Malnutrition Screening and Assessment
Abstract
:1. Introduction
2. Methods: Literature Search Strategy
3. Early Diagnosis of Malnutrition: Nutritional Screening
4. Nutritional Screening Tools
4.1. Mini Nutritional Assessment Short Form (MNA-SF)
4.2. Malnutrition Universal Screening Test (MUST)
4.3. Simplified Nutritional Appetite Questionnaire (SNAQ)
4.4. Nutritional Risk Screening 2002 (NRS 2002)
4.5. Malnutrition Screening Tool (MST)
4.6. Nutrition Risk in the Critically Ill (NUTRIC Score)
4.7. Risk Scales Based on Nutritional Parameters
4.7.1. Nutritional Risk Index (NRI)
4.7.2. Geriatric Nutritional Risk Index (GNRI)
4.7.3. Prognostic Nutritional Index (PNI)
4.7.4. Prognostic Inflammatory and Nutritional Index (PINI)
4.8. Other Nutritional Screening Tools
5. Nutritional Assessment
5.1. Clinical Assessment
5.2. Anthropometry
5.2.1. Weight and Derived Indices
5.2.2. Body Mass Index (BMI)
5.2.3. Circumference Measures and Skinfolds
5.3. Body Composition Methods
5.3.1. Bioimpedance Analysis (BIA)
5.3.2. Dual-Energy X-ray Absorptiometry (DEXA)
5.3.3. Computed Tomography (TC)
5.3.4. Magnetic Resonance Imaging (MRI)
5.3.5. Densitometry
5.3.6. Other Techniques
5.3.7. Muscle Ultrasonography
5.4. Functional Examination
- Functional measurement of muscle strength is important, since protein and energy deficiency decrease muscle strength and power, and general physical condition. Muscle function tests are very sensitive to nutritional deficiencies and, therefore, to nutritional interventions as well. The most widely used test is dynamometry, which measures voluntary muscle strength (hand grip strength) and correlates well with nutritional status and results, as well as with the response to nutrition and the rehabilitation process. It is easy to perform and provides quantitative data that can be used in the diagnosis of sarcopenia; one diagnostic criterion is a manual compression force of <27 kg in men and <16 kg in women [132]. There is an inverse relationship between the pressure produced and the number of postoperative complications, length of hospital stays, and hospital readmission rate [133]. It is one of the diagnostic criteria for malnutrition for ASPEN [133];
- Respiratory function: the measurement of peak flow and FEV1 reflects respiratory muscle strength, related to catabolism and protein loss;
- Immune function: measures the cellular response to intradermal antigens. Situations of severe malnutrition led to anergy: a lack of response to antigens.
5.5. Laboratory Parameters
- Serum albumin is the most extensively studied protein in relation to malnutrition, and it is shown to be a good predictor of surgical risk [135,136]. However, due to its long half-life of 18 days, it reflects the severity of the disease and not of malnutrition in acute situations, behaving as a negative acute-phase reactant which, in inflammatory situations, causes a reduction in its synthesis, an increase in transcapillary losses, and an increase in degradation and dilution due to hyperhydration. However, it is a good nutritional indicator in chronic malnutrition. Serum albumin is often included in certain nutritional screening tools, particularly nutritional risk scores [110,137,138,139];
- Shorter half-life proteins, such as transthyretin (2 days) and transferrin (7 days), are also subject to the same distribution and influences of dilution as albumin, but may be better and more sensitive reflections of nutritional status. Transthyretin, also called prealbumin, is a good marker of malnutrition when there are no signs of inflammation [140], and it is a good data item for following evolution after a nutritional intervention, even when inflammation is present [137]. Normal values are between 20 and 30 mg/dL, a moderate degree of malnutrition is between 10 and 20 mg/dl, and severe malnutrition corresponds to values below 10 mg/dL. In different studies it is correlated with visceral and muscle proteins compared with studies using BIA and DXA [141]. The C-reactive protein (CRP)/prealbumin ratio, known to be a prognostic indicator of complications, is proposed for assessing the effect of inflammation on prealbumin levels [142];
