• Marinos Elia, Abbie L Cawood, Tahir Akbar, and Trevor Smith.
• Faculty of Medicine, University Hospital Southampton NHS Foundation Trust, Southampton, UK. Electronic address: Elia@soton.ac.uk.
• Nutrition. 2019 Nov 1; 67-68: 110529.

ObjectiveSince nutritional screening is not routinely and accurately performed by busy care workers, the aim of this study was to evaluate a self-screening electronic measuring station that includes sonic height measurements.MethodsIn all, 114 patients, 18 to 85 y of age and attending gastrointestinal outpatient clinics, followed automatically triggered audio-recorded instructions for weight and height measurements. The patients also provided information about unintentional weight loss to establish malnutrition risk using the Malnutrition Universal Screening Tool (MUST). In 56 healthy individuals, the effect of head/foot positions on height was examined using video-recordings. Laboratory studies examined the effects of hair/wigs, the position of a skull and horizontal plates and ambient conditions. Measurements were also made on a mechanical machine for comparison.ResultsOf the patients, 21.9% were malnourished, with 99% agreement between sonic and mechanical machine categorization. Patients self-screened in only 35.6 ± 14.8 s (median 32 s) and 77% rated the screening as very easy (22%, easy), despite encountering some remediable snags. Within-subject precision for height was 0.186 cm in healthy individuals and 0.368 cm in patients. Humidity and barometric pressure had negligible/undetectable effects on height measurements, but temperature corrections were confounded by calibration errors. In the most lateral standing positions, height was underestimated curvilinearly. In healthy individuals, height measurements were 0.353 ± 0.542 cm lower on the sonic than mechanical device, which was inadequately explained by standing position or body tilt, although hair was found to be "invisible" only to the sonic machine.ConclusionA method has been developed to rapidly and reliably self-screen for malnutrition using MUST, avoiding calculation and categorization errors, while providing results that can be immediately printed or transmitted electronically into patient notes.Crown Copyright © 2019. Published by Elsevier Inc. All rights reserved.

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