Circulating fatty acid profiles are associated with protein energy wasting in maintenance hemodialysis patients: a cross-sectional study

An updated clinical prediction model of protein-energy wasting for hemodialysis patients

Background and aim

Protein-energy wasting (PEW) is critically associated with the reduced quality of life and poor prognosis of hemodialysis patients. However, the diagnosis criteria of PEW are complex, characterized by difficulty in estimating dietary intake and assessing muscle mass loss objectively. We performed a cross-sectional study in hemodialysis patients to propose a novel PEW prediction model.

Materials and methods

A total of 380 patients who underwent maintenance hemodialysis were enrolled in this cross-sectional study. The data were analyzed with univariate and multivariable logistic regression to identify influencing factors of PEW. The PEW prediction model was presented as a nomogram by using the results of logistic regression. Furthermore, receiver operating characteristic (ROC) and decision curve analysis (DCA) were used to test the prediction and discrimination ability of the novel model.

Results

Binary logistic regression was used to identify four independent influencing factors, namely, sex (P = 0.03), triglycerides (P = 0.009), vitamin D (P = 0.029), and NT-proBNP (P = 0.029). The nomogram was applied to display the value of each influencing factor contributed to PEW. Then, we built a novel prediction model of PEW (model 3) by combining these four independent variables with part of the International Society of Renal Nutrition and Metabolism (ISRNM) diagnostic criteria including albumin, total cholesterol, and BMI, while the ISRNM diagnostic criteria served as model 1 and model 2. ROC analysis of model 3 showed that the area under the curve was 0.851 (95%CI: 0.799-0.904), and there was no significant difference between model 3 and model 1 or model 2 (all P > 0.05). DCA revealed that the novel prediction model resulted in clinical net benefit as well as the other two models.

Conclusion

In this research, we proposed a novel PEW prediction model, which could effectively identify PEW in hemodialysis patients and was more convenient and objective than traditional diagnostic criteria.

Benchmarking Diet Quality to Assess Nutritional Risk in Hemodialysis Patients: Applying Adequacy and Moderation Metrics of the Hemodialysis-Healthy Eating Index

OBJECTIVES

This study modified Healthy Eating Index (HEI) based on hemodialysis (HD) specific guidelines and investigated associations between the diet quality (DQ) and nutritional risk in HD patients.

METHODS

The HD-HEI tool adapted the XXX Dietary Guidelines 2010 framework according to HD-specific nutrition guidelines. This HD-HEI was applied to 3-day dietary records of 382 HD patients. Relationships between HD-HEI scores and nutritional parameters were tested by partial correlations. Binary logistic regression models adjusted with confounders were used to determine adjusted odds ratio (_adjOR) with 95% confidence interval (CI) for nutritional risk based on HD-HEI scores categorization.

RESULTS

The total HD-HEI score (51.3 ± 10.2) for this study population was affected by ethnicity (P_trend<0.001) and sex (P=0.003). No patient achieved "good" DQ (score: 81-100), while DQ of 54.5% patients were classified as "needs improvement" (score: 51-80) and remaining as "poor" (score: 0-51). Total HD-HEI scores were positively associated with dietary energy intake (DEI) and dietary protein intakes (DPI), dry weight and handgrip strength, but inversely associated with Dietary Monotony Index (DMI) (all P<0.05). Individually, scores for refined grain, total protein, and animal protein were positively associated with DEI (all P< 0.05), whilst total, animal, fish and vegetable proteins indicated positive associations with DPI (all P< 0.05). Moderating metrics for convenience meals, saturated fats, sodium, and fluid negatively correlated towards DEI with similar trends for DPI excepting convenience meals and fluids. "Poor" DQ was associated with DMI ≥ 29.2 (_adjOR: 18.83, 95% CI: 9.36-37.86, P<0.001), Malnutrition Inflammation Score (MIS) ≥ 5 (_adjOR: 1.78, 95% CI: 1.01-3.15, P=0.045), and Protein Energy Wasting (PEW) (_adjOR: 1.96, 95% CI: 1.14-3.34, P=0.031), but became nullified with covariate adjustments. "Poor" DQ was also associated with low lean tissue mass (< 32.6 kg) in men (_adjOR: 2.38, 95% CI: 1.01-5.58, P=0.046) but not women.

CONCLUSIONS

"Poor" DQ was associated with poor nutritional status in XXX HD patients, who should be targeted for nutritional counselling.