Evidence map›Paper›PMID 32529169›Full record

ArticleCurrent developments in nutrition2020

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

Shirley Sze, Pierpaolo Pellicori, Jufen Zhang, Joan Weston, Andrew L Clark

Abstract read
In one paragraph

Article in Current developments in nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Nutritional Behaviors of Patients With Heart Failure.Nursing research and practice · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shirley SzeDepartment of Cardiology, Castle Hill Hospital, Hull York Medical School at University of Hull, Kingston upon Hull, United Kingdom.
Pierpaolo PellicoriDepartment of Cardiology, Castle Hill Hospital, Hull York Medical School at University of Hull, Kingston upon Hull, United Kingdom.ORCID 0000-0001-7175-0464
Jufen ZhangDepartment of Cardiology, Castle Hill Hospital, Hull York Medical School at University of Hull, Kingston upon Hull, United Kingdom.ORCID 0000-0003-2704-6212
Joan WestonDepartment of Cardiology, Castle Hill Hospital, Hull York Medical School at University of Hull, Kingston upon Hull, United Kingdom.
Andrew L ClarkDepartment of Cardiology, Castle Hill Hospital, Hull York Medical School at University of Hull, Kingston upon Hull, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

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

methodsWe 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.

resultsMen 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.

conclusionsMalnutrition 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.

Indexed as

agreementassessmentclassification performanceheart failuremalnutritionscreening

Identifiers

PMID32529169
PMCPMC7272189

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.