Publications by authors named "V Billa"

Kidney exchange programs (KEPs) aim to find compatible kidneys for recipients with incompatible donors. Patients without a living donor depend upon deceased donor (DD) donations to get a kidney transplant. In India, a ©DD donates kidneys directly to a©DD wait-list.

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Context: Glycemic variability plays a major role in the development as well as the progression of cardiovascular disease in diabetes.

Aims: We compared the mean plasma glucose and glycemic variability (GV) parameters on and off hemodialysis (HD) in patients with End-Stage Diabetic Nephropathy (ESDN) and End-Stage Renal Disease (ESRD).

Settings And Design: Cross-sectional study.

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Introduction: The coronavirus disease 2019 (COVID-19) pandemic has caused significant global disruption, especially for chronic care like hemodialysis treatments. Approximately 10,000 end-stage kidney disease (ESKD) patients are receiving maintenance hemodialysis (MHD) at 174 dialysis centers in Greater Mumbai. Because of the fear of transmission of infection and inability to isolate patients in dialysis centers, chronic hemodialysis care was disrupted for COVID-19-infected patients.

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Article Synopsis
  • This study examines the prevalence of asymptomatic COVID-19 infections in hemodialysis patients and staff, as previous research primarily focused on symptomatic cases.
  • All 705 patients and 103 staff across nine hemodialysis centers were tested for COVID-19, revealing a 7.1% infection rate in patients and 14.6% in staff.
  • The findings suggest that a significant number of infections were asymptomatic, with high rates of antibody development even among those who did not show symptoms, indicating silent transmission within hemodialysis centers.*
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Genome-scale metabolic models (GEMs) are valuable tools to study metabolism and provide a scaffold for the integrative analysis of omics data. Researchers have developed increasingly comprehensive human GEMs, but the disconnect among different model sources and versions impedes further progress. We therefore integrated and extensively curated the most recent human metabolic models to construct a consensus GEM, Human1.

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