Oak Hee Yun; Gyuhwi Lee; Yoon Jung Park

doi:10.4163/jnh.2014.47.1.124

Journal List > J Nutr Health > v.47(2) > 1081330

Go to TopGo to Top Go to BottomGo to Bottom

TOOLS

Yun, Lee, and Park: Development of a simplified malnutrition screening tool for hospitalized patients and evaluation of its inter-methods reliability∗

Research Article

J Nutr Health 2014;47(2):124-133.

Published online: 20 January 2014

DOI: https://doi.org/10.4163/jnh.2014.47.1.124

Development of a simplified malnutrition screening tool for hospitalized patients and evaluation of its inter-methods reliability∗

Oak Hee Yun^1,², Gyuhwi Lee³, Yoon Jung Park³

¹Department of Clinical Health Sciences, Graduate School of Clinical Health Sciences, Ewha Womans University, Seoul 120–750, Korea

²Nutrition Team, Korea Institute of Radiological and Medical Sciences, Seoul 139–709, Korea

³Department of Nutritional Sciences & Food Management, College of Health Sciences, Ewha Womans University, Seoul 120–750, Korea

Received 2 January 2014 Revised 11 February 2014 Accepted 31 March 2014

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose

The current study was designed for development of a simplified malnutrition screening tool (SMST) for hospitalized patients using readily available laboratory and patient information and for evaluation of its reliability compared to well-established tools, such as PGSGA and NRS-2002. Methods: Anthropometric and biochemical measurements, as well as a few subjective assessments, of 903 patients who were preclassified by their nutritional status according to PGS-GA were analyzed. Among them, a combination of factors, including age, BMI, albumin, cholesterol, total protein, hematocrit, and changes in body weight and food intake, were statistically selected as variables for SMST. Results: According to SMST, 620 patients (68.7%) were classified as the normal group and 283 patients (31.3%) were classified as the malnutrition group. Significant differences in age, albumin, TLC, BMI, hemoglobin, hematocrit, total protein, cholesterol, and length of stay were observed between the two groups. For inter-methods reliability, the screening results by SMST were compared with those by PGSGA and NRS-2002. The comparison with PGSGA and NRS-2002 showed ‘Substantial agreement' (sensitivity 94.4%, specificity 88.4%, κ = 0.747) and ‘Moderate agreement' (sensitivity 96.1%, specificity 79.5%, κ = 0.505), respectively, indicating that SMST held high inter-methods reliability. Conclusion: In conclusion, SMST, based on readily available laboratory and patient information and simple subjective assessments on changes in food intake and body weight, may be a useful alternative tool with a simple but reliable risk index, especially in resource-limited domestic hospitals.

Keywords: nutrition screening, malnutrition, nutritional status, hospitalized patients.

References

1. Mueller C, Compher C, Ellen DM. American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Board of Directors. A.S. P.E.N. clinical guidelines: Nutrition screening, assessment, and intervention in adults. JPEN J Parenter Enteral Nutr. 2011; 35(1):16–24.

2. Agarwal E, Ferguson M, Banks M, Bauer J, Capra S, Isenring E. Nutritional status and dietary intake of acute care patients: results from the Nutrition Care Day Survey 2010. Clin Nutr. 2012; 31(1):41–47.

3. Almeida AI, Correia M, Camilo M, Ravasco P. Nutritional risk screening in surgery: valid, feasible, easy! Clin Nutr. 2012; 31(2):206–211.

4. Kyle UG, Kossovsky MP, Karsegard VL, Pichard C. Comparison of tools for nutritional assessment and screening at hospital admission: a population study. Clin Nutr. 2006; 25(3):409–417.

5. Pirlich M, Schütz T, Norman K, Gastell S, Lübke HJ, Bischoff SC, Bolder U, Frieling T, Güldenzoph H, Hahn K, Jauch KW, Schindler K, Stein J, Volkert D, Weimann A, Werner H, Wolf C, Zürcher G, Bauer P, Lochs H. The German hospital malnutrition study. Clin Nutr. 2006; 25(4):563–572.