- Creatinine reflects kidney function, but also correlates with muscle mass. Creatine is metabolized to creatinine at a steady rate, and it is related to the muscle mass. Its excretion in 24 h is used to calculate the creatinine height index CHI% = (urine creatinine in 24 h × 100)/ideal creatin uria index obtained from standard tables. Values of >30% indicate severe muscle depletion, values between 15% and 30% are moderate, and below 15% is mild [110];
- Another parameter measured in urine is 3-Methylhistidine (3MH), which fundamentally depends on muscle degradation, pointing to a decrease in situations of muscle mass loss, and to an increase in situations of stress-associated protein catabolism [143];
- Nitrogen balance can be useful in critically ill patients in whom nitrogen intake is known, and nitrogen losses through urine can be measured either directly using the Kjeldahl method, or by extrapolating it from the urine’s urea content. Although it is not exact, it can provide guidance in ascertaining protein catabolism and as an indication for intake [143];
6. Methods of Nutritional Screening and Assessment
6.1. Subjective Global Assessment (SGA)
6.2. Mini Nutritional Assessment (MNA)
6.3. ESPEN Criteria
6.4. AND/ASPEN Tool (ASPEN)
6.5. Global Leadership Initiative on Malnutrition (GLIM)
6.6. Resume of Nutritional Assessments Tools
7. Discussion
- Body composition measurement tools are used mostly in research, although some of them, such as anthropometry and BIA, can be used in the clinical setting, supported by CT, DXA, and MRI;
- Initiatives for performing nutritional assessment through tools such as SGA, MNA, ESPEN criteria, AND-ASPEN, and GLIM are recommended by the scientific societies, are intended to reach an easier and faster diagnosis, and can be applied to a greater typology of patients;
- The NFPE, together with anthropometric and biochemical values, and particularly with function measurements, such as quality of life and dietary intake surveys, together with muscle strength measurements. Although it is costly in time, it can give a nutritional diagnosis, determine the severity of the malnutrition, and help to highlight specific vitamin and micronutrient deficiencies.
8. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Questions | Points |
---|---|
Did you lose weight unintentionally? | |
More than 6 kg in the last 6 months | 3 |
More than 6 kg in the last 3 months | 2 |
Did you experience a decreased appetite over the last month? | 1 |
Did you use supplemental drinks or tube feeding over the last month? | 1 |
Impaired Nutritional Status | Severity of Disease (Stress Metabolism) | ||
---|---|---|---|
Absent score 0 | Normal nutritional status | Absent score 0 | Normal nutritional requirements |
Mild score 1 | Weight loss 45% in 3 months or Food intake below 50–75% of normal requirement in preceding week | Mild score 1 | Hip fracture; chronic patients, in particular with acute complications: cirrhosis; COPD; chronic hemodialysis, diabetes, oncology |
Moderate score 2 | Weight loss 45% in 2 months or BMI 18.5–20.5 + impaired general condition or Food intake 25–50% of normal requirement in preceding week | Moderate score 2 | Major abdominal surgery; stroke; severe pneumonia, hematologic malignancy |
