Nutritional screening to determine malnutrition and cardiometabolic risk in haemodialysis.

Comparison between direct and indirect methods to diagnosis of malnutrition and cardiometabolic risk in haemodialysis patients

Balbino et al., JHND Early ViewUnknown.png

Background

The present study aimed to evaluate the nutritional status of patients undergoing haemodialysis (HD) by comparing nutritional risk scores with biochemical, anthropometric and body composition variables.

Methods

Eighty-five individuals [65.9% male, mean (SD) age 62 (14) years] participated in a cross-sectional study. Global Objective Assessment (GOA) and Modified Global Subjective Assessment (mGSA) scores, as well as biochemical, anthropometric and body composition data, were collected using standardised procedures.

Results

The prevalence of malnutrition ranged from 20.0% (% body fat by electrical bioimpedance) to 95.3% (by GOA), depending on the indicator or score used. According to the waist circumference, 61.2% of the individuals presented abdominal obesity and visceral adipose tissue was excessive in 20% of them. Malnutrition diagnosis by GOA showed the relationship between the anthropometric and body composition indicators, as assessed by the extent that the ratings of risk nutritional/mild malnutrition and mainly moderate malnutrition were accompanied by a significant decrease in nutritional status and body composition variables. However, with respect to categories of mGSA, no statistically significant differences were observed for nutritional status and body composition variables. In the receiver operator characteristic curve analyses, mGSA and GOA were good indicators for diagnosing malnutrition because both achieved an AUC > 0.5.

Conclusions

mGSA and GOA were more sensitive with respect to identifying individuals at nutritional risk compared to the isolated anthropometric indicators, thus indicating their utility in diagnostic malnutrition. However, individuals at high nutritional risk also presented cardiometabolic risk, as diagnosed mainly by central fat indicators, suggesting the application of both malnutrition and cardiometabolic risk markers in HD patients.

Advertisements

Leave a Reply

Please log in using one of these methods to post your comment:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s