[Free Immunoglobulin Light Chains in Patients With Myocarditis: a New Biomarker of Inflammation and Heart Failure].

Aim: To study the concentration of immunoglobulin free light chains (FLCs) in patients with myocarditis in comparison with non-inflammatory heart diseases, their relationship with inflammatory markers and the severity of chronic heart failure (CHF).

Material And Methods: This study included 77 patients (31 women, mean age 54.1±13.

Patient Adherence and Duration of Continuous Treatment With Various Arbs in Patients With Uncomplicated Arterial Hypertension in the USA Based on The Analysis of the Truven Health Analytics MarketScan Database.

Aim: To discuss two aspects that can be used to improve the adherence to therapy in patients with arterial hypertension (AH): 1) which of the angiotensin II receptor blockers (ARBs) provides the highest adherence rates; 2) how various factors influence adherence rates.

Material And Methods: An analysis of one of the world's largest clinical practice databases, Truven Health Analytics MarketScan (currently Merative MarketScan), was performed. The analysis included data on patients of both sexes aged 30 to 65 years who had been diagnosed with uncomplicated AH (at least once between March 1, 2012 and January 1, 2018) and prescribed monotherapy with one of ARBs.

Metabolomic biomarkers of multiple myeloma: A systematic review.

Multiple myeloma (MM) is an incurable malignancy of clonal plasma cells. Various diagnostic methods are used in parallel to accurately determine stage and severity of the disease. Identifying a biomarker or a panel of biomarkers could enhance the quality of medical care that patients receive by adopting a more personalized approach.

A novel preliminary metabolomic panel for IHD diagnostics and pathogenesis.

Cardiovascular disease (CVD) represents one of the main causes of mortality worldwide and nearly a half of it is related to ischemic heart disease (IHD). The article represents a comprehensive study on the diagnostics of IHD through the targeted metabolomic profiling and machine learning techniques. A total of 112 subjects were enrolled in the study, consisting of 76 IHD patients and 36 non-CVD subjects.