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Nutrition |
1 Laboratory Department and 2
Internal Medicine Department, Ospedale di Lavagna, Lavagna, Italy.
3 Molecular Epidemiology, National Cancer Research Institute, Genoa, Italy.
aAddress correspondence to this author at: Medicina Interna, Ospedale di Lavagna, Via Don Bobbio 25, 16033 Lavagna, Italy. Fax 390185-329542; e-mail omar.racchi{at}libero.it.
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Abstract |
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Methods: We studied PEM prevalence and PAB serum concentrations in 108 hospitalized patients. The Detailed Nutritional Assessment (DNA) was used as the reference method to determine PEM. PAB performance was compared with that of 2 other methods, the Subjective Global Assessment (SGA) and the Prognostic Inflammatory and Nutritional Index score (PINI).
Results: According to the DNA reference method, 41% of patients were classified with mild malnutrition and 19% with severe malnutrition. PAB showed the best concordance with the standard DNA method (concordance index, 76.8%) and a good sensitivity/specificity profile (83.1%/76.7%) compared with SGA and PINI.
Conclusions: We conclude that PAB could represent a feasible and reliable tool in the evaluation of malnutrition, especially in settings where it is difficult to obtain a more detailed and comprehensive nutritional assessment such as the DNA.
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Introduction |
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Anthropometric measurement (e.g., of triceps skin-fold thickness or arm-muscle circumference), an early method of nutritional assessment, has been shown to be an inaccurate indicator of nutritional status (2). Several tools to assess malnutrition have been subsequently developed, many based on a subjective evaluation from the operator, such as the Subjective Global Assessment (SGA) (5)(6). This method is based on the assessment of conditions associated with risk of malnutrition and on a physical examination that includes relevant features such as weight loss and loss of subcutaneous fat. A patient-generated SGA is an alternative tool that includes data provided by the patient (7). The MiniNutritional assessment has been developed specifically for geriatric patients. Like the SGA, it includes evaluation of risk factors associated with malnutrition and additional information on nutritional habits (8).
The use of subjective assessments is very skill dependent and can result in underestimation of malnutrition risk. Alternative methods are based on the evaluation of individual biochemical variables, such as measurement of prealbumin (PAB) (9)(10)(11) or retinol binding protein (RBP) (12), or of multiple variables, as in the Prognostic Inflammatory and Nutritional Index (PINI) score (13), which includes evaluation of albumin, 
1-acid glycoprotein, and C-reactive protein (CRP). Other tools, such as the Detailed Nutritional Assessment (DNA) (14), are based on the combination of both approaches and include history, physical examination, and biochemical data. An international consensus on a reference method is still lacking. The DNA can be considered one of the most comprehensive methods, but it is time-consuming, costly, skill dependent, and unsuitable for large-scale use. Therefore, there is a need for a method that is easy to use in clinical practice, with adequate specificity and sensitivity to assess nutritional status in hospitalized patients.
PAB has been shown to be a useful marker in monitoring malnourished patients, because its serum concentrations are closely related to early changes in the nutritional status and it changes in response to nutritional support (11)(15)(16)(17). We tested the feasibility, sensitivity, and specificity of selected screening methods, namely SGA, PINI, PAB, and RBP, compared with DNA, which we used as a reference method.
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Materials and Methods |
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. The study protocol was approved by our institutional review board, and informed consent was obtained from all participants. All nutritional assessments and biochemical testing were performed on the 3rd day after admission with the following methods.
