Abdominal aortic aneurysms (AAAs) represent a common form of CVD with at least partially distinct genetic and biologic etiology from other forms of CVD. The risk of cancer and how this risk differs compared with other forms of CVD, is unknown among AAA patients. We conducted a retrospective cohort study using the IBM MarketScan Research Database to test whether individuals with AAA have a higher cancer risk independent of traditional shared risk factors. All individuals ≥18 years of age with ≥36 months of continuous coverage between 2008 and 2020 were enrolled. Those with potential Mendelian etiologies of AAA, aortic aneurysm with nonspecific anatomic location, or a cancer diagnosis before the start of follow-up were excluded. A subgroup analysis was performed of individuals having the Health Risk Assessment records including tobacco use and body mass index. The following groups of individuals were compared: (1) with AAA, (2) with non-AAA CVD, and (3) without any CVD. The propensity score-matched cohort included 58 993 individuals with AAA, 117 986 with non-AAA CVD, and 58 993 without CVD. The 5-year cumulative incidence of cancer was 13.1% (12.8%-13.5%) in participants with AAA, 10.1% (9.9%-10.3%) in participants with non-AAA CVD, and 9.6% (9.3%-9.9%) in participants without CVD. Multivariable-adjusted Cox proportional hazards regression models found that patients with AAA exhibited a higher cancer risk than either those with non-AAA CVD (hazard ratio, 1.28 [95% CI, 1.23-1.32]; P<0.001) or those without CVD (hazard ratio, 1.32 [95% CI, 1.26-1.38]; P<0.001). Results remained consistent after excluding common smoking-related cancers and when adjusting for tobacco use and body mass index. Patients with AAA may have a unique risk of cancer requiring further mechanistic study and investigation of the role of enhanced cancer screening.

Identification of biomarkers for abdominal aortic aneurysm in Behçet's disease via mendelian randomization and integrated bioinformatics analyses.

Behçet's disease (BD) is a complex autoimmune disorder impacting several organ systems. Although the involvement of abdominal aortic aneurysm (AAA) in BD is rare, it can be associated with severe consequences. In the present study, we identified diagnostic biomarkers in patients with BD having AAA. Mendelian randomization (MR) analysis was initially used to explore the potential causal association between BD and AAA. The Limma package, WGCNA, PPI and machine learning algorithms were employed to identify potential diagnostic genes. A receiver operating characteristic curve (ROC) for the nomogram was constructed to ascertain the diagnostic value of AAA in patients with BD. Finally, immune cell infiltration analyses and single-sample gene set enrichment analysis (ssGSEA) were conducted. The MR analysis indicated a suggestive association between BD and the risk of AAA (odds ratio [OR]: 1.0384, 95% confidence interval [CI]: 1.0081-1.0696, p = 0.0126). Three hub genes (CD247, CD2 and CCR7) were identified using the integrated bioinformatics analyses, which were subsequently utilised to construct a nomogram (area under the curve [AUC]: 0.982, 95% CI: 0.944-1.000). Finally, the immune cell infiltration assay revealed that dysregulation immune cells were positively correlated with the three hub genes. Our MR analyses revealed a higher susceptibility of patients with BD to AAA. We used a systematic approach to identify three potential hub genes (CD247, CD2 and CCR7) and developed a nomogram to assist in the diagnosis of AAA among patients with BD. In addition, immune cell infiltration analysis indicated the dysregulation in immune cell proportions.

Can Biomarkers and PET Imaging Predict Abdominal Aortic Aneurysm Growth Rate?

Background: Abdominal aortic aneurysm (AAA) is a life-threatening condition due to the risk of aneurysm growth and rupture. Biomarkers linked to AAA pathogenesis are attractive candidates for AAA diagnosis and prognosis. The aim of this study was to assess circulating biomarkers levels relationship with PET imaging positivity and their predictive value in AAA growth rate. Methods: A total of 164 patients with AAA had whole body [18F]FDG PET/CT examination and blood drawn for biomarkers analysis at inclusion. Of these, 121 patients had at least one follow-up imaging assessment for AAA progression. Median (quartiles) imaging follow-up period was 32.8 months (15.2-69.6 months). Results: At baseline, PET was visually positive in 28 (17%) patients. Among PET+ patients, female proportion was higher compared to PET-patients (respectively, n = 6, 21.4% vs. n = 11, 8.1%, p = 0.046). Biomarkers of inflammation (CRP, CCL18), of proteolytic activity (MMP9), of extracellular matrix, and calcification regulation (OPN, OPG) were all significantly increased in PET+ patients (p < 0.05). During follow-up, rapid AAA growth (increase in size ≥ 1 cm per year) was observed in 36 (29.8%) patients and several biomarkers (CRP, MMP9, OPN, and OPG) were increased in those patients compared to patients without rapid growth (p < 0.05). Conclusions: Although PET positivity at baseline was not associated with rapid growth, CRP levels showed a significant association.

