RESUMO
BACKGROUND: Atrial fibrillation and atrial flutter represent the most prevalent clinically significant cardiac arrhythmias. While the CHA2DS2-VASc score is commonly used to inform anticoagulation therapy decisions for patients with these conditions, its predictive power is limited. Therefore, we sought to improve risk prediction for left atrial appendage thrombus (LAAT), a known risk factor for stroke in these patients. METHODS: We developed and validated an explainable machine learning model using the eXtreme Gradient Boosting algorithm with 5 × 5 nested cross-validation. The primary outcome was to predict the probability of LAAT in patients with atrial fibrillation and atrial flutter who underwent transesophageal echocardiogram prior to cardioversion. Our algorithm used 37 demographic, comorbid, and transthoracic echocardiographic variables. RESULTS: A total of 795 patients were included in our analysis. LAAT was present in 11.3% of the patients. The average age of patients was 63.3 years and 34.7% were women. Patients with LAAT had significantly lower left ventricular ejection fraction (29.9% vs 43.5%; p < 0.001), lower E' lateral velocity (5.7 cm vs. 7.9 cm; p < 0.001) and higher E/A ratio (2.6 vs 1.8; p = 0.002). Our machine learning model achieved a high AUC of 0.79, with a high specificity of 0.82, and modest sensitivity of 0.57. Left ventricular ejection fraction was the most important variable in predicting LAAT. Patients were split into 10 buckets based on the percentile of their predicted probability of having thrombus. The lower the percentile (e.g., 10%), the lower the probability of having thrombus. Using a cutoff point of 0.16 which includes 10.0% of the patients, we can rule out thrombus with 100% confidence. CONCLUSION: Using machine learning, we refined the predictive power of predicting LAAT and explained the model. These results show promise in providing better guidance for anticoagulation therapy and cardioversion in AF and AFL patients.
RESUMO
Lyme disease is a progressive infectious disease caused by the Borrelia species that affects multiple organ systems, including the brain, heart, skin, and musculoskeletal systems. The cardiac manifestations of Lyme disease typically present with atrioventricular nodal conduction abnormalities and, more rarely, myocarditis. We report a case of an immunocompromised 57-year-old woman who presented with acute onset shortness of breath, hypervolemia, injective conjunctiva, and global vision loss of the left eye in the setting of a recent tick bite. Serologic testing confirmed borreliosis, and cardiac testing demonstrated acute isolated systolic heart failure without any cardiac conduction system abnormalities on the electrocardiogram. The diagnosis of Lyme carditis was made, and the patient was started on doxycycline with complete recovery of cardiac systolic function. This case demonstrates atypical cardiac manifestations of Lyme disease and highlights the difficulty in workup and understanding of Lyme carditis particularly in immunocompromised patients.
RESUMO
Microvascular dysfunction progressing to pulmonary hypertension can be a primary cause of right ventricular failure or a secondary cause because of an underlying systemic illness. Little is known regarding the etiology and epidemiology of coronary microvascular dysfunction in pulmonary hypertension. Despite this limitation, its presence has been described in patients with pulmonary hypertension. This review focuses on the pathogenesis of cardiac and pulmonary microvascular dysfunction in pulmonary hypertension. Additionally, this review provides a contemporary assessment on the diagnosis and treatment of microvascular dysfunction in patients in pulmonary hypertension. This topic is important to raise awareness of microvascular dysfunction in the coronary and pulmonary circulation, so that future studies will investigate its impact on the pulmonary hypertension patient cohort.