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dna
This method included chart review for height and weight, unintentional weight changes over the previous 3 months, total lymphocyte count, serum albumin concentration, total cholesterol concentration, body mass index, energy requirements and intake during a 24-h period, and the presence of risk factors for malnutrition. Energy intakes were obtained by use of nutritional records of caloric intakes completed during the first 3 days of the hospital stay. The records were completed by the patient with the assistance of caregivers. Nutritional needs were calculated with the Long formula (Harris–Benedict formula corrected by activity and stress factor). Each criterion was scored as previously described by Azad et al. (14), leading to 3 categories of patients: normal (score 7–11), mild malnutrition (score 12–15), and severe malnutrition (score >15).
sga
This method is based on the patient’s history and physical examination. The clinical features addressed in the history were weight loss in the previous 6 months and the presence or absence of gastrointestinal symptoms such as anorexia, nausea, vomiting, and diarrhea. The physical examination included subjective assessment of the loss of subcutaneous fat over the triceps and midaxillary line of the lateral chest wall, muscle wasting in the deltoids and quadriceps, and the presence of ankle edema and/or ascites. According to previously described criteria (5)(6) patients were then classified as class A (normal), class B (mild malnutrition), or class C (severe malnutrition).
pab and rbp
In accordance with previously proposed criteria (15), patients were classified in 3 categories: normal, with PAB serum concentrations >0.17 g/L; mild malnutrition, with concentrations of 0.10–0.17 g/L; and severe malnutrition, with concentrations <0.10 g/L. For RBP, cutoff values were as follows: normal, with RBP concentrations >0.03 g/L; mild malnutrition, with concentrations of 0.02–0.03 g/L; and severe malnutrition, with concentrations <0.02 g/L [modified from Ingenbleek et al. (12)].
pini scoring
This method is based on the measurement of the plasma concentrations of albumin, 1-acid glycoprotein, and CRP. We reduced the original 5-category classification (13) to 3 categories: normal (PINI score <1), mild malnutrition (PINI score 1–20), and severe malnutrition (those originally classified as "risk for death"; PINI score >20).
laboratory methods
We measured PAB, RBP, and albumin with a nephelometric assay (BNII, Laser Nephelometer, Dade Behring). Total cholesterol was measured by the automated cholesterol oxidase: p-aminophenazone (CHOD-PAP) method, CRP and 1-acid glycoprotein by turbidimetric methods (Modular PP, Roche), and lymphocyte counts by ADVIA 120 (Bayer). All the procedures were in accordance with the Health Quality Service Standards.
statistical methods
We used current criteria for the assessment of diagnostic tests, including concordance, sensitivity, and specificity, to evaluate the validity of methods used as alternatives to the DNA method, which served as the reference or gold standard. Agreement between DNA and the other nutritional assessments was also assessed with the Cohen 
test, designed to measure the interrater agreement. Cohen agreement was defined as "poor" if was <0.20, "fair" if was >0.21 and <0.60, "substantial" if was >0.61 and <0.80, and "good" if was >0.80 (18).
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Results |
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. For each method, percentages of patients in each category were as follows: DNA, 41% mild malnutrition and 19% severe malnutrition; SGA, 40% mild malnutrition and 13% severe malnutrition; PINI, 35% mild malnutrition and 29% severe malnutrition; PAB, 44% mild malnutrition and 16% severe malnutrition; and RBP, 42% mild malnutrition and 17% severe malnutrition (Table 3
). Given the highly significant correlation between PAB and RBP (r = 0.77; P <0.001), and also taking into account the potential influence of chronic renal failure on RBP (12)(15), we decided to use only PAB in the nutritional evaluation.
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PAB showed the best concordance with the DNA reference method (concordance index, 76.8%). Corresponding values for SGA and PINI were 63.6% and 63.9%, respectively. Cohen test values were 0.63 for PAB (indicating a substantial agreement), 0.45 for PINI (fair agreement), and 0.40 for SGA (fair agreement).
After combining mild and severe malnutrition into a single group, we evaluated the degree of specificity and sensitivity of different methods. Results for sensitivity/specificity with DNA as the reference method were as follows: SGA, 76.5%/83.7%; PINI, 83.0%/65.1%; and PAB, 83.1%/76.7%. All methods showed good sensitivity. PAB showed the best sensitivity (83.1%), and SGA showed the best specificity (83.7%). PINI showed intermediate results, with good sensitivity and poor specificity.
We found that only 28% of patients achieved at least 80% of their calculated nutritional need. However, we found no significant difference between DNA and PAB for patients reaching vs not reaching 80% of their required energy intake (data not shown). Similarly, after stratification of malnourished and normally nourished patients, we observed no differences in mean PAB values when we compared patients above and below their 80% energy intake (data not shown).