The associations among peptic ulcer disease, Helicobacter pylori infection, and abdominal aortic aneurysms: A nationwide population-based cohort study

BackgroundThere are overlapping risk factors and underlying molecular mechanisms for both peptic ulcer disease (PUD) and abdominal aortic aneurysm (AAA). Despite improvements in the early diagnosis and treatment of AAA, ruptured AAAs continue to cause a substantial number of deaths. Helicobacter pylori are Gram-negative, microaerophilic bacteria that are now recognized as the main cause of PUD. H. pylori infection (HPI) is associated with an increased risk of certain cardiovascular diseases. HPIs can be treated with at least two different antibiotics to prevent bacteria from developing resistance to one particular antibiotic. MethodsWe conducted a population-based cohort study using the National Health Insurance Research Database to evaluate whether associations exist among PUD, HPI, and eradication therapy for HPI and AAA. The primary outcome of this study was the cumulative incidence of AAA among patients with or without PUD and HPI during the 14-year follow-up period. ResultsOur analysis included 7003 patients with PUD/HPI, 7003 patients with only PUD, and another 7003 age-, sex-, and comorbidity-matched controls from the database. We found that patients with PUD/HPI had a significantly increased risk of AAA compared to those with PUD alone and matched controls. The patients who had PUD/HPI had a significantly higher cumulative risk of developing AAA than those with PUD and the comparison group (2.67 % vs. 1.41 % vs. 0.73 %, respectively, p < 0.001). Among those patients with PUD/HPI, patients who had eradication therapy had a lower incidence of AAA than those without eradication therapy (2.46 % vs. 3.88 %, p = 0.012). ConclusionsWe revealed an association among PUD, HPI, and AAA, even after adjusting for age, sex, comorbidities, and annual medical follow-up visits. Notably, we found that HPI eradication therapy reduced the incidence of AAA among patients with PUD.

Risk factors and mortality in dialysis patients with abdominal aortic aneurysm: A retrospective cohort study.

In the general population, abdominal aortic aneurysm (AAA) is synonymous with vascular disease and associated with increased mortality. Vascular disease is common in end-stage renal disease (ESRD) patients on dialysis, but there is limited information on AAA in this population. To address this issue, we queried the United States Renal Data System for risk factors associated with a diagnosis of AAA as well as the impact of AAA on ESRD patient survival. Incident dialysis patients from 2005 to 2014 with AAA and other clinical comorbidities were identified using ICD-9 and ICD-10 codes. Time to death was defined using the time from the start of dialysis to the date of death or to December 31, 2015. Cox proportional hazards (CPH) modeling was used to determine the adjusted hazard ratio (aHR) and 95% confidence intervals (CI) for death. From a total cohort of 820,826, we identified 21,631 subjects with a diagnosis of AAA. When compared to patients without AAA, AAA patients were older and more likely to be of white race and male gender, have a higher mean Charlson comorbidity index (CCI), have hypertension as the ESRD etiology, and use tobacco. Although a bivariate CPH model showed that AAA patients had an increased mortality risk compared to patients without the diagnosis, in the final CPH model, AAA patients had a decreased risk of mortality (aHR = 0.83, 95% CI 0.81-0.84) due to confounding with age. These results suggest that AAA is not associated with increased risk of death in ESRD patients after controlling for various demographic and clinical risk factors.

Surgical Treatment of Abdominal Aortic Aneurysms. A Retrospective Study.

Introduction: Surgical treatment of abdominal aortic aneurysms poses a significant challenge in the field of vascular surgery, with numerous factors influencing operative technique and surgical outcome.&#x0D; This study aimed to assess the outcomes of open surgical treatment for patients with abdominal aortic aneurysms at the Vascular Surgery Service of University Hospital Centre “Mother Teresa” Tirana and provide recommendations for improving outcomes.&#x0D; Material and Methods: A single-center, non-randomized, retrospective study of the results of open surgical treatment of abdominal aortic aneurysms in 206 patients from January 2008 to December 2015 was performed at the Vascular Surgery Service of University Hospital Centre “Mother Teresa” Tirana. The study only included patients with a histologically confirmed diagnosis of abdominal aortic aneurysm, while patients with ruptured abdominal aortic aneurysm were excluded.&#x0D; The study evaluated the incidence of abdominal aortic aneurysms, clinical and imaging findings of the disease (ultrasound, tomographic, and arteriographic), frequency of involvement of the iliac artery in the pathological process, and postoperative complications. Transabdominal access was the most commonly utilized, while retroperitoneal access was deemed the safest. No significant differences in recurrence rates were noted between the two approaches.&#x0D; Results: During the study period, 206 patients underwent surgery for AAA and met the inclusion criteria. Of these, 188 (91.3%) were male and 18 (8.7%) were female. The mean age of the patients was 67.8±5.7 years, with 67.7±5.9 years for men and 69±3.1 years for women. There were no statistically significant differences in age between genders (p&gt;0.05).&#x0D; Conclusion: In all other cases of abdominal aortic aneurysms, surgical treatment should be strongly recommended. Finally, given the clinical benefits of using surgical treatment of asymptomatic aneurysms to reduce mortality, it is necessary to conduct an economic assessment of the feasibility of abdominal aortic aneurysms screening in the population over 55 of the age of both sexes.&#x0D;

