Nutrition Screening Adults

NSCR: Definitions and Criteria (2009)

Nutrition Screening - Nutrition Screening is the process of identifying patients, clients, or groups who may have a nutrition diagnosis and benefit from nutrition assessment and intervention by a registered dietitian (RD).

Key Considerations:

Nutrition screening may be conducted in any practice setting as appropriate
Nutrition screening tools should be quick, easy to use, valid and reliable for the patient, population or setting
Nutrition screening tools and parameters are established by RDs, but the screening process may be carried out by DTRs and others who have been trained in nutrition screening
Nutrition screening and rescreening should occur within an appropriate timeframe for the setting.

Agreement - Measures the extent to which two sets of scores are identical (e.g., scores obtained from two different tools).

Kappa (k) - A statistical measure of inter-rater agreement, developed by Jacob Cohen in 1960. Because k takes into account the agreement occurring by chance, it is generally thought to be a more robust measure than calculating percent agreement. The equation for k is: $\kappa = \frac{\Pr(a) - \Pr(e)}{1 - \Pr(e)}, \!$ where Pr(a) is the relative observed agreement among raters, and Pr(e) is the hypothetical probability of chance agreement. Kappa is always less than or equal to 1. A value of 1 implies perfect agreement and 0 or less implies no agreement (above that expected by chance).

♦Source: http://en.wikipedia.org/wiki/Cohen's_kappa#endnote_Landis1977

Kappa Interpretation - Landis and Koch (1977) gave the following table for interpreting $?$ values. The table was based on personal opinion and is by no means universally accepted. These guidelines must be interpreted cautiously, as the number of categories and subjects will affect the magnitude of the value. The kappa will be higher when there are fewer categories.

$k$	Interpretation
<0	No agreement
0.0 - 0.20	Slight agreement
0.21 - 0.40	Fair agreement
0.41 - 0.60	Moderate agreement
0.61 - 0.80	Substantial agreement
0.81 - 1.00	Almost perfect agreement

♦Source: http://en.wikipedia.org/wiki/Cohen's_kappa#endnote_Landis1977

Negative Predictive Value (NPV) - The proportion of patients with negative test results who are correctly diagnosed as not having the disease/condition. If the data arise from a cross-sectional study (or any study from which valid prevalence estimates can obtained), then the Negative Predictive Value can be defined as:

$NPV = \frac{\rm number\ of\ True\ Negatives}{{\rm number\ of\ True\ Negatives}+{\rm number\ of\ False\ Negatives}}$

For any type study, a more general formula will work:

$NPV = \frac{({\rm specificity}) ({\rm 1 - prevalence})}{({\rm specificity}) ({\rm 1 - prevalence}) + (1 - {\rm sensitivity}) ({\rm prevalence})}$

♦Source: http://en.wikipedia.org/wiki/Negative_predictive_value

Positive Predictive Value (PPV) - Also called precision rate or post-test probability of disease, it is the proportion of patients with positive test results who are correctly diagnosed. It is the most important measure of a diagnostic method as it reflects the probability that a positive test reflects the underlying condition being tested for. Its value does however depend on the prevalence of the disease, which may vary. The Positive Predictive Value can be defined as

$PPV = \frac{\rm number\ of\ True\ Positives}{{\rm number\ of\ True\ Positives}+{\rm number\ of\ False\ Positives}}$

or, alternatively,

$PPV = \frac{({\rm sensitivity}) ({\rm prevalence})}{({\rm sensitivity}) ({\rm prevalence}) + (1 - {\rm specificity}) (1-{\rm prevalence})}$

♦Source: http://en.wikipedia.org/wiki/Positive_predictive_value

Quick and Easy Nutrition Screening Tool - For purposes of the evidence analysis, the Nutrition Screening workgroup has defined a quick and easy tool as one that can be completed in less than 10 minutes.

Reliability - Measures the agreement between the results of the tool when administered by different users (inter-rater) or on different occasions (intra-rater).

Sensitivity - Percentage of undernourished subjects identified by the tool as being at risk (a / a + c). It refers to the proportion of true positives (those with the disease or condition of interest) that are correctly identified by the test.

Specificity - Percentage of adequately nourished subjects identified as not at risk (d / b + d). It refers to the proportion of true negatives (those without the disease or condition of interest) that are correctly identified by the test.

	Under- Nourished	Adequately Nourished
At Risk	a	b
Not at Risk	c	d

♦Reference: Jones JM. Nutritional screening and assessment tools. Nova Science Publishers Inc., New York. 2006; Altman, DG and Bland, JM. Statistics Notes: Diagnostic tests 1: sensitivity and specificity BMJ, Jun 1994; 308: 1,552.

Validity

Construct validity - Extent to which measure performs in accordance with theoretical expectations
Criterion validity - Comparison of a measure/tool with some other measure (usually gold standard). Can be divided into concurrent and predictive validity
Concurrent validity - Comparison of tool with a criterion measured at a similar time to tool
Predictive validity - Compares tool with a future criterion.