Observational studyNutrition & dietetics : the journal of the Dietitians Association of Australia2025
Energy and protein intake threshold modelling using nutrition dashboard technology and sensitivity of hospital malnutrition identification.
Observational study in Nutrition & dietetics : the journal of the Dietitians Association of Australia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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
3 citing papers in PubMed.
- A critical realist exploration of hospital staff experiences of using nutrition dashboard technology.BMC health services research · 2026Article
- Addressing Malnutrition in Australian Hospitals: A Scoping Review to Inform Systems Thinking.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2026Article
- Energy and protein intake threshold modelling using nutrition dashboard technology and sensitivity of hospital malnutrition identification.Nutrition & dietetics : the journal of the Dietitians Association of Australia · 2025Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
aimsHospital food provision/intake dashboards may improve malnutrition screening. The aim of this study was to use Nutrition Dashboard data to determine the optimal threshold for screening for malnutrition risk, and compare the accuracy of this method with estimated dietary requirements.
methodsObservational data were extracted from medical files and food service records of 267 patients for a 4-month period in a 99-bed hospital. Energy (2500-8000 kJ) and protein (30-90 g) thresholds were applied for Nutrition Dashboard categorisation by supply and intake of food. Deficits in estimated requirements (105 kJ/kg/day and 0.75 g/kg/day) were also applied as a comparative method. The association between Nutrition Dashboard categories and the Malnutrition Screening Tool was explored using generalised estimating equations.
resultsA total of 267 patients and 1908 days of data were analysed. The use of estimated requirements for Nutrition Dashboard categorisation was not a statistically significant predictor of malnutrition risk. Application of energy (≤6000 kJ) and protein (≤65 g) thresholds for categorisation was significant (χ
conclusionsNutrition Dashboard categories are associated with an increased risk of malnutrition when categorised using thresholds of up to 6000 kJ and 65 g protein. Technologies like the Nutrition Dashboard present innovative opportunities for dietitians to utilise nutrition informatics to enhance and optimise nutrition care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.