Predictors of left atrial appendage thrombus in atrial fibrillation patients undergoing cardioversion.

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.

Recurrent diabetic myonecrosis in an African American woman with long-standing uncontrolled type 2 diabetes: a case report.

BACKGROUND: Diabetic myonecrosis, also called diabetic muscle infarction, is an uncommon complication of uncontrolled diabetes mellitus and is frequently underdiagnosed. The objective of this case report is to highlight the challenges in the early diagnosis and treatment of this disease. CASE PRESENTATION: A 51-year-old African American woman with a long history of uncontrolled diabetes mellitus presented to her primary care physician with right thigh pain. A diagnosis of diabetes myonecrosis was made on the basis of magnetic resonance imaging, biopsy, and negative autoimmune panel. After failing conservative treatment, the patient was treated with prednisone with gradual improvement of her symptoms. However, she had a recurrence of myonecrosis almost one year after her original presentation, which was also treated with prednisone. The recurrence had a shorter course and the patient recovered well. Challenges to the treatment in this patient were her debilitating pain and her underlying chronic kidney disease. CONCLUSIONS: A high index of suspicion for diabetic myonecrosis is necessary when a patient with diabetes presents with unilateral focal leg pain and swelling. Magnetic resonance imaging and biopsy can help confirm the diagnosis. Prednisone may be considered in patients who lack spontaneous regression with just rest. Educating healthcare professionals about this uncommon condition is of utmost importance in avoiding unnecessary testing and inappropriate treatment.

Pharmacological Therapy Optimization for Heart Failure: A Practical Guide for the Internist.

Heart failure carries significant morbidity and mortality and affects a large population of patients cared for predominantly by primary care physicians. The complexity of managing heart failure patients is increasing as new therapies continue to emerge. This review outlines important clinical pearls and proposes strategies for optimization of medical therapy.

Evaluation of response to stereotactic radiosurgery in patients with radioresistant brain metastases.

PURPOSE: Renal cell carcinoma (RCC) and melanoma have been considered 'radioresistant' due to the fact that they do not respond to conventionally fractionated radiation therapy. Stereotactic radiosurgery (SRS) provides high-dose radiation to a defined target volume and a limited number of studies have suggested the potential effectiveness of SRS in radioresistant histologies. We sought to determine the effectiveness of SRS for the treatment of patients with radioresistant brain metastases. MATERIALS AND METHODS: We performed a retrospective review of our institutional database to identify patients with RCC or melanoma brain metastases treated with SRS. Treatment response were determined in accordance with the Response Evaluation Criteria in Solid Tumors. RESULTS: We identified 53 radioresistant brain metastases (28% RCC and 72% melanoma) treated in 18 patients. The mean target volume and coverage was 6.2 ± 9.5 mL and 95.5% ± 2.9%, respectively. The mean prescription dose was 20 ± 4.9 Gy. Forty lesions (75%) demonstrated a complete/partial response and 13 lesions (24%) with progressive/stable disease. Smaller target volume (p < 0.001), larger SRS dose (p < 0.001), and coverage (p = 0.008) were found to be positive predictors of complete response to SRS. CONCLUSION: SRS is an effective management option with up to 75% response rate for radioresistant brain metastases. Tumor volume and radiation dose are predictors of response and can be used to guide the decision-making for patients with radioresistant brain metastases.