Severe score 3 | Weight loss >5% in 1 month >15% in 3 months or Body Mass Index of 18.5 + impaired general condition or Food intake 0–25% of normal requirement in preceding week | Severe score 3 | Head injury; bone marrow transplantation; intensive care patients (APACHE 10) |
Have you lost weight recently without trying? | |
No | 0 |
Unsure | 2 |
If yes, how much weight (kilograms) have you lost? | |
1–5 | 1 |
6–10 | 2 |
11–15 | 3 |
>15 | 4 |
Unsure | 2 |
Have you been eating poorly because of a decreased appetite? | |
No | 0 |
Yes | 1 |
Total | |
Score of 2 or more = patient at risk of malnutrition. |
Variable | Range | Points | |
---|---|---|---|
Age | <50 | 0 | |
50–<75 | 1 | ||
≥75 | 2 | ||
APACHE II | <15 | 0 | |
15–<20 | 1 | ||
20–28 | 2 | ||
≥28 | 3 | ||
SOFA | <6 | 0 | |
6–<10 | 1 | ||
≥10 | 2 | ||
Number of co-morbidities | 0–1 | 0 | |
≥2 | 1 | ||
Days from hospital to ICU admission | 0–<1 | 0 | |
≥1 | 1 | ||
IL-6 | 0–<400 | 0 | |
≥400 | 1 | ||
Sum of points | Category | Explanation | |
NUTRIC score scoring system, if IL-6 available | |||
6–10 | High score |
| |
0–5 | Low score |
| |
NUTRIC score scoring system, if no IL-6 available | |||
5–9 | High score |
| |
0–4 | Low score |
|
Tool/Acronym/Year | Features/Aspects | Patients Group | Reference |
---|---|---|---|
Instant nutritional assessment (INA, 1979) | Serum albumin levels and total lymphocyte counts | Cancer surgery, liver, and pancreatic diseases | Seltzer et al. [74] |
Prognostic nutritional index (PNI, 1979) | Serum albumin, TSF, TFN, DH | Surgical patients | Mullen et al. [66] |
Prognostic inflammatory and nutritional index (PINI, 1985) | C-reactive protein, orosomucoid, albumin, and transthyretin | Cancer patients, surgery, liver diseases, trauma, burn | Ingenbleek et al. [73] |
Nutritional screening initiative checklist (DETERMINE, 1994) | Questionary about nutritional well being | Elderly people | Dwyer J. [75] |
Nutritional Risk Index (NRI, 1988) | Serum albumin, current/usual body weight ratio. | All inpatients | Buzby et al. [56] |
Malnutrition screening tool (MST, 1999) | Data about recent appetite status and weight loss | All inpatients | Ferguson et al. [46] |
Risk Evaluation for Eating and Nutrition (SCREEN, 2000). | Factors affecting food intake, access to food, social factors, anthropometry, dietary intake | Elderly people | Keller et al. [76] |
Malnutrition inflammatory score (MIS, 2001) | SGA method combined with BMI, serum albumin, and serum TIBC | Dialysis patients | Kalantar-Zadeh et al. [77] |
South Manchester University Hospitals nutritional Assessment Score (2001) | Age, mental condition, weight, dietary intake, ability to eat, medical condition, and gut function | All inpatients | Burden ST [78] |
Controlling nutritional status (CONUT, 2002) | Laboratory data (serum albumin, cholesterol, total lymphocytes, and hematocrit) | All inpatients | Ulibarri et al. [47] |
Nutritional risk screening 2002 (NRS-2002, 2003) | BMI, weight loss, and acute disease score | All inpatients | Kondrup et al. [40] |
Malnutrition Universal Screening Tool (MUST, 2004) | BMI, weight loss, and illness in relation to food intake | All inpatients | Elia et al. [31] |
Rapid Screen (2004) | Weight change, BMI | Inpatients | Visvanathan et al. [79] |
British nutrition screening tool (NST) 2004 | Weight, height, recent unintentional weight loss, and appetite | All inpatients | Weekes et al. [80] |
Simplified Nutritional Appetite Questionnaire (SNAQ, 2005) | Items related to appetite, food timing during day, food preferences, and daily number of meals | Elderly patients | Kruizenga et al. [39] |
