Exploring The Concordance Of Malnutrition Assessment Tools With

The GLIM Criteria Among Hemodialysis Patients

Mirey Karavetian1, Nada Salhab2, Rana Rizk3,4, Kalliopi-Anna Poulia5

1Zayed University, Dubai, United Arab Emirates; 2Maastricht University, Maastricht, Netherlands 3Institut National de Santé Publique, d’Épidémiologie Clinique et de Toxicologie, The Lebanese University, Fanar, Lebanon 4Maastricht University, The Netherlands; 5Laiko General Hospital, Athens, Greece

Introduction

• Malnutrition in hemodialysis (HD) is a well-described condition, often co-existing with inflammation

• It affects 50 to 75% of HD, depending on the diagnostic tool used.

Ta Ikizler et al, Kidney International 2013

Etiology and consequences of PEW in CKD

MIS

ESPEN – GUIDELINES:Bioelectrical impedance analysis: Review of principles & methods. Clin Nutr 2004; 23: 1226-1243

Utilisation in clinical practice. Clin Nutr 2004; 23: 1430-1453

Bioelectrical Impedance Analysis

5

Correlated with

• Nutritional status

• Muscle mass

• Disease severity

Phase angle

g PhA

Reference values

Bioelectrical vector analysis, BIVA

Aim of the study

• Explore the prevalence of malnutrition using the malnutrition inflammation score (MIS) and Phase Angle (PhA)

• Compare their concordance with the new Global Initiative on Malnutrition (GLIM) criteria for the diagnosis of malnutrition.

Fig. 1

Clinical Nutrition DOI: (10.1016/j.clnu.2018.08.002)

Methods • Design and sample

– Cross sectional study

– Randomly recruited HD unit in United Arab Emirates

• Outcome variables

– MIS, malnourished >10

– Malnutrition assessment based on GLIM criteria

• FFMI for men <17kg/m2 , <15kg/m2

– Phase angle (PhA), derived from BIA analysis

• Statistical analysis

– Independent – test and Mann-Whitney U non parametric test, SPSS 21

– Receiver Operating Characteristic (ROC curves), Medcalc software

Results (1) N = 70 (100%)

Gender: Male 43 (61.4%)

Co morbidities

Diabetes

Hypertension

Cardiovascular Diseases

Others

46 (65.71%)

62 (88.57%)

28 (40.00%)

37 (52.86%)

Dialysis Vintage

< 1 year

1-4 years

> 4 years

5 (7.14%)

35 (50.00%)

30 (42.86%)

Results (2) Variable (N=70)

Mean (SD)

Age (years) 54.61 (12.79)

BMI (Kg/m2) 27.22 (6.48)

PhA ()¶ Phase Angle 4.66 (1.21)

MIS Malnutrition Inflammation Score 9.40 (3.07)

FMI (Kg/m2)Fat Mass Index 10.15 (5.00)

SMM Skeletal Muscle Mass(Kg) 19.67 (6.44)

Fat (Kg) 26.70 (12.57)

Median (IQR)

FFMI (Kg/m2)Fat Free Mass Index 17.09 (3.33)

FFM (Kg)Free Fat Mass 42.92 (15.14)

TBW (L)Total Body Water 32.15 (11.4)

ECW (L)Extracellular Water 15.20 (4.7)

Results (3) Prevalence of Malnutrition

Value N (% of pts)

GLIM criteria

•Stage 1, moderate

•Stage 2, severe

38 (54.29)

12 (31.58)

26 (68.62)

MIS (>10) 34 (48.57)

Concordance of GLIM with MIS (>10) and PhA (5.7o)

Criterion MIS>10 PhA5.7o

Sensitivity (%) 39.47 86.84

Specificity (%) 71.87 35.48

K value (p) 0.202

(0.089)

0.234

(0.029)

AUC 0.691 0.614

Results (4) ROC curve for PhA and MIS according to GLIM

Conclusions

• Malnutrition is highly prevalent in the HD patients studied.

• MIS performed slightly better than PhA in the diagnosis of malnutrition

when using GLIM as a reference

• Both tools may perform equally on a large sample.

• Prioritizing malnutrition screening in this population, and integrating cost-

effective, sensitive and specific tools within routine practice is essential for

this population

Thank you for your attention