Development and validation of a machine-learning prediction model to improve abdominal aortic aneurysm screening

ObjectiveDespite recommendations by the United States Preventive Services Task Force and the Society for Vascular Surgery, adoption of screening for abdominal aortic aneurysms (AAAs) remains low. One challenge is the low prevalence of AAAs in the unscreened population, and therefore a low detection rate for AAA screenings. We sought to use machine learning to identify factors associated with the presence of AAAs and create a model to identify individuals at highest risk for AAAs, with the aim of increasing the detection rate of AAA screenings. MethodsA machine-learning model was trained using longitudinal medical records containing lab results, medications, and other data from our institutional database. A retrospective cohort study was performed identifying current or past smoking in patients aged 65 to 75 years and stratifying the patients by sex and smoking status as well as determining which patients had a confirmed diagnosis of AAA. The model was then adjusted to maximize fairness between sexes without significantly reducing precision and validated using six-fold cross validation. ResultsValidation of the algorithm on the single-center institutional data utilized 18,660 selected patients over 2 years and identified 314 AAAs. There were 41 factors identified in the medical record included in the machine-learning algorithm, with several factors never having been previously identified to be associated with AAAs. With an estimated 100 screening ultrasounds completed monthly, detection of AAAs is increased with a lift of 200% using the algorithm as compared with screening based on guidelines. The increased detection of AAAs in the model-selected individuals is statistically significant across all cutoff points. ConclusionsBy utilizing a machine-learning model, we created a novel algorithm to detect patients who are at high risk for AAAs. By selecting individuals at greatest risk for targeted screening, this algorithm resulted in a 200% lift in the detection of AAAs when compared with standard screening guidelines. Using machine learning, we also identified several new factors associated with the presence of AAAs. This automated process has been integrated into our current workflows to improve screening rates and yield of high-risk individuals for AAAs.

ДУОДЕНАЛЬНОЕ КРОВОТЕЧЕНИЕ КАК ОСЛОЖНЕНИЕ АНЕВРИЗМЫ АОРТЫ

Background. Gastrointestinal bleeding of non-ulcerative etiology remains an urgent problem of modern medicine. An aorto-intestinal fistula caused by an aortic aneurysm is one of the rarest causes of intestinal bleeding. Objective. To study the incidence of an aortic aneurysm with a complicated course according to autopsy data and to present a description of a rare case of an aortic aneurysm complicated by the formation of a duodenum fistula, profuse intestinal bleeding with a fatal outcome. Material and methods. The object of the study was the protocols of 2050 autopsies performed in Grodno over 2021-2022, among which in 40 (1.95%) cases the presence of an aortic aneurysm was established. In one case an abdominal aortic aneurysm was complicated by the formation of a fistula with the duodenum and profuse intestinal bleeding which became the direct cause of death. Results. The abdominal aorta was found to be involved in the pathological process in 32 (80.0%) dissections. Along with complications typical for an abdominal aortic aneurysm (bleeding into the retroperitoneal space and abdominal cavity) in 1 (3.1%) of 32 autopsies there has been revealed a formed anastomosis between the aorta and the duodenal lumen which was the cause of intestinal bleeding with fatal outcome. The clinical manifestations of the disease caused difficulties in interpreting the causes of intestinal bleeding. As a result, the fatal complication of an aortic aneurysm was recognized only on the 27th day after hospitalization, 1.5 hours before the patient’s death. Conclusions. The presented clinical case confirms that timely diagnosis of abdominal aortic aneurysms complicated by the formation of fistulas with the intestine is a rare diagnostic challenge. A particular feature of such complications is the fact that patients who are initially in a very serious condition are out of sight of vascular surgeons which leads to a delay in the provision of timely specialized care.

