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All Journal Bioscientia Medicina : Journal of Biomedicine and Translational Research
Rizki Bastari
Faculty of Medicine, Universitas Sriwijaya/Dr. Mohammad Hoesin General Hospital, Palembang, Indonesia
Biochemistry, Genetics & Molecular Biology Immunology & microbiology Medicine & Pharmacology Neuroscience

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The Role of Rituximab in the Management of Heart Failure Rizki Bastari; Taufiq Indrajaya; Syamsu Indra
Bioscientia Medicina : Journal of Biomedicine and Translational Research Vol. 8 No. 7 (2024): Bioscientia Medicina: Journal of Biomedicine & Translational Research
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/bsm.v8i7.1027

Abstract

Rituximab is a chimeric monoclonal antibody mice/humans that bind the transmembrane antigen, CD20 specifically. The mechanism of heart failure is mediated by neurohormonal pathways: the renin-angiotensin-aldosterone system (RAAS), the sympathetic nervous system, and the natriuretic peptide system, thereby triggering activation of the immune system. This literature review will discuss the role of B cell targeted therapy, in this case rituximab in the management of heart failure. Modulation of the immune response holds great promise in the 30% of cases of myocarditis where inflammation does not resolve and progression to chronic inflammatory dilated cardiomyopathy occurs. Pharmacologically, rituximab is a monoclonal immunoglobulin G1 antibody drug that is given intravenously. Rituximab targets the CD20 antigen expressed on the surface of mature B lymphocytes, including memory B cells but not on stem cells or plasma cells. In conclusion, rituximab causes a selective and temporary decrease in the CD20+ B cell subpopulation and represents a more specific and targeted approach to B cell-induced disorders including heart failure.
Accuracy of Fat Mass and Muscle Mass Measured by Bioelectrical Impedance Analysis in Predicting Osteoporosis in Older Adults Nur Riviati; Ari Dwi Prasetyo; Rizki Bastari; Surya Darma; Erial Bahar
Bioscientia Medicina : Journal of Biomedicine and Translational Research Vol. 9 No. 2 (2025): Bioscientia Medicina: Journal of Biomedicine & Translational Research
Publisher : HM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37275/bsm.v9i2.1191

Abstract

Background: Osteoporosis is a prevalent bone disease characterized by reduced bone mineral density (BMD) and increased fracture risk. This study aimed to evaluate the accuracy of fat mass (FM) and muscle mass measured by bioelectrical impedance analysis (BIA) in predicting osteoporosis in older adults. Methods: A cross-sectional study was conducted on 109 outpatients aged 60 years and older. FM parameters (total fat mass, visceral fat level, and fat mass index [FMI]) and muscle mass parameters (total muscle mass, appendicular skeletal muscle mass [ASM], and appendicular skeletal muscle mass index [ASMI]) were measured using BIA. Osteoporosis was diagnosed based on BMD measurements using dual-energy X-ray absorptiometry (DXA). Receiver operating characteristic (ROC) curves were used to determine cut-off points and assess the accuracy of BIA parameters in predicting osteoporosis. Results: The prevalence of osteoporosis was 52.3% (n=57). The optimal cut-off points for predicting osteoporosis were: total fat mass >36.25%, visceral fat level >12.05, FMI >7.82 kg/m2, total muscle mass <37.82 kg, ASM <16.795 kg, and ASMI <6.895 kg/m2. Among the FM parameters, visceral fat level had the highest accuracy (AUC = 60.9%, sensitivity = 64.9%, specificity = 78.8%) while FMI had the lowest (AUC = 53.5%, sensitivity = 56.1%, specificity = 57.7%). For muscle mass parameters, ASM showed the highest accuracy (AUC = 74.0%, sensitivity = 70.2%, specificity = 76.9%). Conclusion: BIA-derived FM and muscle mass parameters, particularly visceral fat level and ASM can be used to predict osteoporosis in older adults with good accuracy. This non-invasive and accessible method may be useful as a screening tool for osteoporosis, especially in settings where DXA is unavailable.
Co-Authors Ari Dwi Prasetyo Erial Bahar Nur Riviati, Nur Surya Darma Syamsu Indra Taufiq Indrajaya