Abdominal Aortic Aneurysm Screening Research Articles

Determinants for non-attendance in abdominal aortic aneurysm (AAA) screening

ObjectiveBenefits of abdominal aortic aneurysm (AAA) screenings are dependent on high attendance. We sought to examine self-reported reasons for non-attendance and to describe differences in socioeconomic factors, comorbidities, and risk factors between non-attenders and attenders. MethodsAll non-attenders to screenings at Oslo University Hospital in 2022 were contacted by letter/phone with a questionnaire about reasons for non-attendance, socioeconomic factors, comorbidities, and risk factors. For all the attenders in 2022, information on comorbidities and risk factors was available in the screening database, and a randomized selection (1:1 to non-attenders) was contacted by phone to obtain information on socioeconomic factors. ResultsThere were 259 non-attenders and 1483 attenders to screenings in 2022. Data on comorbidities and risk factors were available for all attenders. For the 259 men contacted in each group, the response rate was 39% for the non-attenders and 72% for the attenders. Among non-attenders who replied, 57% did not remember receiving an invitation or forgot the appointment; however, 76% replied that they would attend an AAA screening if they were to receive a second invitation. Compared with attenders, non-attenders were more likely to live alone (41% vs 22%; P = .001), receive home nursing (10% vs 0.5%; P < .001), and to smoke (27% vs 14%; P < .001), and they were less likely to have a higher education (54% vs 71%; P = .004). ConclusionsContacting non-attenders yielded a reply from only 39%; thus, reasons for non-attendance are still obscured among the majority. Among those who replied, the main reasons for non-attendance were not remembering receiving an invitation or forgetting the appointment—modifiable factors that could be accounted for in the invitation process. There were significantly more smokers (the strongest modifiable AAA risk factor) among non-attenders, indicating that non-attenders would especially benefit from AAA screenings.

Screening Men and Women above the Age of 50 Years for Abdominal Aortic Aneurysm: A Pilot Study in an Upper Middle Income Country

Screening for abdominal aortic aneurysm (AAA) is recommended in high risk populations based on local conditions. Differences in lifestyle and risk factors between countries with different income status make risk stratification based on geographic location necessary. The majority of epidemiological studies on AAA have reported data from high income countries. The aim of this study was to explore the prevalence and risk factors for AAA in an upper middle income country in Eastern Europe. A pilot screening project for AAA, supported by a mass media campaign, was conducted in 2023 in seven cities in Serbia. Ultrasound evaluation of the abdominal aorta was performed by a registered vascular surgeon on individuals who agreed to participate. Participants who attended screening completed a questionnaire on demographic and clinical information. To assess risk factors for AAA, univariable logistic regression analysis was performed to compute the odds ratio (OR) with 95% confidence interval (CI). Multivariable logistic regression was subsequently performed with adjustments for sex, age, family history of AAA, and other relevant factors. A total of 4 046 participants (51.2% male and 48.8% female; mean age 68.8 ± 7.6 years) responded to the campaign. An aneurysm was found in 195 (4.8%) screened individuals (8.2% of men and 1.3% of women). In males aged 50 - 64 years, the prevalence of AAA was 5.4%. Male sex, older age, family history of AAA, being a smoker or ex-smoker, being overweight, and alcohol consumption were predictors of AAA in the univariable analysis. After adjustments in the multivariable analysis, male sex (OR 8.04, 95% CI 4.87 - 13.28), older age (OR 1.04, 95% CI 1.02 - 1.07), positive family history (OR 2.47, 95% CI 1.61 - 3.78), smoker status (OR 3.10, 95% CI 2.10 - 4.59), ex-smoker status (OR 2.13, 95% CI 1.39 - 3.27), and being overweight (OR 1.85, 95% CI 1.25 - 2.74) were independent risk factors for AAA. The prevalence of AAA has not been reduced in all countries, and screening strategies might be changed based on local epidemiological data. The results of this pilot study underline the importance of exploring the prevalence of AAA in populations with a high prevalence of smoking.