6. Charlton K, Nichols C, Bowden S, Milosavljevic M, Lambert K, Barone L, Mason M, Batterham M. Poor nutritional status of older subacute patients predicts clinical outcomes and mortality at 18 months of follow-up. Eur J Clin Nutr. 2012; 66(11):1224–1228.

7. Lim SL, Ong KC, Chan YH, Loke WC, Ferguson M, Daniels L. Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality. Clin Nutr. 2012; 31(3):345–350.

8. Álvarez-Hernández J, Planas Vila M, León-Sanz M, García de Lorenzo A, Celaya-Pérez S, García-Lorda P, Araujo K, Sarto Gu-erri B. PREDyCES researchers. Prevalence and costs of malnutrition in hospitalized patients; the PREDyCES Study. Nutr Hosp. 2012; 27(4):1049–1059.

9. Kuppinger D, Hartl WH, Bertok M, Hoffmann JM, Cederbaum J, Küchenhoff H, Jauch KW, Rittler P. Nutritional screening for risk prediction in patients scheduled for abdominal operations. Br J Surg. 2012; 99(5):728–737.

10. Ottery FD. Rethinking nutritional support of the cancer patient: the new field of nutritional oncology. Semin Oncol. 1994; 21(6):770–778.

11. Detsky AS, McLaughlin JR, Baker JP, Johnston N, Whittaker S, Mendelson RA, Jeejeebhoy KN. What is subjective global assessment of nutritional status? JPEN J Parenter Enteral Nutr. 1987; 11(1):8–13.

12. Detsky AS, Baker JP, Mendelson RA, Wolman SL, Wesson DE, Jeejeebhoy KN. Evaluating the accuracy of nutritional assessment techniques applied to hospitalized patients: methodology and comparisons. JPEN J Parenter Enteral Nutr. 1984; 8(2):153–159.

13. Baker JP, Detsky AS, Wesson DE, Wolman SL, Stewart S, White-well J, Langer B, Jeejeebhoy KN. Nutritional assessment: a comparison of clinical judgement and objective measurements. N Engl J Med. 1982; 306(16):969–972.

14. Mullen JL, Buzby GP, Waldman MT, Gertner MH, Hobbs CL, Rosato EF. Prediction of operative morbidity and mortality by preoperative nutritional assessment. Surg Forum. 1979; 30:80–82.

15. Bauer J, Capra S, Ferguson M. Use of the scored Patient-Generated Subjective Global Assessment (PG-SGA) as a nutrition assessment tool in patients with cancer. Eur J Clin Nutr. 2002; 56(8):779–785.

16. Kondrup J, Rasmussen HH, Hamberg O, Stanga Z. Ad Hoc ES-PEN Working Group. Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials. Clin Nutr. 2003; 22(3):321–336.

17. Streja E, Kovesdy CP, Molnar MZ, Norris KC, Greenland S, Nissenson AR, Kopple JD, Kalantar-Zadeh K. Role of nutritional status and inflammation in higher survival of African American and Hispanic hemodialysis patients. Am J Kidney Dis. 2011; 57(6):883–893.

18. Han JS, Lee SM, Chung HK, Ahn HS, Lee SM. Development and evaluation of a Nutritional Risk Screening Tool (NRST) for hospitalized patients. Korean J Nutr. 2009; 42(2):119–127.

19. Kim S, Kim S, Sohn C. Development of nutrition screening index for hospitalized patients. Korean J Community Nutr. 2006; 11(6):779–784.

20. Kim JY, Wie GA, Cho YA, Kim SY, Kim SM, Son KH, Park SJ, Nam BH, Joung H. Development and validation of a nutrition screening tool for hospitalized cancer patients. Clin Nutr. 2011; 30(6):724–729.

