SUN-P127: Nutritional Status of Hospitalized Patients and its Effect on Quality of Life

SUN-P127: Nutritional Status of Hospitalized Patients and its Effect on Quality of Life

Nutritional assessment 1 SUN-P127 NUTRITIONAL STATUS OF HOSPITALIZED PATIENTS AND ITS EFFECT ON QUALITY OF LIFE A. E. Gungor1, I. Alparslan2, B. Çakır...

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Nutritional assessment 1 SUN-P127 NUTRITIONAL STATUS OF HOSPITALIZED PATIENTS AND ITS EFFECT ON QUALITY OF LIFE A. E. Gungor1, I. Alparslan2, B. Çakır3, F. N. Kılınç3, E. Energin4, Y. Yavuz5, B. Akman6, S. Demirer7. 1Nutrition and Dietetics, European University of Lefke, Lefke, Cyprus, 2Nutrition Support Team, Ankara University Ibn-i Sina Hospital, Ankara, 3 Nutrition and Dietetics, Kırıkkale University Faculty of Health Sciences, Kırıkkale, 4Nutrition and Dietetics, Ankara University Faculty of Health Sciences, 5Department of Biostatistics, Ankara University School of Medicine, 6 Department of Nephrology, Guven Hospital, 7Department of General Surgery, Ankara University School of Medicine, Ankara, Turkey Rationale: To examine the nutritional status on hospital admission and its effect on quality of life in different patient profiles. Methods: The study comprised 1,069 adult patients (510 F, 559 M, mean age 46.5 ± 12.8 years). There were 452 medical and 617 surgical patients. Weight, height and hand grip strength of patients were recorded on admission. Nutritional Risk Screening 2002 (NRS 2002) was used and Health-related quality of life (SF 36) was administered to each patient by a dietitian. The patients were grouped according to medical diagnosis and length of hospital stay was recorded. Results: Mean BMI was 27.8 ± 6.3. NRS 2002 revealed nutritional risk in 19.1% of all patients. Nutritional risk was higher in males (22.5%) than females (15.3%). Cancer patients (n = 234) had higher NRS 2002 scores (47%) than other (n = 835) patient groups (11.3%). NRS 2002 ≥ 3 score patients had 6 days longer hospitalization than NRS 2002 < 3 patients ( p < 0.001). There was no statistically significant difference between hand grip strength and NRS 2002 scores ( p > 0.05). However, there was a significant relationship between hand grip strength and SF 36 subgroups ( p < 0.001, for all). NRS 2002 ≥ 3 patients had lower health related quality of life scores ( p < 0.001). SF 36 subgroup scores were significantly low in all type of diseases ( p < 0.001). Conclusion: Assessment of nutritional risk on hospital admission is valuable for providing further nutritional support during hospitalization as it may have positive effects on quality of life and shorten hospital stay. Disclosure of Interest: None declared

SUN-P128 SKELETAL MUSCLE ANALYSES: AGREEMENT BETWEEN NON-CONTRASTAND CONTRAST CT SCAN MEASUREMENTS OF SKELETAL MUSCLE AREA AND MEAN MUSCLE ATTENUATION A. Van Der Werf1, I. Dekker1, N. Wierdsma1, M. de van der Schueren1, J. Langius1. 1Nutrition and Dietetics, VUmc, Amsterdam, Netherlands Rationale: Low skeletal muscle area (SMA) and mean muscle attenuation (MMA) are associated with poor prognosis in various populations. To determine SMA and MMA, both non-contrast and contrast CT scans are used. However, the effect of a contrast agent on SMA and MMA is unknown. Therefore, we investigated agreement between these scan options. Methods: SMA and MMA of 41 healthy subjects were analyzed on a paired non-contrast and contrast single L3 CT slice, which were selected on the basis of similarity by 2 researchers

S91 independently. Agreement between results of both scans was assessed with intraclass correlation coefficients (ICC), standard error of measurements (SEM) and smallest detectable differences at a 95% confidence level (SDD95). Analyses were stratified by tube voltage. Results: Difference in SMA between non-contrast and contrast scans was 7.0 ± 7.5 cm2 for scans made with a different tube voltage and 2.3 ± 1.7 cm2 for scans made with the same tube voltage, with higher values for contrast scans. MMA of scans made with a different tube voltage differed 1.3 ± 11.3 HU and for scans made with the same tube voltage, the difference was 6.7 ± 3.2 cm2. ICC, SEM and SDD95 are shown in table 1. Table 1: SMA and MMA measured on paired non-contrast and contrast single CT slices SMA ICC Different tube voltage (n = 20) Same tube voltage (n = 21)

0.952 0.997

MMA SEM

SDD95

7.2 cm

2

19.9 cm

2.0 cm

2

2

5.6 cm

2

ICC

SEM

SDD95

0.207

7.9HU

21.8HU

0.682

5.3HU

14.6HU

Different tube voltage: non-contrast 100 kV, contrast 120 kV. Same tube voltage: both 120 kV. HU: Hounsfield units

Conclusion: SMA and MMA can be slightly influenced by the use of contrast agent. To minimize measurement error, image acquisition (use of contrast agent, tube voltage) of the scans should be similar and be reported. When image acquisition differs, the smallest detectable difference should be taken into account. Disclosure of Interest: None declared

SUN-P129 DIAGNOSTIC ACCURACY OF PGSGA AND MUST OF PATIENTS WITH CHRONIC KIDNEY DISEASES, A PILOT M. Havinga-Kosters1, I. Julicher1, A. Duvan2, E. Yucesan2, H. Zweers-van Essen1, A. V. D. Berg1, H. V. Hamersvelt3. 1 Department of Gastroenterology and Hepatology-Dietetics, Radboudumc, 2HAN university of Applied Sciences, 3 Nephrology, Radboudumc, Nijmegen, Netherlands Rationale: The National registration of the quality indicator for “Risk of Malnutrition” describes only a few patients with Chronic Kidney Diseases (CKD), while the prevalence of Malnutrition and Protein Energy Wasting (PEW) in patients with CKD is between 18% and 75%. We suspect that not all malnourished patients with CKD are recognized by the Malnutrition Universal Screening Tool (MUST), therefore we explore the sensitivity and specificity of the MUSTand PGSGA in patients with CKD. Methods: In this cross sectional study, we collected data on malnutrition using different screening tools in outpatients with CKD. All patients were screened by the MUST, the Patient Generated Subjective Global Assessment (PGSGA) in total and the Short Form (SF) and handgrip strength (HGS) was measured. We used the PEW criteria of the International Society of Renal Nutritional and Metabolism (ISRNM) as golden standard for malnutrition (n = 22). Criteria are classified in 4 categories: serum chemistry (serum albumin), Body Mass (BMI), Muscle Mass (HGS) and Dietary Intake ( protein intake using food diaries).