Abdominal Aortic Aneurysm Screening in a Population Older Than 50 in an Upper Middle Income Country

Abdominal Aortic Aneurysm Screening in a Population Older Than 50 in an Upper Middle Income Country

Evaluating growth patterns of abdominal aortic aneurysms among women

ObjectiveThough initially protected from vessel dilation by estrogen, women may experience rapid abdominal aortic aneurysm (AAA) growth post-menopause. The rate of growth has been poorly defined in prior literature. Here, we describe aneurysm growth in a cohort of women found through an AAA screening program. MethodsWomen with AAAs were retrospectively identified. Aortic imaging was reviewed, and measurements of maximum transverse and anterior-posterior diameters were completed. Growth was stratified by the type of aortic pathology (fusiform aneurysm, aortic ectasia, dissection with aneurysmal degeneration, saccular aneurysm) as well as size category (<3 cm, 3.0-3.9 cm, 4.0-4.9 cm, ≥5.0 cm) at diagnosis. ResultsA cohort of 488 women was identified; 286 had multiple scans for review. The mean age of the entire cohort was 75 ± 9.9 years. Stratified by type of pathology, the mean age was 76 ± 8.9 years in patients with a fusiform AAA, 74 ± 9.8 years in ectasia, 65 ± 13.7 years in dissection, and 76 ± 5.6 years in saccular aneurysms. The maximum growth was highest in women with fusiform AAAs, followed by dissection, ectasia, and saccular pathology (9.7 mm, 7.0 mm, 3.0 mm, and 2.2 mm, respectively; P < .001). Comparing mean growth by year, the highest mean growth was in fusiform AAAs (3.6 mm vs 1.75 mm in dissection; P < .001). The Shapiro-Wilk test demonstrated that mean growth per year was non-normally distributed with a right skew. Stratified by aortic diameter at the time of diagnosis, mean growth/year increased with increasing size at diagnosis in fusiform AAAs and dissection (0.91 mm for <3 cm, 2.34 mm for 3.0-3.9 cm, 2.49 mm for 4.0-4.9 mm, and 6.16 mm for ≥5.0 cm in patients with fusiform AAAs vs 0.57 mm, 0.94 mm, 1.87 mm, and 2.66 mm, respectively, for patients with dissection). Smoking history was associated with a higher mean growth/year (2.6 mm vs 3.3 mm; P < .001). Conversely, patients with a family history of AAA had a lower mean growth/year (3.2 mm vs 1.5 mm; P < .001). ConclusionsThe rate of aneurysm growth in women varies based on pathology and aneurysm size, and women experience rapid aneurysm growth at sizes greater than 4.5 cm. Current screening guidelines are inadequate, and our results demonstrate that the rate of growth of fusiform aneurysms in women is faster than in men at a smaller size and may warrant more frequent surveillance than current Society for Vascular Surgery recommendations to prevent risk of increased morbidity.

One-time screening for abdominal aortic aneurysm in Ontario, Canada: a model-based cost-utility analysis.

Screening programs for abdominal aortic aneurysm (AAA) are not available in Canada. We sought to determine the effectiveness and costutility of AAA screening in Ontario. We compared one-time ultrasonography-based AAA screening for people aged 65 years to no screening using a fully probabilistic Markov model with a lifetime horizon. We estimated life-years, quality-adjusted life-years (QALYs), AAA-related deaths, number needed to screen to prevent 1 AAA-related death and costs (in Canadian dollars) from the perspective of the Ontario Ministry of Health. We retrieved model inputs from literature, Statistics Canada, and the Ontario Case Costing Initiative. Screening reduced AAA-related deaths by 84.9% among males and 81.0% among females. Compared with no screening, screening resulted in 0.04 (18.96 v. 18.92) additional life-years and 0.04 (14.95 v. 14.91) additional QALYs at an incremental cost of $80 per person among males. Among females, screening resulted in 0.02 (21.25 v. 21.23) additional life-years and 0.01 (16.20 v. 16.19) additional QALYs at an incremental cost of $11 per person. At a willingness-to-pay of $50 000 per year, screening was cost-effective in 84% (males) and 90% (females) of model iterations. Screening was increasingly cost-effective with higher AAA prevalence. Screening for AAA among people aged 65 years in Ontario was associated with fewer AAA-related deaths and favourable cost-effectiveness. To maximize QALY gains per dollar spent and AAA-related deaths prevented, AAA screening programs should be designed to ensure that populations with high prevalence of AAA participate.

