# Beyond the Malnutrition Screening Tool: Assessing Hand Grip Strength and Gastrointestinal Symptoms for Malnutrition Prediction in Outpatients with Chronic Kidney Disease Not on Kidney Replacement Therapy

## TL;DR

This study evaluates new ways to detect malnutrition in outpatients with advanced kidney disease, finding that combining hand grip strength and a screening tool improves sensitivity.

## Contribution

The study introduces a combined approach using hand grip strength and MST for improved malnutrition detection in CKD outpatients.

## Key findings

- Combining hand grip strength ≤ 29.5 kg or MST ≥ 2 achieved high sensitivity (95.5%) for detecting malnutrition.
- MST alone and other tested tools showed limited accuracy with AUC ranging from 0.604 to 0.710.
- The combined tool had a high negative predictive value (93.3%) but low specificity (33.3%).

## Abstract

Background: The Malnutrition Screening Tool (MST) is commonly used to identify malnutrition risk; however it has demonstrated poor sensitivity to detect malnutrition in inpatients with chronic kidney disease (CKD) and kidney replacement therapy (KRT) populations. Gastrointestinal symptoms, such as poor appetite, may better detect malnutrition. The accuracy of MST or other nutrition-related parameters to detect malnutrition in ambulatory patients with CKD stages 4–5 without KRT has not been evaluated. Methods: A single site retrospective audit of outpatient records from May 2020 to March 2025 was conducted. Patients with eGFR < 25 mL/min/1.73 m2 without KRT who had both MST and a 7-point Subjective Global Assessment (SGA) within 7 days were included. Sensitivity, specificity, and ROC-AUC analyses compared nutritional parameters against SGA-defined malnutrition. Nutritional parameters tested included MST, hand grip strength, upper gastrointestinal symptom burden, poor appetite and a combination of some of these parameters. Results: Among 231 patients (68.8% male, median age 69 years, median eGFR 15), 29.9% were at risk of malnutrition (MST ≥ 2) and 33.8% malnourished (SGA ≤ 5). All potential screening tools had AUC ranging from 0.604 to 0.710, implying a poor-to-moderate discriminator ability to detect malnutrition. Combining HGS ≤ 29.5 kg or MST ≥2 demonstrated high sensitivity (95.5%) and negative predictive value (93.3%), but low specificity (33.3%) for detecting malnutrition, indicating this approach is effective for ruling out malnutrition but may over-identify at-risk individuals. Conclusions: MST and other tested tools showed limited overall accuracy to identify malnutrition. Using combined nutritional markers of HGS or MST score was the most sensitive tool for detecting malnutrition in this advanced CKD without KRT population.