Diagnostic Accuracy of Urine Color to Detect ≥2% Body Mass Loss

2015 ◽  
Vol 47 ◽  
pp. 655-656
Author(s):  
Amy L. McKenzie ◽  
Colleen X. Muñoz ◽  
Lawrence E. Armstrong
Keyword(s):  
Diagnostic Accuracy ◽  
Mass Loss ◽  
Body Mass ◽  
Body Mass Loss ◽  
Urine Color

scholarly journals Accuracy of Urine Color to Detect Equal to or Greater Than 2% Body Mass Loss in Men

2015 ◽  
Vol 50 (12) ◽  
pp. 1306-1309 ◽  
Author(s):  
Amy L. McKenzie ◽  
Colleen X. Muñoz ◽  
Lawrence E. Armstrong
Keyword(s):  
Mass Loss ◽  
Likelihood Ratio ◽  
Body Mass ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Hydration Status ◽  
Body Mass Loss ◽  
Diagnostic Efficacy ◽  
Hot Environment ◽  
Urine Color

Context  Clinicians and athletes can benefit from field-expedient measurement tools, such as urine color, to assess hydration state; however, the diagnostic efficacy of this tool has not been established. Objective  To determine the diagnostic accuracy of urine color assessment to distinguish a hypohydrated state (≥2% body mass loss [BML]) from a euhydrated state (<2% BML) after exercise in a hot environment. Design  Controlled laboratory study. Setting  Environmental chamber in a laboratory. Patients or Other Participants  Twenty-two healthy men (age = 22 ± 3 years, height = 180.4 ± 8.7 cm, mass = 77.9 ± 12.8 kg, body fat = 10.6% ± 4.6%). Intervention(s)  Participants cycled at 68% ± 6% of their maximal heart rates in a hot environment (36°C ± 1°C) for 5 hours or until 5% BML was achieved. At the point of each 1% BML, we assessed urine color. Main Outcome Measure(s)  Diagnostic efficacy of urine color was assessed using receiver operating characteristic curve analysis, sensitivity, specificity, and likelihood ratios. Results  Urine color was useful as a diagnostic tool to identify hypohydration after exercise in the heat (area under the curve = 0.951, standard error = 0.022; P < .001). A urine color of 5 or greater identified BML ≥2% with 88.9% sensitivity and 84.8% specificity (positive likelihood ratio = 5.87, negative likelihood ratio = 0.13). Conclusions  Under the conditions of acute dehydration due to exercise in a hot environment, urine color assessment can be a valid, practical, inexpensive tool for assessing hydration status. Researchers should examine the utility of urine color to identify a hypohydrated state under different BML conditions.

Relationships Between WUT (Body Weight, Urine Color, and Thirst Level) Criteria and Urine Indices of Hydration Status

2021 ◽  
pp. 194173812110384
Author(s):  
Yasuki Sekiguchi ◽  
Courteney L. Benjamin ◽  
Cody R. Butler ◽  
Margaret C. Morrissey ◽  
Erica M. Filep ◽  
...  
Keyword(s):  
Specific Gravity ◽  
Mass Loss ◽  
Body Mass ◽  
Urine Osmolality ◽  
Urine Specific Gravity ◽  
Venn Diagram ◽  
Hydration Status ◽  
Body Mass Loss ◽  
Living Situation ◽  
Urine Color

Background: A Venn diagram consisting of percentage body mass loss, urine color, and thirst perception (weight, urine, thirst [WUT]) has been suggested as a practical method to assess hydration status. However, no study to date has examined relationships between WUT and urine hydration indices. Thus, the purpose of this study was to investigate relationships between urine specific gravity, urine osmolality, and the WUT criteria. Hypothesis: Urine specific gravity and urine osmolality indicate hypohydration when the WUT criteria demonstrate hypohydration (≥2 markers). Study Design: Laboratory cohort study. Level of Evidence: Level 3. Methods: A total of 22 women (mean ± SD; age, 20 ± 1 years; mass, 65.4 ± 12.6 kg) and 21 men (age, 21 ± 1 years; body mass, 78.7 ± 14.6 kg) participated in this study. First morning body mass, urine color, urine specific gravity, urine osmolality, and thirst level were collected for 10 consecutive days in a free-living situation. Body mass loss >1%, urine color >5, and thirst level ≥5 were used as the dehydration thresholds. The number of markers that indicated dehydration levels were counted and categorized into either 3, 2, 1, or 0 WUT markers that indicated dehydration. One-way analysis of variance with Tukey pairwise comparisons was used to assess the differences in urine specific gravity and urine osmolality between the different number of WUT markers. Results: Urine specific gravity in 3 WUT markers (mean ± SD [effect size], 1.021 ± 0.007 [0.57]; P = 0.025) and 2 WUT markers (1.019 ± 0.010 [0.31]; P = 0.026) was significantly higher than 1 WUT marker (1.016 ± 0.009). Urine mosmolality in 2 WUT markers (705 ± 253 mOsmol [0.43]; P = 0.018) was significantly higher than 1 WUT (597 ± 253 mOsmol). Meeting at least 2 WUT markers resulted in sensitivities of 0.652 (2 WUT criteria met) and 0.933 (3 WUT criteria met) to detect urine osmolality >700 mOsmol. Conclusion: These results suggest that when 3 WUT markers are met, urine specific gravity and urine osmolality were greater than euhydration cutoff points. The WUT criterion is a useful tool to use in field settings to assess hydration status when first morning urine sample was used. Clinical Relevance: Athletes, coaches, sports scientists, and medical professionals can use WUT criteria to monitor dehydration with reduced cost and time.