Patient-Friendly Summary of the ACR Appropriateness Criteria®: Screening for Abdominal Aortic Aneurysm

Patient-Friendly Summary of the ACR Appropriateness Criteria®: Screening for Abdominal Aortic Aneurysm

CACTUSS: Common Anatomical CT-US Space for US examinations.

The detection and treatment of abdominal aortic aneurysm (AAA), a vascular disorder with life-threatening consequences, is challenging due to its lack of symptoms until it reaches a critical size. Abdominal ultrasound (US) is utilized for diagnosis; however, its inherent low image quality and reliance on operator expertise make computed tomography (CT) the preferred choice for monitoring and treatment. Moreover, CT datasets have been effectively used for training deep neural networks for aorta segmentation. In this work, we demonstrate how leveraging CT labels can be used to improve segmentation in ultrasound and hence save manual annotations. We introduce CACTUSS: a common anatomical CT-US space that inherits properties from both CT and ultrasound modalities to produce an image in intermediate representation (IR) space. CACTUSS acts as a virtual third modality between CT and US to address the scarcity of annotated ultrasound training data. The generation of IR images is facilitated by re-parametrizing a physics-based US simulator. In CACTUSS we use IR images as training data for ultrasound segmentation, eliminating the need for manual labeling. In addition, an image-to-image translation network is employed for the model's application on real B-modes. The model's performance is evaluated quantitatively for the task of aorta segmentation by comparison against a fully supervised method in terms of Dice Score and diagnostic metrics. CACTUSS outperforms the fully supervised network in segmentation and meets clinical requirements for AAA screening and diagnosis. CACTUSS provides a promising approach to improve US segmentation accuracy by leveraging CT labels, reducing the need for manual annotations. We generate IRs that inherit properties from both modalities while preserving the anatomical structure and are optimized for the task of aorta segmentation. Future work involves integrating CACTUSS into robotic ultrasound platforms for automated screening and conducting clinical feasibility studies.

Internal iliac debranching in combination with abdominal aortic stent graft to treat bilateral common iliac aneurysms

Introduction&#x0D; Common iliac artery aneurysms are often diagnosed during routine screening for infrarenal abdominal aortic aneurysms. Preserving the internal iliac artery helps avoid colonic ischemia and buttocks claudication. Hybrid surgery combining internal iliac artery transposition and endovascular treatment is a method with good early and long-term results.&#x0D; Methods&#x0D; We report of a case of bilateral common iliac artery aneurysm treated by hybrid surgery and endovascular intervention at Dong Nai General Hospital&#x0D; Results&#x0D; A 69 year-old male, diagnosed with bilateral common iliac artery aneurysm and left internal iliac artery occlusion. Surgical transposition was performed to repimplant the right internal iliac artery into the right external iliac artery, folowed by endovascular treatment, the right branch of the graft was placed at the external iliac artery, the left branch of the graft was placed at the common iliac artery. Postoperative condition was stable, no early complications recorded&#x0D; Conclusion&#x0D; Hybrid surgery to treat iliac aortic aneurysms and common iliac artery aneurysms has quite good mid- and long-term results. The initial successful implementation of this technique at Dong Nai General Hospital contributes to team development, reduces the load on central hospitals and brings practical benefits to patients.

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.