An Approach to Point-Of-Care Ultrasound Evaluation of the Abdominal Aorta.

Disorders of the abdominal aorta, including aneurysms and dissection, have potentially high rates of morbidity and mortality. While computed tomography (CT) is the current gold standard to image the abdominal aorta, the process of obtaining a CT may be time-consuming, requires the use of intravenous contrast dye, and involves exposure to ionizing radiation. Point-of-care Ultrasound (POCUS) can be performed at the bedside and has excellent sensitivity and specificity for the diagnosis of abdominal aortic aneurysm and excellent specificity for the diagnosis of abdominal aortic dissection. Additionally, POCUS is non-invasive, cost-effective, lacks ionizing radiation, requires no intravenous contrast dye, and can be performed without taking the patient from a critical care area. Screening for abdominal aortic aneurysm (AAA) can be done in primary care settings as well. This article will review the approach to POCUS of the abdominal aorta to evaluate such critical pathology. In this paper, we will review the sonographic anatomy of the abdominal aorta as well as the choice of the ultrasound probe, description of POCUS image acquisition, and some pearls and pitfalls of using POCUS to aid in the diagnosis of potentially life-threatening abdominal aortic pathology.

Status of diagnosis and therapy of abdominal aortic aneurysms.

Abdominal aortic aneurysms (AAAs) are characterized by localized dilation of the abdominal aorta. They are associated with several serious consequences, including compression of adjacent abdominal organs, pain, treatment-related financial expenditure. The main complication of AAA is aortic rupture, which is responsible for about 200,000 deaths per year worldwide. An increasing number of researchers are dedicating their efforts to study AAA, resulting in significant progress in this field. Despite the commendable progress made thus far, there remains a lack of established methods to effectively decelerate the dilation of aneurysms. Therefore, further studies are imperative to expand our understanding and enhance our knowledge concerning AAAs. Although numerous factors are known to be associated with the occurrence and progression of AAA, the exact pathway of development remains unclear. While asymptomatic at most times, AAA features a highly unpredictable disease course, which could culminate in the highly deadly rupture of the aneurysmal aorta. Current guidelines recommend watchful waiting and lifestyle adjustment for smaller, slow-growing aneurysms, while elective/prophylactic surgical repairs including open repair and endovascular aneurysm repair are recommended for larger aneurysms that have grown beyond certain thresholds (55 mm for males and 50 mm for females). The latter is a minimally invasive procedure and is widely believed to be suited for patients with a poor general condition. However, several concerns have recently been raised regarding the postoperative complications and possible loss of associated survival benefits on it. In this review, we aimed to highlight the current status of diagnosis and treatment of AAA by an in-depth analysis of the findings from literatures.

Immune-dysregulated neutrophils characterized by upregulation of CXCL1 may be a potential factor in the pathogenesis of abdominal aortic aneurysm and systemic lupus erythematosus

BackgroundThe abdominal aortic aneurysm (AAA) incidence is closely related to systemic lupus erythematosus (SLE). However, the common mechanisms between AAA and SLE are still unknown. The purpose of this research was to examine the main molecules and pathways involved in the immunization process that lead to the co-occurrence of AAA and SLE through the utilization of quantitative bioinformatics analysis of publicly available RNA sequencing databases. Moreover, routine blood test information was gathered from 460 patients to validate the findings. Materials and methodsDatasets of both AAA (GSE57691 and GSE205071) and SLE (GSE50772 and GSE154851) were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were analyzed using bioinformatic tools. To determine the functions of the common differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia analyses were conducted. Subsequently, the hub gene was identified through cytoHubba, and its validation was carried out in GSE47472 for AAA and GSE81622 for SLE. Immune cell infiltration analysis was performed to identify the key immune cells correlated with AAA and SLE, and to evaluate the correlation between key immune cells and the hub gene. Subsequently, the routine blood test data of 460 patients were collected, and the result of the immune cell infiltration analysis was further validated by univariate and multivariate logistic regression analysis. ResultsA total of 25 common DEGs were obtained, and three genes were screened by cytoHubba algorithms. Upon validation of the datasets, CXCL1 emerged as the hub gene with strong predictive capabilities, as evidenced by an area under the curve (AUC) > 0.7 for both AAA and SLE. The infiltration of immune cells was also validated, revealing a significant upregulation of neutrophils in the AAA and SLE datasets, along with a correlation between neutrophil infiltration and CXCL1 upregulation. Clinical data analysis revealed a significant increase in neutrophils in both AAA and SLE patients (p < 0.05). Neutrophils were found to be an independent factor in the diagnosis of AAA and SLE, exhibiting good diagnostic accuracy with AUC >0.7. ConclusionThis study elucidates CXCL1 as a hub gene for the co-occurrence of AAA and SLE. Neutrophil infiltration plays a central role in the development of AAA and SLE and may serve to be a potential diagnostic and therapeutic target.