Geriatric Nutritional Risk Index (GNRI, 2005) | Serum albumin and the relationships between current weight and ideal weight | Elderly patients | Bouillane et al. [58] |
Glasgow Prognostic Score (GPS, 2007) | Serum levels of albumin and C-reactive protein (CRP) | Cancer patients | McMillan et al. [81] |
Protein Energy Wasting (PEW, 2008) | Serum chemistry, BMI, muscle mass, and dietary intake | Dialysis patients | Fouque et al. [82] |
Cachexia consensus (2008) | Decreased muscle strength, fatigue, anorexia, low fat-free mass index, abnormal biochemistry | Cachexia diseases | Evans WJ et al. [83] |
Mini Nutritional Assessment short form (MNA-SF, 2009) | First 6 items of 18 MNA | Elderly patients | Rubenstein et al. [25] |
Imperial Nutritional Screening (INSYST, 2009) | Unintentional weight loss, reduced food intake | All inpatients | Tammam et al. [84] |
3-Minute Nutrition Screening (3-MinNS, 2009) | Unintentional weight loss in the past six months, intake in the past week, body mass index (BMI), disease with nutrition risks, and presence of muscle wasting in the temporalis and clavicular areas | All inpatients | Lim et al. [85] |
Objective screening nutrition dialysis (OSND, 2010) | Some anthropometric measurements, albumin, transferrin, and cholesterol levels | Dialysis patients | Beberashvili et al. [86] |
Cancer cachexia classification (2011) | Weight loss, BMI, dietary intake, anorexia, muscle mass, metabolic change | Cancer patients | Fearon et al. [87] |
Nutrition Risk in Critically ill (NUTRIC, 2011) | Age, APACHE II score, SOFA score, comorbidities, days in the hospital before admission to the ICU, and interleukin-6 | Critically ill patients | Heyland et al. [48] Rahman et al. [49] |
Spinal nutrition screening tool (SNST, 2012) | History of recent weight loss, BMI, age, level of SCI, presence of co-morbidity, skin condition, appetite, and ability to eat. | Spinal cord-injured patients | Wong et al. [88] |
Royal Free Hospital Nutritional Prioritizing Tool (RFH-NPT, 2012) | Unintentional weight loss, BMI, influence of excess body fluids, and food intake. | Chronic liver disease | Arora et al. [89] |
Nutrition impact symptoms score (NIS, 2013) | Symptoms impacting on food intake | Dialysis patients | Campbell et al. [90] |
Eating Validation Scheme (EVS, 2013) | Eating habits | Elderly in primary care | Beck et al. [91] |
Canadian Nutrition Screening Tool (CNST, 2015) | Weight loss, decreased food intake, body mass index (BMI) | All inpatients | Laporte et al. [92] |
Royal Marsden Nutrition Screening Tool (RMNST, 2015) | Weight loss during the previous 3 months, a food intake of less than 50 % of normal in the previous 5 days, symptoms affecting intake | Cancer patients | Shaw er al. [93] |
Malnutrition Inflammation Risk Tool (MIRT, 2016) | BMI, weight Loss, CRP | Inflammatory bowel diseases | Jansen et al. [94] |
NUTRISCORE (2017) | MST, tumor location, active treatment | Cancer patients | Arribas et al. [95] |
Saskatchewan Inflammatory Bowel Disease Nutrition Risk Tool (SaskIBD-NRT, 2018) | Weight loss, GI symptoms, anorexia, food intake restriction | Inflammatory bowel diseases | Haskey et al. [96] |
BMI–lymphocyte–uric acid–triglyceride (BULT, 2019) | BMI, lymphocyte, uric acid, and triglyceride | Esophageal squamous cell carcinoma | Xu et al. [97] |
Bach Mai Boston Tool (BBT, 2019) | Oral intake, body mass index (BMI), and weight loss in the last 3 months. | Cancer patients | Van et al. [98] |
Dialysis Malnutrition Score (DMS, 2021) | Similar to PS-SGA with additional questions about dialysis history, and physical examination concerning loss of subcutaneous fat and muscle wasting. | Dialysis patients | Hassanin et al. [99] |