Implicit screening of abdominal aortic aneurysms among veterans using lumbar spine MRI

BackgroundEarly detection of abdominal aortic aneurysms (AAAs) is critical given the high morbidity and mortality of a ruptured aneurysm. Screening ultrasound is recommended for men 65 and 75 years of age with a smoking history. However, studies have shown that the rate of ultrasound screening is low and that implicit AAA screening by abdominal imaging studies that were not originally intended for AAA screening can play a major role in AAA detection. ObjectiveThe main objective was to evaluate the role of lumbar spine MRIs as an implicit AAA screening study by assessing the detection rate of AAAs in a broader cohort of veterans that included screening and non-screening populations. Methods4085 consecutive lumbar spine MRIs from our institution between 2/2020 and 9/2023 were retrospectively reviewed. Each study was labeled AAA present, AAA not present, or indeterminate by radiologists. The correlation between the presence of AAAs and cardiovascular risk factors was assessed using multinomial logistic regression. ResultsAAAs were present in 89 studies (2.2 %) from 80 patients (mean age 75.8 (56–93), M:F 10:0) and absent in 3935 cases (96.3 %) from 3310 patients (mean age 61.7 (19–100), M:F 9:1). Indeterminate cases (n = 61, 1.5 %) were mainly due to incomplete visualization (70.5 %). Mean AAA size was 3.6 cm with most AAAs (n = 43) smaller than 3.5 cm. Sixteen AAAs were 3.5–3.9 cm, 16 between 4 and 4.9cm, and 6 between 5 and 5.9 cm. Artifact precluded measurements in 8 cases. Among the AAA-positive cases, 20 had no prior documentation of AAA. Twenty-one patients with AAAs would not have met the criteria for the routine AAA screening ultrasound. Higher rates of hypertension, hyperlipidemia, and smoking were observed for the AAA cohort at 78.8 % (OR 2.037, CI 1.160–3.576, P = .013), 82.5 % (2.808, 1.543-5.110, P < .001), and 75 % (3.340, 1.979–5.638, P < .001), respectively, compared to the matched no-AAA cohort (58.2 %, 57.6 %, and 50.8 %; n = 2055). Conclusion: Lumbar spine MRI is a valid modality for implicit screening of AAAs. Clinical impactThose interpreting lumbar spine MRIs should be vigilant about assessing for AAAs, especially in men with a history of hypertension, hyperlipidemia, or tobacco smoking.

Machine learning-based prediction of abdominal aortic aneurysms for individualized patient care

ObjectiveThe United States Preventative Services Task Force guidelines for screening for abdominal aortic aneurysms (AAA) are broad and exclude many at risk groups. We analyzed a large AAA screening database to examine the utility of a novel machine learning (ML) model for predicting individual risk of AAA. MethodsWe created a ML model to predict the presence of AAAs (>3 cm) from the database of a national nonprofit screening organization (AAAneurysm Outreach). Participants self-reported demographics and comorbidities. The model is a two-layered feed-forward shallow network. The ML model then generated AAA probability based on patient characteristics. We evaluated graphs to determine significant factors, and then compared those graphs with a traditional logistic regression model. ResultsWe analyzed a cohort of 10,033 patients with an AAA prevalence of 2.74%. Consistent with logistic regression analysis, the ML model identified the following predictors of AAA: Caucasian race, male gender, advancing age, and recent or past smoker with recent smoker having a more profound affect (P < .05). Interestingly, the ML model showed body mass index (BMI) was associated with likelihood of AAAs, especially for younger females. The ML model also identified a higher than predicted risk of AAA in several groups, including female nonsmokers with cardiac disease, female diabetics, those with a family history of AAA, and those with hypertension or hyperlipidemia at older ages. An elevated BMI conveyed a higher than expected risk in male smokers and all females. The ML model also identified a complex relationship of both diabetes mellitus and hyperlipidemia with gender. Family history of AAA was a more important risk factor in the ML model for both men and women too. ConclusionsWe successfully developed an ML model based on an AAA screening database that unveils a complex relationship between AAA prevalence and many risk factors, including BMI. The model also highlights the need to expand AAA screening efforts in women. Using ML models in the clinical setting has the potential to deliver precise, individualized screening recommendations.