The Enigma of Treating Colorectal Cancer and an Abdominal Aortic Aneurysm

As the average lifespan of individuals increases, malignancies and cardiovascular diseases are becoming a common cause of morbidity and mortality. The treatment of abdominal aortic aneurysms (AAAs) with concomitant diagnosis of colorectal cancer (CRC) is challenging. We aim to review the experience of a single tertiary institution in the management of patients with concurrent diagnosis of AAA and CRC hoping to glean information on how better to treat these patients. This is a retrospective review of all individuals treated between 2009 and 2022 at a large tertiary care center who had a documented diagnosis of CRC and AAA. A careful review of 102 patients resulted in a sample of 89 patients. Of the 89 patients in our cohort, 39 (43.8%) were diagnosed with CRC over 1 year before their AAA diagnosis. Fifteen (16.9%) patients were diagnosed with an AAA over 1 year before their CRC diagnosis and 35 (39.3%) were diagnosed concurrently with both CRC and AAA (Fig). In the concurrent subgroup, AAA was found on cancer staging workup CT scans, and we found the following in regard to their treatment: 12 (34.3%) individuals underwent CRC resection and surveillance of an AAA between 3 and 4 cm, 14 (40.0%) underwent CRC resection and surveillance of an AAA between 4 and 5 cm, and 3 (8.6%) had an AAA of over 5 cm and met criteria for repair; however, they had metastatic CRC and passed on hospice. There were no incidents of aneurysm rupture during surveillance. Ultimately, of the 35 individuals with concomitant AAA and CRC, 6 (17.1%) required treatment for both conditions—3 individuals had an endovascular aneurysm repair (EVAR) 4 to 6 months before CRC surgical resection, 2 had an EVAR after completing chemoradiation, and 1 individual had an EVAR 1.5 weeks after fecal diversion for obstructing CRC. In this group, there were no incidents of operative mortality. The treatment of both CRC and AAA has limited guidelines on how to proceed with the Society of Vascular Surgery level 2C recommendation for concomitant treatment. Our retrospective review of a single tertiary center identified 35 patients who were found to have an AAA during CRC workup. Although the majority had a small AAA that could be surveilled, of those who required repair, we found that EVAR was the sole approach. Further studies are needed to assess long-term outcomes with larger patient volumes from multiple institutions to recommend a definitive treatment algorithm.

P434 PAY ATTENTION TO PARA–AORTIC LYMPH NODES: A PITFALL IN ECHOGRAPHIC ABDOMINAL AORTIC ANEURYSM DIAGNOSIS

Abstract A 65–year–old woman was scheduled for coronary angiography during the pre–surgery evaluation because of an abdominal aortic aneurysm (AAA) detected at ultrasound (Figure). The patient referred worsening dyspnoea and asthenia in the last few months, associated with atypical chest pain. Because of these symptoms and taking into account that AAA patients are very high cardiovascular risk, exclusion of coronary artery desease semmed appropriate. At admission, patient showed enlarged lymph nodes at cervical and inguinal region. In the suspicion of a malignant cancer, a contrast enhanced comupter tomography was scheduled, showing an increase in para–aortic, inguinal, cervical and maxillary lynph nodes size in absence of the AAA (figure). After blood tests and haematologic consultation, a final diagnosis of chornic myeloid leukaemia was made. The echo–colour doppler is the first line imaging test for diagnosis of AAA. However, in some cases it might be not sufficient. Para–aortic lymphadenopathy should be considered as a possible pitfall in the differential diagnosis of abdobinal aortic aneurysm.

The risk of abdominal aortic aneurysm rupture prediction according to computed tomography data

