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Whether the association between decreased protein intake and raised risk for all–cause, cardiovascular death and peritonitis is confounded by inflammation status is unknown. This study aimed to explore the predicting role of daily protein intake (DPI) in above outcome events in patients with and without inflammation respectively. Our study enrolled 305 incident patients who could be followed regularly. Demographic data was collected at baseline. Biochemical, dietary and nutritional data, dialysis adequacy were measured at the baseline and thereafter at regular intervals. A total of 127 patients died during the 44.5-month follow-up. Total 129 first-episode peritonitis were observed. Patients with high tertile of baseline DPI had significantly higher serum albumin, prealbumin, hemoglobin, lean body mass and hand grip strength compared to low tertile group (P

The estimated energy expenditure is critical for prescribing an appropriate energy intake for dialysis patients. Unfortunately, it is often higher than actual energy intake from a single-point measurement. It is hypothesized that the difference might be reduced with repeated measurements. A total of 206 clinically–stable patients on peritoneal dialysis longer than 3 months were studied. Dietary protein and energy intakes were measured repeatedly and time-averaged values were calculated. Energy expenditures were estimated from Harris-Benedict, Schofield and WHO formulas. Other nutritional indices included anthropometric, biochemistry, lean body mass from DEXA and hand grip strength. The time-averaged normalized protein and energy intake were 0.86±0.14 g/kg/d, 28.24±4.40 kcal/kg/d. The estimated energy expenditures were significantly higher than actual energy intake calculated by above formulas with differences of 369.35, 433.26 and 469.99 kcal/d respectively. When patients were divided into three groups according to the tertile of differences between estimated energy expenditure from Harris–Benedict equation and actual energy intake, we did not observe any differences in serum albumin and prealbumin, lean body mass measured by DEXA, and hand grip strength between groups. Conclusions: The estimated energy expenditure from above formulas still surpassed the actual energy intake even though it was measured repeatedly in well-trained PD patients. The appropriate equations of energy expenditure should be derived from dialysis population specifically

Seasonal variation of blood pressure is a common phenomenon in dialysis patients. The potential mechanisms are not verified. Whether dietary acid load plays an importance role in seasonal variation of blood pressure is unknown. A total of 181 clinically-stable patients who had been on peritoneal dialysis(PD) more than 3 months were studied between June, 2011 and Nov, 2011, i.e summer to autumn, when seasonal variation of blood pressure represented most obviously. Blood pressure and dietary nutrients intakes were measured monthly and time-averaged values calculated for summer and autumn respectively. Dietary acid load was estimated by NEAP: NEAP (mEq/d)=54.5*protein (g/d)/potassium (mEq/d)-10.2. Other biochemistry and dialysis adequacy was examined also. With the cold season coming, systolic and diastolic blood pressure (SBP and DBP) increased, SBP129.2±16.8mmHg vs 133.9±15.6 mmHG and DBP 76.8±10.5 mmHg vs 78.7±10.1mmHg respectively. Similar trends were observed in body weight, total fluid removal via dialysate and urine, and all dietary nutrients intakes including NEAP values. However, the differences in SBP and DBP between autumn and summer were not associated with the differences in NEAP and dietary nutrients intakes. Conclusions: The increased nutrient intakes including dietary acid load could not explain the seasonal variation of blood pressure in PD patients. Other potential causes still need to be determined.