21. Lee JS, Cho MR, Lee GJ. Validation of the developed nutritional screening tool for hospital Patients. Korean J Nutr. 2010; 43(2):189–196.

22. Kim SY, Yeom HS, Park YM, Chung SH, Shin AR, Han HS, Park DJ. Comparison of tools for nutritional risk screening at hospital admission. J Korean Soc Parent Enter Nutr. 2009; 2(1):6–12.

23. Akpele L, Bailey JL. Nutrition counseling impacts serum albumin levels. J Ren Nutr. 2004; 14(3):143–148.

24. Thorsdottir I, Jonsson PV, Asgeirsdottir AE, Hjaltadottir I, Bjornsson S, Ramel A. Fast and simple screening for nutritional status in hospitalized, elderly people. J Hum Nutr Diet. 2005; 18(1):53–60.

25. Federation of American Societies for Experimental Biology, Life Sciences Research Office. Nutrition monitoring in the United States: an update report on nutrition monitoring. Prepared for the U.S. Department of Agriculture and the U.S. Department of Health and Human Services. DHHS Publication No. (PHS) 89–1255. Washington D.C.: U.S. Government Printing Office;1989.

26. Sauberlich HE, Dowdy RP, Skala JH. Laboratory tests for the assessments of nutritional statues. Cleveland (OH): CRC Press;1974.

27. Delgado-Rodríguez M, Medina-Cuadros M, Gómez-Ortega A, Martínez-Gallego G, Mariscal-Ortiz M, Martinez-Gonzalez MA, Sillero-Arenas M. Cholesterol and serum albumin levels as predictors of cross infection, death, and length of hospital stay. Arch Surg. 2002; 137(7):805–812.

28. Brugler L, Stankovic AK, Schlefer M, Bernstein L. A simplified nutrition screen for hospitalized patients using readily available laboratory and patient information. Nutrition. 2005; 21(6):650–658.

29. Kondrup J, Allison SP, Elia M, Vellas B, Plauth M. Educational and Clinical Practice Committee, European Society of Parenteral and Enteral Nutrition (ESPEN). ESPEN guidelines for nutrition screening 2002. Clin Nutr. 2003; 22(4):415–421.

30. Smith RC, Ledgard JP, Doig G, Chesher D, Smith SF. An effective automated nutrition screen for hospitalized patients. Nutrition. 2009; 25(3):309–315.

31. Velasco C, García E, Rodríguez V, Frias L, Garriga R, Alvarez J, García-Peris P, León M. Comparison of four nutritional screening tools to detect nutritional risk in hospitalized patients: a multicentre study. Eur J Clin Nutr. 2011; 65(2):269–274.

32. Laky B, Janda M, Kondalsamy-Chennakesavan S, Cleghorn G, Obermair A. Pretreatment malnutrition and quality of life – association with prolonged length of hospital stay among patients with gynecological cancer: a cohort study. BMC Cancer. 2010; 10:232.

33. Youden WJ. Index for rating diagnostic tests. Cancer. 1950; 3(1):32–35.

Table 1.

Patient characteristics based on an anthropometric and laboratory data

		Total n = 903 (100%)
Gender	Man Woman	387 (42.9) 516 (57.1)
Age	< 65 (years) ≥ 65 (years)	651 (72.1) 252 (27.9)
Alb¹⁾	< 3.5 (g/dl) ≥ 3.5 (g/dl)	86 (9.5) 817 (90.5)
TLC²⁾	< 900 (cells/mm²) ≥ 900 (cells/mm²)	171 (18.9) 732 (81.1)
BMI³⁾	< 18.5 (kg/m²) ≥ 18.5 (kg/m²)	55 (6.1) 848 (93.9)
Hb⁴⁾	< 12 (g/dl) ≥ 12(g/dl)	432 (47.8) 471 (52.2)
Hct⁵⁾	< 36 (%) ≥ 36 (%)	498 (55.1) 405 (44.9)
T.pro⁶⁾	< 6 (g/ml) ≥ 6(g/ml)	110 (12.2) 793 (87.8)
Chol⁷⁾	< 150 (mg/dl) ≥ 150(mg/dl)	221 (24.5) 682 (75.5)
Wt.change⁸⁾	Yes No	163 (18.1) 740 (81.9)
Intake change⁹⁾	Yes No	184 (20.4) 719 (79.6)
LOS¹⁰⁾	< 11 (day) ≥ 11 (day)	685 (75.9) 218 (24.1)

