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

OBJECTIVE: The 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. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: We 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.

Unusual complication of late presentation deceleration aortic injury.

A 50-year-old patient presented with a stroke. An ascending aortic mass noted by computed tomography was attached to the aortic wall and was found to be thrombus at surgery. Pathologic examination revealed an intraluminal thrombus attached to a focal segment of intimal fragmentation. Sectioning of the aortic wall revealed what were findings consistent with what would be noted with a previously unrecognized traumatic ascending aortic deceleration injury. To our knowledge, this is the first case of a late presentation of deceleration aortic injury, presenting with a thrombus within the ascending aorta.

Evaluating the prevalence of abdominal aortic aneurysms in the United States through a national screening database.

OBJECTIVE: The U.S. Preventative Services Task Force guidelines for abdominal aortic aneurysm (AAA) screening are based mainly on studies of older Caucasian males from non-U.S. POPULATIONS: This study was designed to analyze the findings of a large, all-inclusive AAA screening program in the United States. METHODS: Screening events were held nationally by a U.S. nonprofit organization between 2001 and 2017. AAA screening was offered regardless of risk profile. Participants filled out a demographics form with known comorbidities. Significant risk factors were determined using logistic regression with backward stepwise variable selection. Odds ratios (OR) are reported with 95% confidence intervals (CIs). RESULTS: A total of 9457 screened participants (47% male) were analyzed. The mean age was 67 ± 9 years with 40.8% between 65 and 75 years old. Most participants were Caucasian (83.4%), followed by African American (13.1%). Screened risk factors included hypertension (58.1%), hyperlipidemia (54.9%), smoking (52.0%), cardiac disease (29.2%), diabetes mellitus (18.4%), a family history of AAA (22.4%) or brain aneurysms (8.6%), and body mass index (26.9 ± 5.28). Overall, 267 participants (2.82%) were found to have an AAA (>3 cm). Those ages 65 to 75 had a prevalence of 2.98%. In a fully adjusted, multivariate logistic regression, there was an increased risk of AAA in males (OR, 3.24; 95% CI, 2.39-4.40), current smokers (OR, 3.28; 95% CI, 2.36-4.54), previous smokers (OR, 1.86; 95% CI, 1.41-2.47), cardiac disease (OR, 1.30; 95% CI, 1.01-1.68), family history of AAA (OR, 1.60; 95% CI, 1.20-2.14), and advancing age (P < .0001). Female ever smokers 65 to 75 years old had a prevalence of 1.7%. Male smokers 45 to 54 and 55 to 64 years old had a prevalence of 3.37% and 4.43%, respectively. There was an increased risk of AAA in females with morbid obesity (OR, 5.54; 95% CI, 1.34-22.83 in never smokers and OR, 5.61; 95% CI, 1.04-30.15 in smokers), female smokers with hypertension (OR, 3.22; 95% CI, 1.21-8.58), males with cardiac disease (OR, 2.06; 95% CI, 1.08-3.90 in never smokers and OR, 1.48; 95% CI, 1.05-2.09), male smokers with a family history of AAA (OR, 1.69; 95% CI, 1.61-2.46), and current smokers (OR, 6.33; 95% CI, 2.62-15.24 for females and OR, 2.50; 95% CI, 1.70-3.65 for males). CONCLUSIONS: This study shows that there remain high-risk groups outside the current guidelines that would likely benefit from AAA screening. Risk factors for AAA include male gender, smoking, cardiac disease, family history of AAA, and advancing age. The most significant risk factor is current smoking status.

Coronary "balanced ischemia" with false negative regadenoson Technetium Tc99 m Sestamibi stress test subsequently diagnosed by FFRCT.

A 63-year-old female with multiple cardiovascular risk factors presented with a nontypical chest pain syndrome. Myocardial perfusion imaging (MPI) with a regadenoson (Lexiscan) Technetium Tc99 m (Sestamibi) stress test was interpreted as normal. The patient's chest pain syndrome continued, and subsequently, she presented to the emergency room. Cardiac computed tomographic angiography (CCTA) revealed a partially calcified left main coronary artery (LMCA) plaque with mild positive remodeling, having low attenuation (68 Hounsfield units-HU) in the noncalcified portion. In addition, a significant proximal left anterior descending coronary artery (LAD) noncalcified plaque was also noted. These lesions were hemodynamically significant by CCTA fractional flow reserve (FFRCT ) as evidenced by a significant drop across the LMCA, followed by the LAD and circumflex (CX) vessels. Stenting of the stenosis was performed with resolution of symptoms. The phenomenon of "balanced ischemia" was not readily detected with a regadenoson Technetium Tc99 m perfusion stress test but was readily documented by FFRCT .

Evaluation of athletes with complex congenital heart disease.

As a result of improvements in congenital heart surgery, there are more adults alive today with congenital heart disease (CHD) than children. Individuals with cardiac birth defects may be able to participate in physical activities but require proper cardiovascular evaluation. The American Heart Association and American College of Cardiology released guidelines in 2015 for athletes with cardiovascular abnormalities. The guidelines express that although restriction from competitive athletics may be indicated for some, the majority of individuals with CHD can and should engage in some form of physical activity. This case study demonstrates the importance of combining all aspects of history, physical examination, ECG, and imaging modalities to evaluate cardiac anatomy and function in young athletes with complex CHD.

Novel Application of Tissue Doppler Imaging: A Preliminary Observational Study.

Tissue Doppler imaging was used with transthoracic and transesophageal echocardiography to determine its clinical usefulness beyond visualization of ventricular wall motion. Thirteen novel applications were found: acoustically difficult transthoracic studies, thrombus, mitral chordal motion, shunt detection using saline contrast, spontaneous echo contrast, intra-aortic balloon pump position and function, endocarditis (prosthetic and native), valve strands (prosthetic and native), mobile aortic atheroma, prosthetic valve motion, aortic valve motion in the presence of a calcified aortic annulus, systolic anterior motion of the mitral valve, and cardiac tumors. Tissue Doppler imaging directly affected the ability to make difficult diagnostic decisions with increased confidence and reduced the need for additional studies.