Evaluation of outcomes and utility of abdominal aortic aneurysm surveillance in octogenarians and nonagenarians.

The aim of this study was to evaluate the utility of our regional abdominal aortic aneurysm (AAA) screening programme in octogenarians and nonagenarians. This was to help decide whether discontinuation might be appropriate in certain instances. Primary outcomes were the number of patients who reached threshold (5.5cm) and the number where intervention was offered. Secondary outcome was cost effectiveness. A retrospective review of a regional AAA surveillance database was carried out to evaluate outcomes. Data collected included patient age, sex, date of first and last scan, initial and latest size of aneurysm, outcome, time under surveillance and total number of scans. Patients were divided into three groups (80-84 years, 85-89 years and 90+ years). The number of patients in this age group was 354. Only 2.0% (n=7) of patients underwent intervention. Threshold size was achieved in 8.3% (n=18), 14.8% (n=18) and 26.7% (n=4), in the age groups 80-84 years, 85-89 years and 90+ years, respectively. Of these patients, operative intervention was possible in 2.8% (n=6), 0.8% (n=1) and 0% (n=0), respectively. A relatively small number of octogenarians and nonagenarians reach the threshold size during surveillance. An even smaller proportion require repair of their aneurysm. While there may be a role for AAA surveillance in octogenarians in highly selected groups, these data should inform the discussions made with individual patients. It should also inform future evaluation of such surveillance.

Interacting with best practice advisory (BPA) notifications in the electronic medical record significantly improves screening rates for abdominal aortic aneurysms

ObjectiveBest practice advisory notifications (BPAs) have become an integral part of many electronic medical record (EMR) systems. These communications alert providers to recommended therapy or screenings for patients depending on factors found within the EMR. Our goal was to evaluate the impact of BPAs on the rate of abdominal aortic aneurysm (AAA) screening in patients who met guidelines for screening in a single-center EMR. MethodsWe reviewed all patients who triggered a BPA alert for AAA screening from December 2018 to December 2021 in a single tertiary academic setting. The BPA alerts the provider when closing the chart when a patient meets the criteria for AAA screening based on the United States Preventive Services Task Force recommendations of screening male patients aged 65 to 75 years with a smoking history. Provider responses to these triggers were analyzed, and the predictors of response to the advisory and its impact on AAA screening for individual patients within 6 months of the alert was evaluated. ResultsOver this period, 1292 patients triggered the BPA for AAA screening. After excluding deceased patients, 1205 patients were included in the final analysis. Providers interacted with rather than dismissed the BPA in 20.4% of patients. The overall screening rate in this patient cohort was 28.28%. Interacting with the BPA significantly increased the odds of being appropriately screened for a AAA (odds ratio, 2.48). A higher number of visits and BPA triggers correlated with increased odds of undergoing screening for AAA (odds ratios, 1.08 and 1.02, respectively). Additionally, patients who underwent screening were younger in age and more often African American as compared with other races. The presence and number of comorbid conditions were not associated with screening rates, although hyperlipidemia was associated with positive response to BPA. ConclusionsThe overall rate of appropriate AAA screening is low, despite the presence of BPAs. Positively interacting with rather than dismissing the BPA is correlated with an increased rate of appropriate AAA screening. Providers were more likely to screen patients if the patient was younger, had more health care system visits, or if the trigger was delivered more often to members of the health care team. Further study is needed to evaluate provider factors that will result in an increased adherence to recommended screening guidelines.

Incidental Cardiovascular Abnormalities in the Abdominal Aortic Aneurysm (AAA) Surveillance Population During the AAA Get Fit Trial: A Case Series and Review of the Literature.