¹⁾ Alb: albumin

²⁾ TLC: total lymphocyte count

³⁾ BMI: body mass index

⁴⁾ Hb: hemoglobin

⁵⁾ Hct: hematocrit

⁶⁾ T.pro: total protein

⁷⁾ Chol: cholesterol

⁸⁾ Wt.change: weight loss in resent 6 months

⁹⁾ Intake Change: decrease in the last week

¹⁰⁾ LOS: length of stay

Table 2.

Relationship between normal and malnutrition by PGSGA

n (%)	Total 903 (100%)	PGSGA ²⁾		p values
n (%)	Total 903 (100%)	Normal ³⁾ 688 (76.2)	Malnutrition 215 (23.8) ⁴⁾	p values
Age (years)	55.8 ± 13.1¹⁾	54.8 ± 13.0	58.8 ± 13.1	< 0.001
Alb (g/dl)⁵⁾	4.2 ± 0.5	4.3 ± 0.5	3.9 ± 0.6	< 0.001
TLC (cells/mm²)⁶⁾	1517.1 ± 706.8	1575.1 ± 687.8	1331.6 ± 735.1	< 0.001
BMI (kg/m²)⁷⁾	23.4 ± 3.4	23.9 ± 3.3	21.9 ± 3.3	< 0.001
Hb (g/dl)⁸⁾	12.0 ± 1.8	12.2 ± 1.8	11.4 ± 1.9	< 0.001
Hct (%)⁹⁾	35.2 ± 5.3	35.8 ± 5.1	33.2 ± 5.4	< 0.001
T.pro (g/ml)¹⁰⁾	6.7 ± 0.7	6.7 ± 0.6	6.5 ± 0.8	< 0.001
Chol (mg/dl)¹¹⁾	180.9 ± 54.9	184.1 ± 56.6	170.6 ± 48.1	0.002
LOS (day)¹²⁾	8.5 ± 12.4	8.1 ± 11.3	9.9 ± 15.3	0.057

¹⁾ Mean ± SD

²⁾ PGSGA: patient generated-subjective global assessment. score: normal (0–1), malnutrition stage 1 (2–3), mal nutrition stage 2 (4–8), malnutrition stage 3 (≥ 9)

³⁾ Normal: normal + malnutrition stage 1

⁴⁾ Malnutrition: malnutrition stage 2 + malnutrition stage 3

⁵⁾ Alb: albumin

⁶⁾ TLC: total lymphocyte count

⁷⁾ BMI: body mass index

⁸⁾ Hb: hemoglobin

⁹⁾ Hct hematocrit

¹⁰⁾ T.pro: total protein

¹¹⁾ Chol: cholesterol

¹²⁾ LOS: length of stay

Table 3.