Background. Abdominal aortic aneurysm – is a widespread disease, which in some cases does not have any specific clinical symptoms, but possible complications of this pathology are characterized by high mortality. Aortic aneurism rupture is an extremely serious condition that requires emergency surgical treatment. A timely diagnosis of abdominal aortic aneurysm’s rupture risk remains extremely important, since the patient mortality rate is up to 7 times higher when performing an emergency surgery, than when performing a planned surgery. Aim of study: to improve the diagnosis of abdominal aortic aneurysms instability by creating an assessing scale of aortic rupture risk according to computed tomography data. Materials and methods. CT studies were performed by a 160-slice CT scanner and included the native and arterial phases of the scanning. The MSCT data of 179 patients with diagnosed abdominal aortic aneurysm were retrospectively studied, in 46 of whom the condition was complicated by an aortic rupture. CT scans can reveal a number of specific structural changes in the aorta and also surrounding tissues, which can be regarded as aortic wall rupture prediction. That specific structural changes were stratified by severity and the preliminary results were compared with the treatment tactics and the outcome of the disease. Results. The MSCT data of 179 patients with diagnosed abdominal aortic aneurysm shows that the minimum and sufficient set of abdominal aortic aneurysm rupture predictions are: aneurysm size, a sickle sign, aortic wall draping sign, paraaortic fat induration, the thickness of parietal thrombotic masses. The obtained parameters give the possibility to predict the risks of AAA rupture. The prognostic scale is represented by a 4-point scale for assessing aneurysm parameters. Depending on the influence degree of each parameter, it is assigned a number of points corresponding to the level of prognostic significance. The maximum number of risk factors is 17 points. Finding. The assessing scale of the abdominal aortic aneurysm rupture’s risk according to computed tomography data was developed.

Abdominal Aortic Aneurysm and PET/CT: From Molecular Mechanisms to Potential Molecular Imaging Targets

Abdominal aortic aneurysm (AAA) is the most common and critical aortic disease. Bleeding is the most serious complication from a ruptured AAA, which often results in death. Therefore, early diagnosis and treatment are the only effective means to reduce AAA associated mortality. Positron emission tomography/computed tomography (PET/CT) combines functional and anatomical imaging. The expanded application of PET/CT in the medical field could have benefits for the diagnosis and treatment of patients with AAA. This review explores the efficiency of PET/CT in the diagnosis of AAA based on our understanding of the underlying molecular mechanisms of AAA development.

Identification and characterization of new candidates for abdominal aortic aneurysm screening in patients outside of current accepted guidelines

BackgroundPrevious studies have identified groups of patients with abdominal aortic aneurysm (AAA) that fall outside of currently accepted screening guidelines. Population-based studies have found AAA screening would be cost-effective at a prevalence of 0.5% to 1.0%. The goal of this study was to determine the prevalence of AAA in patients that fall outside of the current screening guidelines. In addition, we analyzed outcomes of the groups with a prevalence of greater than 1%. MethodsUsing the TriNetX Analytics Network, several patient cohorts were abstracted with a diagnosis of ruptured or unruptured AAA based on previously identified groups with a potentially high risk for AAA that fall outside of currently accepted screening guidelines. Groups were also stratified by sex. For groups found to have a prevalence of greater than 1%, the unruptured patients were further analyzed for long-term rates of rupture and included male ever-smokers aged 45 to 65, male never-smokers aged 65 to 75, male never-smokers aged greater than 75, and female ever-smokers aged 65 or greater. Long-term mortality, stroke, and myocardial infarction rates were compared in patients with treated and untreated AAA after propensity score matching. ResultsWe identified 148,279 patients across the four groups with a prevalence of AAA of greater than 1% with female ever-smokers aged 65 or older being the most prevalent (2.73%). In each of the four groups, the rate of AAA rupture increased every 5 years and all had rupture rates of greater than 1% at 10 years. Meanwhile, controls for each of these four subgroups without a previous AAA diagnosis had rupture rates between 0.090% and 0.013% at 10 years. Those who underwent repair of their AAA had decreased incidence of mortality, stroke, and myocardial infarction. Specifically, male ever-smokers aged 45 to 64 had a significant difference in incidence of mortality and myocardial infarction at 5 years and stroke at 1 and 5 years. ConclusionsOur analysis suggests male ever-smokers aged 45 to 65, male never-smokers aged 65 to 75, male never-smokers aged greater than 75, and female ever-smokers aged 65 or greater have a more than 1% prevalence of AAA and, therefore, may benefit from screening. Outcomes were significantly worse compared with well-matched controls in these groups.

Convolutional neural network for automatic detection and characterization of abdominal aortic aneurysm.