Nutritional Screening inflammatory bowel diseases (NS-IBD, 2021) | BMI, unintended weight loss, GI symptoms, surgery for IBD | Inflammatory bowel diseases | Fiorindi et al. [100] |
Alternative 1: | BMI < 18.5 kg/m2 |
Alternative 2: | Weight loss (unintentional) > 10% indefinite of time, or >5% over the last 3 months combined with either: BMI < 20 kg/m2 if <70 years of age, or <22 kg/m2 if =>70 years of age, or FFMI < 15 kg/m2 in women and 17 kg/m2 in men |
Phenotypic Criteria | Etiologic Criteria | |||
---|---|---|---|---|
Weight Loss (%) | Low Body Mass Index (kg/m2) | Reduced Muscle Mass | Reduced Food Intake or Assimilation | Inflammation |
>5% within past 6 months or >10% beyond 6 months | <20 if <70 years, or <22 if >70 years | Reduced by validated body composition measuring techniques | <50% of ER >1 week, or any reduction for >2 weeks or any chronic GI condition that adversely impacts food assimilation or absorption | Acute disease/injury or chronic disease-related |
Subjective Global Assessment (SGA, 1987) | Weight change, dietary intake change, gastrointestinal symptoms, functional capacity, and physical examination | Cancer patients, surgery, liver diseases | Detsky et al. [145] |
Patient-Generated Subjective Global Assessment (PG-SGA, 1996) | Weight change, dietary intake change, gastrointestinal symptoms, functional capacity, and physical examination | Cancer patients, surgery, liver diseases | Ottery FD. [152] |
Mini nutritional assessment (MNA, 1996) | Anthropometric measures, clinical history, and nutritional data | Elderly people | Guigoz et al. [158] |
ASPEN Criteria for malnutrition (2012) | Insufficient energy intake, weight loss, loss of muscle mass, loss of subcutaneous fat, localized or generalized fluid accumulation, diminished functional status | All patients | White J et al. [133] |
ESPEN criteria for malnutrition (2015) | BMI (<18.5 kg/m2), or weight loss and reduced BMI, or a low FFMI | All patients | Cederholm T et al. [108] |
GLIM (2019) | Weight loss, BMI, muscle mass, dietary intake change, inflammation | All patients | Cederholm T et al. [166] |
Tool | Sensitivity | Specificity | Positive Predictive Value | Negative Predictive Value | Overall Validity | Agreement | Reliability |
---|---|---|---|---|---|---|---|
MST | Moderate | Moderate | Moderate | Moderate | Moderate | Moderate | Moderate |
MUST | Moderate | Moderate | Moderate | High | High | Moderate | Moderate |
MNA-SF | Moderate | Moderate | Low | Moderate | Moderate | Low | Moderate |
SNAQ | Moderate | High | Low | High | Moderate | — | Moderate |
MNA-SF-BMI | Moderate | Moderate | Moderate | High | Moderate | Moderate | — |
NRS-2002 | Moderate | High | Moderate | Moderate | Moderate | Moderate | — |
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Serón-Arbeloa, C.; Labarta-Monzón, L.; Puzo-Foncillas, J.; Mallor-Bonet, T.; Lafita-López, A.; Bueno-Vidales, N.; Montoro-Huguet, M. Malnutrition Screening and Assessment. Nutrients 2022, 14, 2392. https://doi.org/10.3390/nu14122392
Serón-Arbeloa C, Labarta-Monzón L, Puzo-Foncillas J, Mallor-Bonet T, Lafita-López A, Bueno-Vidales N, Montoro-Huguet M. Malnutrition Screening and Assessment. Nutrients. 2022; 14(12):2392. https://doi.org/10.3390/nu14122392
Chicago/Turabian StyleSerón-Arbeloa, Carlos, Lorenzo Labarta-Monzón, José Puzo-Foncillas, Tomas Mallor-Bonet, Alberto Lafita-López, Néstor Bueno-Vidales, and Miguel Montoro-Huguet. 2022. "Malnutrition Screening and Assessment" Nutrients 14, no. 12: 2392. https://doi.org/10.3390/nu14122392
APA StyleSerón-Arbeloa, C., Labarta-Monzón, L., Puzo-Foncillas, J., Mallor-Bonet, T., Lafita-López, A., Bueno-Vidales, N., & Montoro-Huguet, M. (2022). Malnutrition Screening and Assessment. Nutrients, 14(12), 2392. https://doi.org/10.3390/nu14122392