Although sessional losses of protein and UN were greater with HD, weekly losses were similar between modalities. We found no differences between HD and HDF. However, total nitrogen losses were much greater than the combination of protein and UN, suggesting greater nutritional losses with dialysis than previously reported.
Objective Kidney dialysis patients treated by peritoneal dialysis (PD) are at increased risk of muscle wasting and clinical guidelines recommend assessing dietary intake, by calculating protein equivalent of nitrogen appearance (PNA) to assure protein sufficiency. The PNA equations were developed many years ago, and we wished to re-evaluate them by comparing estimated and measured peritoneal nitrogen losses. Design Cross sectional observational cohort study Setting Outpatient peritoneal dialysis centre of a University Hospital Subjects 67 peritoneal dialysis patients, 61.2% male, median age 67.3 (53.2-79.4) years Intervention Measurements of the nitrogen content of 24 hour spent peritoneal dialysate, by automated chemiluminescence analyser compared to estimates of nitrogen losses based on dialysate urea loss using the Bergström, Randerson and Blumenkrantz equations. *Manuscript (without author identifiers) Click here to view linked References Results Measured total dialysate nitrogen was more than urea nitrogen equivalent, 5.79±4.07 vs 2.66±1.67 g/day (p<0.001). Each equation has an inflation factor to compensate for non-urea protein losses, however measured nitrogen loss was 27.7 (15.5-59.6) vs Bergström 16.5 (9.8-27.1), Randerson 16.4 (9.8-27.3) and Blumenkrantz 12.9 (7.9-25.4) g/day, p<0.001. Bland Altman analysis demonstrated systematic bias with increasing underestimation by these equations with increasing measured nitrogen losses (r=0.74, p<0.001). Conclusion Our findings demonstrate that at higher protein losses, the currently used predictive equations underestimate the amount lost. It is important to attempt to compensate iatrogenic protein loss by recommending the appropriate intake of dietary protein to patients, in an attempt to minimise muscle wasting. This discrepancy may have arisen because of the characteristics of newer PD prescriptions and change in patient demographics. We propose a new equation PNA g/day = 0.31 x (urea loss mmol) + 7.17, which will require prospective validation in additional studies.
Here, we tested the hypothesis that sucralose differentially affects metabolic responses to labeled oral glucose tolerance tests (OGTTs) in participants with normal weight and obesity. Participants (10 with normal weight and 11 with obesity) without diabetes underwent three dual-tracer OGTTs preceded, in a randomized order, by consuming sucralose or water, or by tasting and expectorating sucralose (e.g., sham-fed; sweetness control). Indices of β-cell function and insulin sensitivity (S I ) were estimated using oral minimal models of glucose, insulin, and C-peptide kinetics. Compared with water, sucralose ingested (but not sham-fed) resulted in a 30 ± 10% increased glucose area under the curve in both weight groups. In contrast, the insulin response to sucralose ingestion differed depending on the presence of obesity: decreased within 20-40 min of the OGTT in normal-weight participants but increased within 90-120 min in participants with obesity. Sham-fed sucralose similarly decreased insulin concentrations within 60 min of the OGTT in both weight groups. Sucralose ingested (but not sham-fed) increased S I in normal-weight participants by 52 ± 20% but did not affect S I in participants with obesity. Sucralose did not affect glucose rates of appearance or β-cell function in either weight group. Our data underscore a physiological role for taste perception in postprandial glucose responses, suggesting sweeteners should be consumed in moderation.
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