We read with great interest the recent publication of Camara et al. on the development of an artificial intelligence (AI)-derived method to enable an automatic detection of abdominal aortic aneurysm (AAA) (1Camara JR TR, Pop A, Matthew BS, Shedd P, Brandon S, Dobrowski BS, Cole J, Knox BS, Abou-Zamzam A, Sharon C, Kiang Journal of Vascular Surgery Cases and Innovative techniquesGoogle Scholar). Using datasets composed of 200 computed tomography angiography (CTA) from patients with AAA and 200 matched control patients with non-aneurysmal infrarenal aorta, the authors developed a method based on convolutional neural network (CNN) and testing demonstrated a robust accuracy of the model (99.1% with an area under the curve of 0.99). Their results point to the interest of such application for the screening of AAA. The VGG-16 neural network architecture was used to develop the AAA detection system and transfer learning was applied to the neural network. It would be interesting to know what was the accuracy of the CNN before transfer learning to show what was the added value of the transfer learning in the pipeline. The use of CNN to classify aneurysmal from non-pathological aortas has been so far poorly reported (2Mohammadi S. Mohammadi M. Dehlaghi V. Ahmadi A. Automatic Segmentation, Detection, and Diagnosis of Abdominal Aortic Aneurysm (AAA) Using Convolutional Neural Networks and Hough Circles Algorithm.Cardiovasc Eng Technol. 2019; 10: 490-499Crossref PubMed Scopus (27) Google Scholar). Nevertheless, it is to note that several studies have recently demonstrated the interest of CNN to develop a fully automatic segmentation of AAA (3Lareyre F. Adam C. Carrier M. Raffort J. Automated Segmentation of the Human Abdominal Vascular System Using a Hybrid Approach Combining Expert System and Supervised Deep Learning.J Clin Med. 2021; 10Crossref Scopus (9) Google Scholar, 4Caradu C. Spampinato B. Vrancianu A.M. Berard X. Ducasse E. Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation.J Vasc Surg. 2021; 74: 246-256 e6Abstract Full Text Full Text PDF Scopus (20) Google Scholar, 5Adam C. Fabre D. Mougin J. Zins M. Azarine A. Ardon R. et al.Pre-surgical and Post-surgical Aortic Aneurysm Maximum Diameter Measurement: Full Automation by Artificial Intelligence.Eur J Vasc Endovasc Surg. 2021; Abstract Full Text Full Text PDF Scopus (12) Google Scholar). These studies showed a good accuracy of the methods compared to human experts and demonstrated the feasibility to use AI for an automatic measurement of AAA maximal diameter (4Caradu C. Spampinato B. Vrancianu A.M. Berard X. Ducasse E. Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation.J Vasc Surg. 2021; 74: 246-256 e6Abstract Full Text Full Text PDF Scopus (20) Google Scholar, 5Adam C. Fabre D. Mougin J. Zins M. Azarine A. Ardon R. et al.Pre-surgical and Post-surgical Aortic Aneurysm Maximum Diameter Measurement: Full Automation by Artificial Intelligence.Eur J Vasc Endovasc Surg. 2021; Abstract Full Text Full Text PDF Scopus (12) Google Scholar, 6Lareyre F. Chaudhuri A. Flory V. Augene E. Adam C. Carrier M. et al.Automatic measurement of maximal diameter of abdominal aortic aneurysm on computed tomography angiography using artificial intelligence.Ann Vasc Surg. 2021; Google Scholar). Hence, CNN offers perspectives to develop applications oriented toward screening and identification of AAA as well as new tools to facilitate its anatomic characterization, which could improve pre-surgical planning and follow-up. As stated by the authors, in addition to develop advanced imaging analysis, ML has the potential to build predictive models of patients’ outcomes and several studies have underlined its interest to better assess AAA growth, risk of rupture, as well as risks of post-operative complications including mortality or re-interventions (7Raffort J. Adam C. Carrier M. Ballaith A. Coscas R. Jean-Baptiste E. et al.Artificial intelligence in abdominal aortic aneurysm.J Vasc Surg. 2020; Abstract Full Text Full Text PDF Scopus (53) Google Scholar, 8Raffort J. Adam C. Carrier M. Lareyre F. Fundamentals in Artificial Intelligence for Vascular Surgeons.Ann Vasc Surg. 2020; 65: 254-260Abstract Full Text Full Text PDF PubMed Scopus (25) Google Scholar, 9Lareyre F. Raffort J. Looking for the Optimal Evaluation of Abdominal Aortic Aneurysm Risk of Rupture.J Endovasc Ther. 2020; 27: 345-346Crossref Scopus (0) Google Scholar). AI has the potential to enhance precision medicine and although further studies are required to evaluate the accuracy and external validation, applications for clinical practice can hopefully be expected within the next few years. This work has been supported by the French government, through the 3IA Côte d’Azur Investments in the Future project managed by the National Research Agency (ANR) with the reference number ANR-19-P3IA-0002.

A pitfall in the echographic diagnosis of abdominal aortic aneurysm: when para-aortic lymph nodes are the trick.

