Cardiac amyloidosis describes clinically significant involvement of the heart by amyloid deposition, which may or may not be associated with involvement of other organs. The purpose of this review is to summarize the current state of evidence for the effective evaluation and management of cardiac amyloidosis. Acquired systemic amyloidosis occurs in more than 10 per million person-years in the U.S. population. Although no single noninvasive test or abnormality is pathognomonic of cardiac amyloid, case-control studies indicate that echocardiographic evidence of left ventricular wall thickening, biatrial enlargement, and increased echogenicity in conjunction with reduced electrocardiographic voltages is strongly suggestive of cardiac amyloidosis. Furthermore, newer echocardiographic techniques such as strain and strain rate imaging can demonstrate impairment in longitudinal function before ejection fraction becomes abnormal. Recent observational studies also suggest that cardiovascular magnetic resonance imaging yields characteristic findings in amyloidosis, offering promise for the early detection of cardiac involvement, and the presence of detectable cardiac troponin and elevated B-type natriuretic peptide in serum of affected patients portends an adverse prognosis. Management strategies for cardiac amyloid are largely based on nonrandomized single-center studies. One of the few published randomized studies shows the superiority of oral prednisolone and melphalan compared with colchicine in systemic AL amyloidosis. Intermediate-dose infusional chemotherapy regimes (such as vincristine, adriamycin, and dexamethasone) and high-dose chemotherapy with peripheral stem cell rescue have been used widely, but treatment-related mortality remains substantial with chemotherapy. Recent studies also indicate promising strategies to stabilize the native structures of amyloidogenic proteins; inhibit fibril formation; and disrupt established deposits using antibodies, synthetic peptides, and small-molecule drugs.
1. Anaemia is an independent predictor of mortality in pro-atherosclerotic conditions with impaired endothelial function, such as diabetes and chronic kidney disease. However, the prevalence of anaemia in hypertension, a condition characterized by endothelial dysfunction, is unclear. 2. Haemoglobin concentration, renal function and echocardiographic parameters of 187 consecutive patients (M : F 83 : 104; mean (+/-SD) age 58 +/- 15 years) who underwent ambulatory blood pressure monitoring between 2005 and 2006 were assessed in a tertiary level university hospital. 3. The prevalence of normocytic anaemia in our cohort of hypertensive patients was 16% and was higher in patients with uncontrolled hypertension (20%) than among those with well-controlled hypertension (4%; P = 0.03). Red cell indices (mean corpuscular volume, mean cell haemoglobin and mean cell haemoglobin concentration) did not differ between the groups. However, the haemoglobin concentration was progressively lower between patients with well-controlled hypertension and uncontrolled hypertension (P = 0.007). Haematological parameters did not correlate to echocardiographic indices of left ventricular size and function. 4. Normocytic anaemia was highly prevalent in hypertensive patients. Poor blood pressure control was associated with lower haemoglobin concentration. This may indicate a higher cardiovascular risk in uncontrolled hypertension, as in other pro-atherosclerotic conditions. Additional studies are needed to evaluate the effect of anaemia on morbidity and mortality in hypertensive patients.
The performance of the supervised learning algorithms such as k-nearest neighbor (k-NN) depends on the labeled data. For some applications (Target Domain), obtaining such labeled data is very expensive and labor-intensive. In a real-world scenario, the possibility of some other related application (Source Domain) is always accompanied by sufficiently labeled data. However, there is a distribution discrepancy between the source domain and the target domain application data as the background of collecting both the domains data is different. Therefore, source domain application with sufficient labeled data cannot be directly utilized for training the target domain classifier. Domain Adaptation (DA) or Transfer learning (TL) provides a way to transfer knowledge from source domain application to target domain application. Existing DA methods may not perform well when there is a much discrepancy between the source and the target domain data, and the data is non-linear separable. Therefore, in this paper, we provide a Kernelized Unified Framework for Domain Adaptation (KUFDA) that minimizes the discrepancy between both the domains on linear or non-linear data-sets and aligns them both geometrically and statistically. The substantial experiments verify that the proposed framework outperforms state-of-the-art Domain Adaptation and the primitive methods (Non-Domain Adaptation) on real-world Office-Caltech and PIE Face data-sets. Our proposed approach (KUFDA) achieved mean accuracies of 86.83% and 74.42% for all possible tasks of Office-Caltech with VGG-Net features and PIE Face data-sets.
Background: septic arthritis caused by Pseudomonas aeruginosa is uncommon in the immunocompetent older population, despite its occurrence in younger patients with open injuries and in intravenous drug abusers. Case Report: here we report a case of septic arthritis caused by P. aeruginosa complicated by death in an older patient with recently treated Pseudomonas urinary tract infection. Discussion: the diagnosis of Pseudomonas septic arthritis is made on culturing the organism from synovial fluid aspirate. Concurrent septic arthritis and crystal arthropathy is associated with a high mortality.
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