23 Nutritional Intake and Weight Change in Severely Burned Patients

2021 ◽  
Vol 42 (Supplement_1) ◽  
pp. S20-S21
Author(s):  
Sandrine O Fossati ◽  
Beth A Shields ◽  
Renee E Cole ◽  
Adam J Kieffer ◽  
Saul J Vega ◽  
...  
Keyword(s):  
Wound Healing ◽  
Mass Loss ◽  
Performance Improvement ◽  
Body Mass ◽  
Total Body Surface Area ◽  
Nutritional Intake ◽  
Energy Deficit ◽  
Body Mass Loss ◽  
Improvement Project ◽  
Burn Care

Abstract Introduction Nutrition is crucial for recovery from burn injuries, as severe weight (wt.) loss can lead to impaired immunity and wound healing, infections, skin graft failure, and mortality. Previous studies recommended avoiding more than 10% wt. loss, as this level resulted in increased infection rates. However, wt. loss is often not quantifiable during the critical illness phase, with severe edema masking non-fluid related body wt. changes. Energy (kcal) deficits can be used to estimate wt. loss until the edema has resolved, but previous studies in non-burn patients indicate that actual wt. loss is less than the commonly used 3500 kcal per pound of fat (7700 kcal per kg of fat). The objective of this performance improvement project was to evaluate nutritional intake and the resulting dry wt. change in severely burned patients. Methods This performance improvement project was approved by our regulatory compliance division. We performed a retrospective evaluation on patients with at least 20% total body surface area (TBSA) burns admitted for initial burn care to our intensive care unit over a 7-year period. Patients who died or who had major fascial excisions or limb amputations were excluded. Patients who did not achieve a recorded dry wt. after wound healing were not included in this analysis. Retrospective data were collected, including sex, age, burn size, kcal intake, kcal goal per the Milner equation using activity factor of 1.4, admission dry wt., dry wt. after wound healing (defined as less than 10% TBSA open wound), and days to dry wt. after wound healing. Descriptive statistics and linear regression were performed using JMP. Significance was set at p< 0.05. Results The 30 included patients had the following characteristics: 90% male, 30 ± 11 years old, 45% ± 15% TBSA burn. They received 2720 ± 1092 kcal/day, meeting 68% ± 24% kcal goal, and took approximately 53 ± 30 days from injury to achieve dry wt. after wound healing. These patients had wt. loss of 8 ± 8 kg from the kcal deficit of 69,819 ± 51,704 during this time period. The kcal deficit was significantly associated with wt. change [p < 0.001, R2 = 0.49, wt. change in kg = (-0.000103 x kcal deficit) – 1]. This translates to one kg of body wt. loss resulting from 9709 kcal deficit. Conclusions This performance improvement project found that an energy deficit of approximately 9700 kcal in our patients equates to 1 kg of body mass loss (4400 kcal deficit equates to 1 pound of body mass loss). These findings are similar to wt. loss studies in other patient populations and contrary to the commonly used 3500 kcal per pound of fat (7700 kcal per kg of fat).

scholarly journals Simulated model of obesity and immediate metabolic disorders after gastric shunting with anastomosis in small laboratory animals

2020 ◽  
Vol 87 (9-10) ◽  
pp. 84-88
Author(s):  
R. I. Vynogradov ◽  
O. S. Tyvonchuk ◽  
K. O. Nadiein ◽  
V. V. Moskalenko
Keyword(s):  
Small Intestine ◽  
Mass Loss ◽  
Body Mass ◽  
Metabolic Disorders ◽  
Metabolic Changes ◽  
Experimental Simulation ◽  
Body Mass Loss ◽  
Simulated Model ◽  
Group I ◽  
Group Ii

Objective. To study metabolic changes and peculiarities of mineral balance depending on the common loop length while constructing of the simulated model of gastric shunting with one anastomosis during 60 days. Materials and methods. Experimental simulation of gastric minishunting with one anastomosis of various length of bilio-pancreatic loop was constructed on the rats. In 10 rats the anastomosis was formatted on level of half of total length of small intestine (Group I), and also in 10 - a third part of general length of small intestine (Group II). Control Group consisted of 5 rats. The indices of the extra body mass loss and metabolic changes were compared. Results. In the rats of Group I the index of the body mass loss have constituted 16.6% (41.7 gm), and of the Group II -20.6% (53.2 gm). Lowering of indices of mineral and prion metabolism, comparing preoperative values, was observed in both Groups. Dystrophic changes in osseous tissue of vertebral bodies of lumbar vertebral column were noted in animals of both Groups, more pronounced - in Group II. Conclusion. The protein and mineral metabolism disorders may be observed not only in large resection volume, but in exclusion of half and more segment of small bowel from general transit, using gastric shunting, what lacks significant advantages in the extra body mass loss, but leads to more profound metabolic disorders.

Deviation from goal pace, body temperature and body mass loss as predictors of road race performance

2017 ◽  
Vol 20 (3) ◽  
pp. 302-306 ◽  
Author(s):  
William M. Adams ◽  
Yuri Hosokawa ◽  
Luke N. Belval ◽  
Robert A. Huggins ◽  
Rebecca L. Stearns ◽  
...  
Keyword(s):  
Body Temperature ◽  
Mass Loss ◽  
Body Mass ◽  
Body Mass Loss ◽  
Road Race ◽  
Race Performance
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