The abdominal aortic aneurysm (AAA) is a potentially fatal asymptomatic disease. It progresses silently with clinical complications that, when they occur, constitute a very serious event, frequently resulting in the patient's exitus. As a result, early detection and treatment are critical because the right therapeutic strategy can halt the disease's natural progression. AAA is frequently discovered as an incidental finding during an abdominal ultrasound or a plain X-ray of the abdomen, which is required for other pathologies. The primary diagnostic tool for AAA identification is abdominal B-mode ultrasound. It is cheap, widely available, non-invasive, and has high diagnostic sensitivity. However, this diagnostic tool may fail in rare cases due to misleading anatomical findings. We present an unusual flaw in the echographic AAA evaluation that should be considered during the diagnostic work-up.

Abdominal Aortic Aneurysms: Epidemiological, Clinical and Echographic Aspects in The Health Structures of Lomé and At The Kara University Hospital (TOGO)

Objective To describe the epidemiological, clinical and arterial Doppler ultrasound aspects of abdominal aortic aneurysm (AAA). Material and methods This is a prospective study with descriptive and analytical aims carried out from January 2019 to March 2022 (3 years) at the cardiovascular exploration center (CEC) "Saint-Esprit" of the association of the people's doctors for the research on cardiovascular diseases (AMP-MCV), at the clinic "Le Printemps" and at the University Hospital of Kara. All patients who underwent arterial Doppler ultrasound of the lower limbs for any reason in these centers during the study period were included. Ultrasound scans were performed or confirmed by a physician with a diploma specializing in vascular Doppler ultrasound. Results We retained 32 Doppler ultrasound scans out of 739 performed for AAA with a frequency of 4.38%. The mean age was 73.5± 9.07 years. The sex ratio M/F was 1.4. The cardiovascular medical history (84.38%) found was: hypertension (33.33%), diabetes (18.52%), dyslipidemia (33.33%) and a combination of diabetes and hypertension (14.81%). The circumstances of discovery were: downstream MI ischemia (72%), incidental finding on abdominal ultrasound (15.63%) and De bakey sign (6.25%). The location of the aneurysms was subrenal (84.4%), suprarenal (9.4%) and both (6.2%). AAAs were fusiform (71.9%) and saccular (28.1%). The size of the aneurysms was greater than 5 cm in 78.17% of patients. High blood pressure increases the probability of the occurrence of subrenal AAA while dyslipidemia increases the occurrence of fusiform AAA. Diabetes increases the probability of occurrence of AAA larger than 7cm. AAAs were thrombosed in 75% of patients. There were extensions of the aneurysms to the iliac arteries in 70.59%. Downstream embolic complications represented 46.88%, in the form of occlusions and tight stenoses. Spontaneous mortality was 81.24%. Conclusion Arterial Doppler ultrasonography is a very important tool in the screening, positive and lesion diagnosis of AAA. The risk factors for AAA are: age over 60 years, male gender, hypertension, diabetes and dyslipidemia. Early detection remains essential, because the spontaneous prognosis is poor.

Association Between Serum MicroRNAs and Abdominal Aortic Aneurysm Diagnosis and Growth

This study aimed to examine the association between serum microRNAs (miRNAs) and diagnosis and growth of abdominal aortic aneurysm (AAA), and to test their diagnostic and prognostic value. The expression levels of 800 miRNA tags were assessed in 108 patients with AAA, 12 age and sex matched healthy controls (HCs), and 12 patients with peripheral artery disease (PAD) using NanoString technology. Findings were assessed in an independent sample of 66 patients with AAA and 29 age and sex matched HCs by reverse transcriptase polymerase chain reaction. AAA growth was assessed by a median of three (interquartile range [IQR] 2, 3) repeat ultrasound scans over a median follow up of 1.1 (IQR 1.0, 2.0) years. The association between the miRNA and AAA diagnosis and growth was examined by regression and linear mixed effects analyses. The diagnostic and prognostic potential of the miRNAs were examined using area under the receiver operator characteristic curve (AUC), net re-classification index (NRI), and Cox hazard analyses. In comparison with HCs, a model combining clinical risk factors, let-7b-5p and miR-548n had an AUC of 98.0% (95% confidence interval [CI] 95.6 - 100.0; p= .003) for diagnosing AAA, which was a significant improvement over clinical risk factors alone (NRI 1.74; 95% CI 1.61 - 1.87; p < .001). Compared with PAD, a model combining clinical risk factors and miR-548n had an AUC of 99.6% (95% CI 98.9 - 100.0, p= .037) for diagnosing AAA, which was a significant improvement over clinical risk factors alone (NRI 1.79, 95% CI 1.68 - 1.91; p < .001). In the longitudinal cohort, none of the miRNAs were able to predict the likelihood of reaching surgical threshold diameter better than clinical risk factors alone. Serum let-7b-5p and miR548n significantly improved the ability to diagnose AAA. None of the miRNAs had independent prognosis value in predicting AAA growth.