Introduction: Cardiovascular mortality remains high among peritoneal dialysis (PD) patients. Several small studies have suggested that PD patients are volume expanded, and as such this could be a cardiovascular risk factor. We therefore wished to investigate factors which could lead to extracellular water (ECW) expansion.
Methods: Retrospective cross-sectional audit of 600 prevalent, adult PD patients attending two tertiary university PD centers, with corresponding assessments of PD adequacy, transport status, and multifrequency bioimpedance measurements of extracellular water to total body water (ECW/TBW).
Results: 600 PD patients, median age 57.5 (46.9-67.9) years, 54% male, 31% diabetic, 47.6% Caucasoid, median PD vintage 16 (3.7-38) months, (64% prescribed icodextrin, 34% hypertonic glucose dialysates, and 74% antihypertensive medications). Mean ECW 15.1±0.2 L, ICW 20±0.2 L, ECW/TBW ratio 0.437±0.007. On multivariate analysis %ECW/TBW was associated with age (F=13.1 ß=0.045 p=0.000), number of antihypertensive medications (F=10.3 ß=0.43 p=0.001), log CRP (F=12.9 ß=1.3 p=0.000), and negatively with serum albumin (F=25 ß=-0.22 p=0.000), and residual renal function (urine volume mL F=9.96 ß=-0.001 p=0.002) (weekly Kt/Vurine F=8.82 ß=-2.05, p=0.003).
Conclusions: Overhydration as assessed by ECW/TBW is prevalent in adult PD patients, and is associated with loss of residual renal function, inflammation, malnutrition and hypertension - as assessed by antihypertensive medications. As this was a retrospective cross-sectional audit, whether loss of residual renal function, inflammation, and protein energy wasting lead to volume expansion remains to be determined in prospective longitudinal studies.
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http://dx.doi.org/10.5301/ijao.5000080 | DOI Listing |
Diabetes Care
January 2025
Department of Epidemiology and Biostatistics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
J Am Geriatr Soc
January 2025
Department of Epidemiology and Population Health, Stanford University, Stanford, California, USA.
Background: Deprescribing antihypertensives is of growing interest in geriatric medicine, yet the impact on functional status is unknown. We emulated a target trial of deprescribing antihypertensive medications compared with continued use on functional status measured by activities of daily living (ADL) in a long-term care population.
Methods: We included 12,238 Veteran Affairs long-term care residents age 65+ who had a stay ≥ 12 weeks between 2006 and 2019.
Cureus
December 2024
Medical Strategic Affairs, Torrent Pharmaceuticals Ltd., Ahmedabad, IND.
Introduction: Elevated central aortic pressure, cardiac output and peripheral vascular resistance contribute to high morbidity in relation to end organ dysfunction in obstructive and non-obstructive coronary artery disease (NOCAD) cases despite revascularization. Bisoprolol preempts further progression of left ventricular dysfunction in such cases due to anti-ischemic and anti-hypertensive effects, further extending its evaluation in local Indian settings.
Methods: Post-hoc analyses of NOCAD patients with epicardial stenosis (N=378, 30 to 70% stenosis) from cross-sectional analyses conducted across eighty centers in India.
Sci Rep
January 2025
Department of Plastic Surgery, Jiangxi Provincial Children's Hospital, 1666 Diezihu Avenue, Nanchang, China.
The objective of this study was to evaluate the efficacy and safety of propranolol hydrochloride tablets and oral solution in neonates with severe IHs. A retrospective cohort study included 184 consecutive neonates diagnosed with severe IHs and treated with propranolol from January 2016 to June 2023. Of these, 126 patients received propranolol tablets, and 58 received propranolol oral solution.
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January 2025
School of Pharmacy, Guilin Medical University, Guilin, 541199, China.
The hypotensive side effects caused by drugs during their use have been a vexing issue. Recent studies have found that deep learning can effectively predict the biological activity of compounds by mining patterns and rules in the data, providing a potential solution for identifying drug side effects. In this study, we established a deep learning-based predictive model, utilizing a data set comprised of compounds known to either elevate or lower blood pressure.
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