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Background and objectives:Diarrhea is a common complication of enteral nutrition (EN), which affects recovery and prolongs the length of hospital stay (LOHS). To investigate the effect of fiber and probiotics in reducing diarrhea associated with EN in postoperative patients with gastric cancer (GC), the authors designed this prospective randomized-controlled trial.Methods and study design:This study included 120 patients with GC, and the patients were classified into 3 groups via random picking of envelopes: fiber-free nutrition formula (FF group, n = 40), fiber-enriched nutrition formula (FE group, n = 40), and fiber- and probiotic-enriched nutrition formula (FEP group, n = 40). All patients were given EN formulas for 7 consecutive days after surgery.Results:The number of diarrhea cases was higher in the FF group than in the FE group (P = .007). The FEP group had a lower number of diarrhea cases compared with the FE group (P = .003). Patients in the FE group had a significantly shorter first flatus time than the FF group (P = .002). However, no significant difference was observed between the FE group and FEP group (P = .30). Intestinal disorders were similar between the FE group and FF group (P = .38). The FEP group had a lower number of intestinal disorder cases than the FF group (P = .03). LOHS in the FE and FEP groups was shorter than that in the FF group (P = .004; P < .001). However, no significant difference was observed between the FE and FEP groups (P = .28). In addition, no significant difference was observed between the 3 groups in terms of total lymphocyte count, albumin, prealbumin, and transferrin levels on day 7 of enteral feeding.Conclusions:The combination of fiber and probiotics was significantly effective in treating diarrhea that is associated with EN in postoperative patients with GC.

Background The role of resistant starch (RS) in glucose, insulin, insulin resistance or sensitivity, and lipid parameters have been reported in several studies and remained controversial. A pooled analysis which assessed these parameters has not been performed. Thus, we conducted a meta-analysis to sum up existing evidence about the issue. Methods We searched in MEDLINE and PUBMED for studies that were published before November 2018. Meta-analysis of diabetics and nondiabetics trials were performed by use of a random-effects model. Results A total of 13 case–control studies that included 428 subjects with body mass index ≥25 were identified. RS supplementation reduced fasting insulin in overall and stratified (diabetics and nondiabetics trials) analysis (SMD = –0.72; 95% CI: –1.13 to –0.31; SMD = –1.26; 95% CI: –1.66 to –0.86 and SMD = –0.64; 95% CI: –1.10 to –0.18, respectively), and reduced fasting glucose in overall and stratified analysis for diabetic trials (SMD = –0.26; 95% CI: –0.5 to –0.02 and SMD = –0.28; 95% CI: –0.54 to –0.01, respectively). RS supplementation increased HOMA-S% (SMD = 1.19; 95% CI: 0.59–1.78) and reduced HOMA-B (SMD =–1.2; 95% CI: –1.64 to –0.77), LDL-c concentration (SMD =–0.35; 95% CI: –0.61 to −0.09), and HbA1c (SMD = –0.43; 95% CI: –0.74 to –0.13) in overall analysis. Conclusions This meta-analysis has provided evidence that RS supplementation can improve fasting glucose, fasting insulin, insulin resistance and sensitivity, especially for diabetic with overweight or obesity. However, owing to potential sophistication, individual difference and composition of intestinal microbiota, this result should be carefully taken into account.

BackgroundMost resting energy expenditure (REE) predictive equations for adults were derived from research conducted in western populations; whether they can also be used in Chinese young people is still unclear. Therefore, we conducted this study to determine the best REE predictive equation in Chinese normal weight young adults.MethodsForty-three (21 male, 22 female) healthy college students between the age of 18 and 25 years were recruited. REE was measured by the indirect calorimetry (IC) method. Harris-Benedict, World Health Organization (WHO), Owen, Mifflin and Liu’s equations were used to predictREE (REEe). REEe that was within 10% of measured REE (REEm) was defined as accurate. Student’s t test, Wilcoxon Signed Ranks Test, McNemar Test and the Bland-Altman method were used for data analysis.ResultsREEm was significantly lower (P < 0.05 or P < 0.01) than REEe from equations, except for Liu’s, Liu’s-s, Owen, Owen-s and Mifflin in men and Liu’s and Owen in women. REEe calculated by ideal body weight was significantly higher than REEe calculated by current body weight ( P < 0.01), the only exception being Harris-Benedict equation in men. Bland-Altman analysis showed that the Owen equation with current body weight generated the least bias. The biases of REEe from Owen with ideal body weight and Mifflin with both current and ideal weights were also lower.ConclusionsLiu’s, Owen, and Mifflin equations are appropriate for the prediction of REE in young Chinese adults. However, the use of ideal body weight did not increase the accuracy of REEe.

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