Evidence map›Paper›PMID 36723707›Full record

ArticleEuropean journal of nutrition2023

Comparison between digital and paper urine color to assess hydration status.

Yasuki Sekiguchi, David G Martin, Ayami Yoshihara, Douglas J Casa

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Article in European journal of nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

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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

4 authors.

Yasuki SekiguchiDepartment of Kinesiology, Korey Stringer Institute, University of Connecticut, 2095 Hillside Road U-1110, Storrs, CT, 06269, USA. yasuki.sekiguchi@ttu.edu.ORCID http://orcid.org/0000-0002-2972-8738
David G MartinDepartment of Kinesiology, Korey Stringer Institute, University of Connecticut, 2095 Hillside Road U-1110, Storrs, CT, 06269, USA.
Ayami YoshiharaDepartment of Kinesiology, Korey Stringer Institute, University of Connecticut, 2095 Hillside Road U-1110, Storrs, CT, 06269, USA.
Douglas J CasaDepartment of Kinesiology, Korey Stringer Institute, University of Connecticut, 2095 Hillside Road U-1110, Storrs, CT, 06269, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purpose of this study was to investigate associations between digital urine color and paper urine color with other urine indices to assess hydration status.

methodsTwelve male subjects (mean ± standard deviation; age, 26 ± 8 years; body mass, 57.8 ± 5.3 kg; height, 177.5 ± 8.9 cm; VO

resultsThere were extremely large associations found between digital urine color and paper urine color (r = 0.926, p < 0.001). Correlation coefficients showing associations with USG and UOsmo were similar between digital urine color (USG, r = 0.695, p < 0.001; UOsmo, r = 0.555, p < 0.001) and paper urine color (USG, r = 0.713, p < 0.001; UOsmo, r = 0.570, p < 0.001). Bland-Altman analysis indicated that no proportional bias was observed between digital and paper urine colors (bias, - 0.148; SD of bias, 0.492; 95% LOA, - 1.11, 0.817; p = 0.094).

conclusionsStrong associations were found between digital and paper urine colors with no proportional bias. Furthermore, the degree of associations with USG and UOsmo was similar between digital and paper urine color. These results indicate that digital urine color is a useful tool to assess hydration status and this method could be used as an alternative method to using paper urine color.

Indexed as

DehydrationUrinalysisAdolescentAdultBiomarkersColorHot TemperatureHumansMaleOsmolar ConcentrationSpecific GravityUrineYoung AdultBiomarkersAssessmentDehydrationHydrationUrine

Identifiers

PMID36723707

What OpenQuestion holds

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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.