Agreement and Classification Performance of Malnutrition Tools in Patients with Chronic Heart Failure

Malnutrition is common in patients with chronic heart failure (CHF) and is associated with adverse outcome, but few data exist.

The objective of this study was to compare the agreement and classification performance of 6 malnutrition tools in patients with CHF.

We evaluated the performance of 6 malnutrition tools: COntrolling NUTritional Status Index (CONUT), Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), Malnutrition Universal Screening Tool (MUST), Mini Nutritional Assessment-Short Form (MNA-SF), and Subjective Global Assessment (SGA), in 467 consecutive patients with CHF who attended our clinic for follow-up. We used Venn diagrams and Kappa statistics to study the agreement of different tools. Because there is no "gold standard" for malnutrition evaluation, for each of the malnutrition tools, we used the results of the other 5 tools to produce a standard combined index for evaluating at least moderate malnutrition. Subjects were considered as having at least moderate malnutrition if so identified by ≥3/5 tools. We evaluated the sensitivity, specificity, and predictive values of different tools in identifying significant malnutrition as defined by the combined index.

Men comprised 67% of patients, median age was 76 years, and median N-terminal pro-B-type natriuretic peptide (NTproBNP) was 1156 ng/L. The prevalence of any degree and at least moderate malnutrition ranged between 6-60% and 3-9%, respectively, with CONUT classifying the highest proportion of subjects as malnourished. Malnourished patients tended to be older and have worse symptoms, higher NTproBNP, and more comorbidities. CONUT had the highest sensitivity (80%), MNA-SF and SGA had the highest specificity (99%), and MNA-SF had the lowest misclassification rate (2%) in identifying at least moderate malnutrition as defined by the combined index.

Malnutrition is common in patients with CHF. The prevalence of malnutrition varies depending on the tool used. Among the 6 malnutrition tools studied, MNA-SF has the best classification performance in identifying significant malnutrition as defined by the combined index.