Selection of variations in developing a new tool for the Simplified Malnutrition Screening Tool (SMST)

	Odd ratio (95% Cl)¹⁾	p values²⁾
	Odd ratio (95% Cl)¹⁾	Step 1	Step 2	Step 3	Step 4
Age (years)
≥ 65 < 65	5.66 (2.78–11.54) 1.00	< 0.001	< 0.001	< 0.001	< 0.001
BMI (kg/m²)³⁾
< 18.5 ≥ 18.5	5.46 (1.45–20.55) 1.00	0.012	0.012	0.011	0.011
Albumin (g/dl)
< 3.5 ≥ 3.5	3.48 (1.21–9.99) 1.00	0.021	0.020	0.018	0.010
Chol (mg/dl)⁴⁾
< 150 ≥ 150	0.54 (0.27–1.08) 1.00	0.080	0.078	0.076	0.084
T.pro (g/ml)⁵⁾
< 6 ≥ 6	2.64 (1.02–6.81) 1.00	0.045	0.045	0.046	0.045
Hct (%)⁶⁾
< 36 ≥ 36	1.81 (0.62–5.28) 1.00	0.279	0.277	0.033	0.047
Wt.change⁷⁾
Yes No	46.04 (20.89–101.47) 1.00	< 0.001	< 0.001	< 0.001	< 0.001
Intake change⁸⁾
Yes No	319.94 (135.83–753.63) 1.00	< 0.001	< 0.001	< 0.001	< 0.001
Gender
Woman Man	0.66 (0.35–1.23) 1.00	0.187	0.186	0.190
Hb (g/dl)⁹⁾
< 12 ≥ 12	1.10 (0.39–3.11) 1.00	0.860	0.860
TLC (cells/mm²)¹⁰⁾
< 900 ≥ 900	1.00 (0.48–2.06) 1.00	0.993

¹⁾ OR according to logistic regression analysis with all variables (step1)

²⁾ Logistic regression analysis with backward elimination methods

³⁾ BMI: body mass index

⁴⁾ Chol: cholesterol

⁵⁾ T.pro: total protein

⁶⁾ Hct: hematocrit

⁷⁾ Wt.change: weight loss in resent 6 months

⁸⁾ Intake Change: decrease in the last week

⁹⁾ Hb: hemoglobin

¹⁰⁾ TLC: total lymphocyte count

Table 4.

Logistic regression analysis of the variables for SMST model

	Regression coefficient (B)	Odds ratio (95% Cl)
Intercept	–5.214
Age ≥ 65 (years)	1.801	6.05 (2.99–12.26)
BMI < 18.5 (kg/m²) ¹⁾	1.708	5.52 (1.48–20.59)
Albumin < 3.5 (g/dl)	1.362	3.90 (1.38–11.03)
Cholesterol < 150 (mg/dl)	–0.605	0.55 (0.28–1.08)
T.pro < 6 (g/ml) ²⁾	0.968	2.63 (1.02–6.79)
Hct < 36 (%) ³⁾	0.613	1.85 (1.01–3.39)
Wt.change ⁴⁾	3.873	48.11 (21.90–105.67)
Intake change ⁵⁾	5.705	300.23 (129.57–698.70)
Model⁶⁾ = −5.214 + (1.801 × Age) + (1.708 × BMI) + (1.362 × Alb) + (−0.605 × Chol) + (0.968 × T.Pro) + (0.613 × Hct) + (3.873 × Wt. change) + (5.705 × Intake change) P (Malnourished) = exp (model)/1 + exp (model)

¹⁾ BMI: body mass index

²⁾ T.pro: total protein

³⁾ Hct: hematocrit

⁴⁾ Wt.change: weight loss in resent 6 months

⁵⁾ Intake Change: decrease in the last week

⁶⁾ Age (years), < 65 = 0, ≥ 65 = 1; BMI (kg/m²), ≥ 18.5 = 0, < 18.5 = 1; Alb (g/dl), ≥ 3.5 = 0, < 3.5 = 1; Chol (mg/dl), ≥ 150 = 0, < 150 = 1; T.pro (g/ml), ≥ 6 = 0, < 6 = 1; Hct(%), ≥ 36 = 0, < 36 = 1; Wt.change, no weight loss = 0, weight loss = 1; Intake change, no change = 0, decrease = 1

Table 5.