Background The prevalence of cardiovascular disease and incidence of major adverse cardiovascular events (MACEs) is very high among the abdominal aortic aneurysm (AAA) surveillance population. Formal assessments of and interventions to reduce cardiovascular risk are not a routine part of the surveillance programme at present. However, its potential importance is highlighted by incidental findings during the AAA Get Fit Trial, a randomised controlled trial which included baseline cardiopulmonary exercise testing (CPET). We speculate that CPET can act as an opportunistic screening programme to identify cardiovascular disease in AAA surveillance patients. Methods The AAA Get Fit Trial was a prospective, randomised controlled trial at a tertiary vascular centre, Manchester University NHS Foundation Trust, conducted between November 2017 and August 2019. Patients underwent CPET at baseline, 8, 16, 24 and 36 weeks as well as clinical history and examination and blood tests. We report on incidental cardiovascular abnormalities diagnosed during the trial. Results Of the 59 participants in the trial, four (6.8%) were identified to have abnormal findings suggestive of unstable cardiovascular disease. On subsequent further investigation, two patients were diagnosed and treated for severe coronary artery disease after abnormal ECG findings were noted during CPET. One patient was diagnosed with unstable angina after obtaining a detailed history on baseline assessment which was treated medically before going on to have a successful elective AAA repair. Conclusions There is a high incidence of MACEs among this high-risk population both pre and perioperatively. Identifying and treating cardiovascular disease among the AAA surveillance population must be a focus of the future AAA screening programme.

Expansion of Abdominal Aortic Aneurysm Screening and Ultrasound Utilization and Diagnosis

This cohort study uses a deidentified national administrative claims database to assess the association of eligibility expansion with abdominal aortic aneurysm screening and diagnosis.

Development and Validation of a Machine Learning Prediction Model to Improve Abdominal Aortic Aneurysm Screening

Development and Validation of a Machine Learning Prediction Model to Improve Abdominal Aortic Aneurysm Screening

Current Imaging Strategies in Patients with Abdominal Aortic Aneurysms.

An abdominal aortic aneurysm (AAA) is defined as a localized dilatation of the abdominal aorta of ≥ 3 cm. With a prevalence of 4-8 %, AAA is one of the most common vascular diseases in Western society. Radiological imaging is an elementary component in the diagnosis, monitoring, and treatment planning of AAA patients. This is a narrative review article on preoperative imaging strategies of AAA, incorporating expert opinions based on the current literature and standard-of-care practices from our own center. Examples are provided to illustrate clinical cases from our institution. Radiological imaging plays a pivotal role in the initial diagnosis and monitoring of patients with AAA. Ultrasound is the mainstay imaging modality for AAA screening and surveillance. Contrast-enhanced CT angiography is currently considered the gold standard for preoperative imaging and image-based treatment planning in AAA repair. New non-contrast MR angiography techniques are robustly applicable and allow precise determination of aortic diameters, which is of critical importance, particularly with regard to current diameter-based surgical treatment guidelines. 3D imaging with multiplanar reformation and automatic centerline positioning enables more accurate assessment of the maximum aortic diameter. Modern imaging techniques such as 4D flow MRI have the potential to further improve individualized risk stratification in patients with AAA. · Ultrasound is the mainstay imaging modality for AAA screening and monitoring. · Contrast-enhanced CT angiography is the gold standard for preoperative imaging in AAA repair. · Non-contrast MR angiography allows for accurate monitoring of aortic diameters in AAA patients. · Measurement of aortic diameters is more accurate with 3D-CT/MRI compared to ultrasound. · Research seeks new quantitative imaging biomarkers for AAA risk stratification, e. g., using 4D flow MRI.

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.

