BACKGROUND: Dehydration is a common medical problem requiring heuristic evaluation. Our aim was to develop a quantitative and graphical tool based on serial changes in either plasma osmolality (P(osm)), urine specific gravity (U(sg)), or body mass (B(m)) to aid in determining the probability that a person has become dehydrated. A secondary purpose was to validate use of the tool by dehydrating a group of volunteers. METHODS: Basic data were obtained from a recent study of biological variation in common hydration status markers. Four reference change values (RCV) were calculated for each variable (P(osm), U(sg), B(m)) using four statistical probabilities (0.80, 0.90, 0.95, and 0.99). The probability derived from the Z-score for any given change can be calculated from: Z=change/[2(1/2)(CV(a)(2)+CV(i)(2))(1/2)]. This calculation was simplified to require one input (measured change) by plotting the RCV against probability to generate both an empirical equation and a dual quantitative-qualitative graphic. RESULTS: Eleven volunteers were dehydrated by moderate levels (-2.1% to -3.5% B(m)). Actual probabilities were obtained by substituting measured changes in P(osm), U(sg), and B(m) for X in the exponential equation, Y=1-e(-K·X), where each variable has a unique K constant. Median probabilities were 0.98 (P(osm)), 0.97 (U(sg)), and 0.97 (B(m)), which aligned with 'very likely' to 'virtually certain' qualitative probability categories for dehydration. CONCLUSIONS: This investigation provides a simple quantitative and graphical tool that can aid in determining the probability that a person has become dehydrated when serial measures of P(osm), U(sg), or B(m) are made.
BACKGROUND:Dehydration is a common medical problem requiring heuristic evaluation. Our aim was to develop a quantitative and graphical tool based on serial changes in either plasma osmolality (P(osm)), urine specific gravity (U(sg)), or body mass (B(m)) to aid in determining the probability that a person has become dehydrated. A secondary purpose was to validate use of the tool by dehydrating a group of volunteers. METHODS: Basic data were obtained from a recent study of biological variation in common hydration status markers. Four reference change values (RCV) were calculated for each variable (P(osm), U(sg), B(m)) using four statistical probabilities (0.80, 0.90, 0.95, and 0.99). The probability derived from the Z-score for any given change can be calculated from: Z=change/[2(1/2)(CV(a)(2)+CV(i)(2))(1/2)]. This calculation was simplified to require one input (measured change) by plotting the RCV against probability to generate both an empirical equation and a dual quantitative-qualitative graphic. RESULTS: Eleven volunteers were dehydrated by moderate levels (-2.1% to -3.5% B(m)). Actual probabilities were obtained by substituting measured changes in P(osm), U(sg), and B(m) for X in the exponential equation, Y=1-e(-K·X), where each variable has a unique K constant. Median probabilities were 0.98 (P(osm)), 0.97 (U(sg)), and 0.97 (B(m)), which aligned with 'very likely' to 'virtually certain' qualitative probability categories for dehydration. CONCLUSIONS: This investigation provides a simple quantitative and graphical tool that can aid in determining the probability that a person has become dehydrated when serial measures of P(osm), U(sg), or B(m) are made.
Authors: Samuel N Cheuvront; Brett R Ely; Robert W Kenefick; Mark J Buller; Nisha Charkoudian; Michael N Sawka Journal: Eur J Appl Physiol Date: 2012-04-06 Impact factor: 3.078
Authors: Erica T Perrier; Inmaculada Buendia-Jimenez; Mariacristina Vecchio; Lawrence E Armstrong; Ivan Tack; Alexis Klein Journal: Dis Markers Date: 2015-03-18 Impact factor: 3.434
Authors: Olga Malisova; Adelais Athanasatou; Alex Pepa; Marlien Husemann; Kirsten Domnik; Hans Braun; Ricardo Mora-Rodriguez; Juan F Ortega; Valentin E Fernandez-Elias; Maria Kapsokefalou Journal: Nutrients Date: 2016-04-06 Impact factor: 5.717
Authors: E Perrier; P Rondeau; M Poupin; L Le Bellego; L E Armstrong; F Lang; J Stookey; I Tack; S Vergne; A Klein Journal: Eur J Clin Nutr Date: 2013-05-22 Impact factor: 4.016