ArticleBMC pediatrics2024
Ultrasound assessment of malnutrition in infancy: a pilot case-control study.
Article in BMC pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- A machine learning approach to using ultrasound for body composition and nutritional status assessment in newborns: a pilot study protocol.Pilot and feasibility studies · 2026Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
Abstract
This study aimed at determining the intra- and inter-rater reliability in ultrasound body composition measurements and investigating the differences between malnourished and non-malnourished infants. Sonographic images for measurements of fat and muscle thickness were compared between 9 malnourished and 9 non-malnourished hospitalized infants. The mean of fat and muscle thickness sums were 12.44 ± 7.58 mm and 28.98 ± 7.18 mm, respectively. The intra- and inter-rater intraclass correlation coefficient were above 0.9 for both measurements, indicating high intra- and inter-rater reliability. Compared to non-malnourished infants, malnourished infants have 45% of fat thickness sum and 71% of muscle thickness sum. Ultrasound measurements of body composition in infants were different between hospitalized malnourished and non-malnourished infants. This approach has the potential to be utilized more broadly, from assessing the nutritional status of critically ill infants in intensive care units to screening for malnutrition in high-risk infant populations.
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Registered trials
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