Association between socioeconomic deprivation and presentation with a ruptured abdominal aortic aneurysm

ObjectiveGiven the ongoing nature of research in the social determinants space and urges to improve United States Preventive Services Task Force screening efforts for abdominal aortic aneurysms (AAAs), this project aims to characterize the association between the level of socioeconomic deprivation, rurality, and ruptured AAA (rAAA) presentation across the United States. MethodsWe queried the Vascular Quality Initiative registry (2010-2019) for patients with AAAs. The area deprivation index (ADI) is an index from 1 to 100 used to capture socioeconomic status. ADI was grouped into quintiles, with the most deprived regions being quintile 5 and having the highest ADI index. Multivariable logistic regression assessed the association between ADI, rurality, and rAAA presentation overall and before age 65. ResultsOf the 82,909 patients included, 11,458 patients (14%) resided in the most socioeconomically deprived regions, and 18,083 patients (22%) lived in rural regions. Overall, 6831 patients (8.2%) experienced an rAAA, with 4696 patients (69%) residing in the three most deprived quintiles. Most patients underwent endovascular repair (n = 67,933; 82%), followed by open repair (n = 14,976; 18%). On multivariable analysis, residence in the most socioeconomically deprived region was associated with a near 1.5-fold increased odds of presenting with an rAAA compared with a residence in the least deprived regions (odds ratio [OR], 1.46; 95% confidence interval [CI], 1.31-1.63; P < .001), whereas urban residence was associated with a decreased odds to present with an rAAA compared with rural residence (OR, 0.84; 95% CI, 0.79-0.89; P < .001). When stratifying the study population by the United States Preventive Services Task Force recommended age for AAA screening (65 years old), 14,147 patients (17%) were under 65. Of those under 65, 1381 patients (9.8%) experienced a rAAA, and 9955 patients (71%) resided in the three most deprived quintiles. Residence in the most socioeconomically deprived region was associated with an increased odds of presenting with an rAAA compared with residence in the least deprived region (OR, 1.31; 95% CI, 1.01-1.69; P = .042). However, there were no significant associations between rural residence and increased rAAA presentation among individuals under 65 (OR, 1.07; 95% CI, 0.93-1.23; P = .36). ConclusionsAmong all patients in this study, patients residing in highly socioeconomically deprived or rural regions were more likely to present with an rAAA, but among those under 65, only residence in a socioeconomically deprived area was associated with increased odds of rAAA presentation. Understanding the effects of socioeconomic deprivation on rAAA presentation can identify at-risk populations for early AAA screening before rupture.

Proposed public policies to improve outcomes in vascular surgery: an experts' forum.

To evaluate outcomes of vascular surgeries and identify strategies to improve public vascular care. This was a descriptive, qualitative, and cross-sectional survey involving 30 specialists of the Hospital Israelita Albert Einstein via Zoom. The outcomes of vascular procedures performed in the Public Health System extracted through Big Data analysis were discussed, and 53 potential strategies to improve public vascular care to improve public vascular care. There was a consensus on mandatory reporting of some key complications after complex arterial surgeries, such as stroke after carotid revascularization and amputations after lower limb revascularization. Participants agreed on the recommendation of screening for diabetic feet and infrarenal abdominal aortic aneurysms. The use of Telemedicine as a tool for patient follow-up, auditing of centers for major arterial surgeries, and the concentration of complex arterial surgeries in reference centers were also points of consensus, as well as the need to reduce the values of endovascular materials. Regarding venous surgery, it was suggested that there should be incentives for simultaneous treatment of both limbs in cases of varicose veins of the lower limbs, in addition to the promotion of ultrasound-guided foam sclerotherapy in the public system. After discussing the data from the Brazilian Public System, proposals were defined for standardizing measures in population health care in the area of vascular surgery. Notification of complications of arterial surgeries is essential in identifying strategies to improve surgical outcomes. Screening of prevalent and/or morbid diseases allows early intervention and prevention of complications. Use of telemedicine in vascular follow-up allows optimizing the use of resources and reducing the burden on health services. Concentrating complex cases in reference hospitals leads to improved surgical outcomes.