CRP plasma concentrations were increased in 72 patients (67%). We found a statistically significant inverse correlation between PAB and CRP (P <0.05) (Fig. 1
). In spite of the inverse relationship between PAB and CRP, we observed very good concordance between PAB and DNA at high and low CRP concentrations (Table 4
), with concordance indexes of 80.6% for high and 77.8% for low CRP concentrations.
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Discussion |
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DNA can be considered a reliable procedure to identify patients at risk of malnutrition, but this method is time-consuming and difficult to use on a large scale. In the last few years, many nutritional screening tools have been developed, tested, and implemented in clinical practice, several combining laboratory tests and patient information (22). Biochemical markers have always been an attractive option because they are easier to introduce and standardize in clinical practice. Albumin is a traditional marker of nutritional status, but its large body pool, with a half-life of 20 days, and its sensitivity to the patient’s hydration state make it too insensitive to be used to assess PEM. PAB is a better nutritional marker because it has a short half-life (48 h), a relatively small body pool, and a rapid rate of synthesis that responds to protein intake (9). Plasma PAB concentration has been shown to significantly decrease only 3 days after inadequate nutrient intake (16), and to increase 1 mg/day when the nutrient needs are satisfied (17); plasma PAB can be influenced by an acute or chronic renal insufficiency, however (16).
Our prevalence data, which show that 60% of patients had variable degrees of malnutrition (Table 3
), are in agreement with the literature (1)(2)(3). The higher percentage of patients with severe malnutrition identified with PINI can be explained by the fact that this method is affected by plasma concentrations of acute-phase proteins indicative of a stress hypermetabolic response. In our study group, only 30 patients (28%) achieved at least 80% of their calculated nutritional need, a cutoff value that has been shown to correlate with a high risk of malnutrition during hospitalization (23). On the other hand, the proportion of patients identified as normally nourished by the DNA and the other methods was higher (range, 36%–47%), a discrepancy that can be explained by the fact that the energy intake is only a part of the DNA score calculation, and intake below the expected 80% is a condition of risk that does not necessarily correlate with malnutrition as closely as other variables.
Our results showed various degrees of concordance between DNA and the alternative methods investigated. Among these, PAB showed the best concordance with DNA and had a good sensitivity/specificity profile. A major limitation to the use of biochemical markers is that their plasma concentrations may be influenced by pathologic conditions. In particular, PAB concentrations decrease in the presence of inflammation (negative acute-phase reactant). The inverse correlation between PAB and CRP concentrations (Fig. 1
) may represent a confounding factor in the interpretation of the results. Plasma PAB concentrations change rapidly; a decrease of up to 50% in PAB concentration is expected after few days of inadequate nutrient intake and/or diseases with an acute phase response, conditions that often coexist in severely ill patients (24). Conversely, a rapid increase of PAB concentration is seen when adequate nutritional intake is restored (21) or CRP stabilizes(25); therefore rapid changes of CRP can induce an overestimation of malnutrition. Although these limitations should be taken into consideration, our data suggest that PAB can still be reliable in cases involving inflammation. A good correlation between PAB and DNA was found at both low and high CRP concentrations (Table 4
). Notably, CRP and other markers of acute-phase response are not included in the DNA score calculation.
In conclusion, our study results indicate that PAB is an inexpensive, feasible, and reliable tool in the evaluation of malnutrition affecting hospitalized patients, particularly in settings where it is difficult to perform a more detailed and comprehensive nutritional assessment such as the DNA. Further investigation with sequential measurements is needed to elucidate the complex relationship between PAB and inflammation and clarify the role of PAB in monitoring the efficacy of nutritional interventions.
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Footnotes |
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References |
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The following articles in journals at HighWire Press have cited this article:
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  A. Shenkin Serum Prealbumin: Is It a Marker of Nutritional Status or of Risk of Malnutrition? Clin. Chem., December 1, 2006; 52(12): 2177 - 2179. [Full Text] [PDF]
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