Inter-methods Reliability of the SMST index

SMST ¹⁾ value (positive if less than or equal to)	Sensitivity (%)	Specificity (%)	Youden index ²⁾
–2.2035	0.963	0.855	0.817
–2.0895	0.958	0.856	0.814
–1.9945	0.953	0.862	0.815
–1.8890	0.953	0.869	0.823
–1.7685	0.944	0.878	0.822
–1.7010	0.944	0.882	0.826
–1.5675	0.944	0.884	0.828
–1.3895	0.940	0.887	0.826
–1.3370	0.902	0.911	0.814
–1.2080	0.884	0.917	0.801
–1.0790	0.879	0.917	0.796
–1.0265	0.874	0.922	0.796
–0.8530	0.874	0.923	0.797

¹⁾ SMST: simplified malnutrition screening tool

²⁾ Youden index: sensitivity + specificity – 1

Table 6.

Patient characteristics by SMST

n (%)	Total 903 (100)	SMST ¹⁾		p values
n (%)	Total 903 (100)	Normal 620 (68.7)	Malnutrition 283 (31.3)	p values
Age (years)	55.8 ± 13.1¹⁰⁾	55.1 ± 13.4	57.3 ± 12.4	0.024
Alb (g/dl)²⁾	4.2 ± 0.5	4.3 ± 0.4	4.0 ± 0.6	< 0.001
TLC ³⁾ (cells/mm²)	1517.1 ± 706.8	1572.8 ± 678.1	1395.0 ± 752.7	0.001
BMI (kg/m²)⁴⁾	23.4 ± 3.4	23.9 ± 3.4	22.3 ± 3.3	< 0.001
Hb (g/dl)⁵⁾	12.0 ± 1.8	12.2 ± 1.8	11.6 ± 1.9	< 0.001
Hct (%)⁶⁾	35.2 ± 5.3	35.8 ± 5.1	33.9 ± 5.5	< 0.001
T.pro (g/ml) ⁷⁾	6.7 ± 0.7	6.7 ± 0.6	6.6 ± 0.8	0.006
Chol (mg/dl) ⁸⁾	180.9 ± 54.9	185.6 ± 58.5	170.6 ± 44.7	< 0.001
LOS (day)⁹⁾	8.5 ± 12.4	7.9 ± 11.0	9.9 ± 14.8	0.046

¹⁾ SMST: simplified malnutrition screening tool

²⁾ Alb: albumin

³⁾ TLC: total lymphocyte count

⁴⁾ BMI: body mass index

⁵⁾ Hb: hemoglobin

⁶⁾ Hct: hematocrit

⁷⁾ T.pro: total protein

⁸⁾ Chol: cholesterol

⁹⁾ LOS: length of stay

¹⁰⁾ Mean ± SD

Table 7.

Statistical comparisons of PGSGA, NRS2002 and SMST at admission

	PGSGA ¹⁾		NRS2002 ²⁾		Total
	Normal	Malnutrition	Normal	Malnutrition	Total
SMST ³⁾
Normal	608 (67.3) ⁴⁾	12 (1.3)	615 (68.1)	5 (0.6)	620 (68.7)
Malnutrition	80 (8.9)	203 (22.5)	159 (17.6)	124 (13.7)	283 (31.3)
Total	688 (76.2)	215 (23.8)	774 (85.7)	129 (14.3)	903 (100)
Sensitivity	94.4		96.1
Specificity	88.4		79.5
Kappa value	0.747^∗∗∗		0.505^∗∗∗

¹⁾ PGSGA: patient generated – subjective global assessment. score: normal (0–1), malnutrition stage 1 (2–3), malnutrition stage 2 (4–8), malnutrition stage 3 (≥ 9), normal: normal + malnutrition stage 1, malnutrition: malnutrition stage 2 + malnutrition stage 2 NRS2002: nutritional risk screening 2002

³⁾ SMST: simplified malnutrition screening tool

⁴⁾ n (%)

^∗∗∗ : p < 0.001

TOOLS

Similar articles