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Abstract Objectives Endocardial trabeculae undergo varicose changes and hyperplasia in response to hemodynamic influences and are a variable phenotype reflecting changes in disease. Fractal analysis has been used to analyze the complexity of endocardial trabeculae in a variety of cardiomyopathies. The aim of this paper was to quantify the myocardial trabecular complexity through fractal analysis and to investigate its predictive value for the diagnosis of heart failure with preserved ejection fraction (HFpEF) in patients with multivessel coronary artery disease (CAD). Methods The retrospective study population consisted of 97 patients with multivessel CAD, 39 of them were diagnosed with HFpEF, while 46 healthy volunteers were recruited as controls. Fractal dimension (FD) was obtained through fractal analysis of endocardial trabeculae on LV short-axis cine images. Logistic regression analyses were used to confirm the predictors and compare different prediction models. Results Mean basal FD was significantly higher in patients with HFpEF than in patients without HFpEF or in the healthy group (median: 1.289; IQR: 0.078; p

Abstract Background Multiple case reports and case series have been published on heart failure due to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs), yet the management and outcome of the said disease have been scarcely discussed in sufficient details. This review is aimed at characterizing the signs, symptoms, laboratory parameters, and outcomes of this entity by analyzing recent published case reports and case series reporting new-onset heart failure in non-small cell lung cancer tumor (NSCLC) patients who are being treated with EGFR TKIs. Methods This is a systematic review of case reports and case series for cases of EGFR TKI-induced heart failure. A systematic search was conducted across a number of databases starting with PubMed databases utilizing its MeSH database; after that, a complementary search through Google Scholar was conducted. Results In total, 23 cases of epidermal growth factor receptor tyrosine kinase inhibitor-induced heart failure were included. The majority of the reported case were females (20 females and three males) with a male-to-female ratio of 1:6.6. Ages ranged from 47 to 91 years of age with a mean age of 70.73 and a median of 71 years of age. Symptom improvement and being symptom-free from a heart failure perspective after treatment from the acute event were observed in 18 cases (78.26%) while heart failure progressively worsened and led to the death of the patient in only one case (4.3%). Conclusion The utilization of EGFR TKIs in NSCLCs has been associated with a better outcome and fewer side effects when compared to classical chemotherapeutic agents. However, cardiotoxic effects, such as heart failure, could be significant for a small proportion of patients. Recent papers have reported heart failure in younger and cardiac risk-free patients. Still, it is only advised to monitor for heart failure in the high-risk group. Treatment should be individualized and based on a case-by-case basis.

Abstract Diabetes is a significant health concern with more than 30 million Americans living with diabetes. Onset of diabetes increases the risk for various complications, including kidney disease, myocardial infractions, heart failure, stroke, retinopathy, and liver disease. In this paper, we study and predict the onset of these complications using a network-based approach by identifying fast and slow progressors. That is, given a patient’s diagnosis of diabetes, we predict the likelihood of developing one or more of the possible complications, and which patients will develop complications quickly. This combination of "if a complication will be developed” with ”how fast it will be developed” can aid the physician in developing better diabetes management program for a given patient.