RESUMEN
Cardiac amyloidosis is an important clinical entity associated with significant morbidity and mortality. Although the signs and symptoms can be apparent early in the disease course, diagnoses are often made late because of inadequate recognition. A diagnosis of cardiac amyloidosis requires careful scrutiny of a patient's symptoms, an electrocardiogram, and imaging studies, including echocardiography and magnetic resonance imaging. Further evaluation is required through the measurement of serum and urine light chains and the use of bone scintigraphy imaging to differentiate transthyretin amyloidosis from light-chain cardiac amyloidosis. The available treatments have expanded tremendously in recent years and have improved outcomes in the population with this disorder. Thus, it has become increasingly important to diagnose cardiac amyloidosis and provide timely therapies. This article will clarify the various misconceptions about cardiac amyloidosis and provide a framework for primary care providers to better identify this disease in their practice.
Asunto(s)
Amiloidosis/diagnóstico , Cardiomiopatías/diagnóstico , Neuropatías Amiloides Familiares/diagnóstico , Neuropatías Amiloides Familiares/epidemiología , Neuropatías Amiloides Familiares/fisiopatología , Neuropatías Amiloides Familiares/terapia , Amiloidosis/epidemiología , Amiloidosis/fisiopatología , Amiloidosis/terapia , Compuestos de Anilina , Circulación Asistida , Fibrilación Atrial/fisiopatología , Fibrilación Atrial/terapia , Técnicas de Imagen Cardíaca , Cardiomiopatías/epidemiología , Cardiomiopatías/fisiopatología , Cardiomiopatías/terapia , Diagnóstico Diferencial , Ecocardiografía , Electrocardiografía , Glicoles de Etileno , Humanos , Amiloidosis de Cadenas Ligeras de las Inmunoglobulinas/diagnóstico , Amiloidosis de Cadenas Ligeras de las Inmunoglobulinas/epidemiología , Amiloidosis de Cadenas Ligeras de las Inmunoglobulinas/fisiopatología , Amiloidosis de Cadenas Ligeras de las Inmunoglobulinas/terapia , Imagen por Resonancia Magnética , Tomografía de Emisión de Positrones , Radiofármacos , EstilbenosRESUMEN
BACKGROUND AND PURPOSE: Perioperative stroke is a significant complication of transcatheter aortic valve implantation (TAVI). This study aimed to quantify perioperative stroke as an independent risk factor for in-hospital mortality and postoperative morbidity in patients receiving TAVI. METHODS: A retrospective cohort study was conducted using the National Inpatient Sample. Patients undergoing TAVI during 2012 and 2013 were identified using diagnostic codes of International Classification of Diseases, ninth revision. Univariate and multivariate analyses were performed using patient demographics and comorbidities to identify predictors of mortality and morbidity, defined by a length of stay of >14 days and/or discharge to a place other than home. RESULTS: Data were obtained from 7,556 patients undergoing TAVI during 2012 and 2013. The incidence rates of mortality and morbidity were 4.57 and 71.12%, respectively. Perioperative stroke was an independent risk factor for mortality [odds ratio (OR)=3.182, 95% confidence interval (CI)=1.530-6.618, p=0.002], as were infection (OR=17.899, 95% CI=9.876-32.440, p<0.001) and pericardial tamponade (OR=7.272, 95% CI=2.874-18.402, p<0.001). Stroke also predicted morbidity (OR=5.223, 95% CI=2.005-13.608, p=0.001), which was also associated with age, being female, being Asian, moderate and high Van Walraven scores (VWR), and infection. CONCLUSIONS: In conclusion, perioperative stroke was found to be independently associated with in-hospital mortality and postoperative morbidity, as are age and high VWR. Our findings support the use of further preoperative, intraoperative, and postoperative management strategies during TAVI.
RESUMEN
Despite the considerable progress in understanding the biology of human cancer and technological advancement in drug discovery, treatment failure remains an inevitable outcome for most cancer patients with advanced diseases, including melanoma. Despite FDA-approved BRAF-targeted therapies for advanced stage melanoma showed a great deal of promise, development of rapid resistance limits the success. Hence, the overall success rate of melanoma therapy still remains to be one of the worst compared to other malignancies. Advancement of next-generation sequencing technology allowed better identification of alterations that trigger melanoma development. As development of successful therapies strongly depends on clinically relevant preclinical models, together with the new findings, more advanced melanoma models have been generated. In this article, besides traditional mouse models of melanoma, we will discuss recent ones, such as patient-derived tumor xenografts, topically inducible BRAF mouse model and RCAS/TVA-based model, and their advantages as well as limitations. Although mouse models of melanoma are often criticized as poor predictors of whether an experimental drug would be an effective treatment, development of new and more relevant models could circumvent this problem in the near future.