Brett R. Ely

Biological variation and diagnostic accuracy of dehydration assessment markers

BACKGROUND Well-recognized markers for static (one time) or dynamic (monitoring over time) dehydration assessment have not been rigorously tested for their usefulness in clinical, military, and sports medicine communities. OBJECTIVE This study evaluated the components of biological variation and the accuracy of potential markers in plasma, urine, saliva, and body mass (B(m)) for static and dynamic dehydration assessment. DESIGN We studied 18 healthy volunteers (13 men and 5 women) while carefully controlling hydration and numerous preanalytic factors. Biological variation was determined over 3 consecutive days by using published methods. Atypical values based on statistical deviations from a homeostatic set point were examined. Measured deviations in body fluid were produced by using a separate, prospective dehydration experiment and evaluated by receiver operating characteristic (ROC) analysis to quantify diagnostic accuracy. RESULTS All dehydration markers displayed substantial individuality and one-half of the dehydration markers displayed marked heterogeneity of intraindividual variation. Decision levels for all dehydration markers were within one SD of the ROC criterion values, and most levels were nearly identical to the prospective group means after volunteers were dehydrated by 1.8-7.0% of B(m). However, only plasma osmolality (P(osm)) showed statistical promise for use in the static dehydration assessment. A diagnostic decision level of 301 plusmn 5 mmol/kg was proposed. Reference change values of 9 mmol/kg (P(osm)), 0.010 [urine specific gravity (U(sg))], and 2.5% change in B(m) were also statistically valid for dynamic dehydration assessment at the 95% probability level. CONCLUSIONS P(osm) is the only useful marker for static dehydration assessment. P(osm), U(sg), and B(m) are valid markers in the setting of dynamic dehydration assessment.

Skin temperature modifies the impact of hypohydration on aerobic performance.

This study determined the effects of hypohydration on aerobic performance in compensable [evaporative cooling requirement (E(req)) < maximal evaporative cooling (E(max))] conditions of 10 degrees C [7 degrees C wet bulb globe temperature (WBGT)], 20 degrees C (16 degrees C WBGT), 30 degrees C (22 degrees C WBGT), and 40 degrees C (27 degrees C WBGT) ambient temperature (T(a)). Our hypothesis was that 4% hypohydration would impair aerobic performance to a greater extent with increasing heat stress. Thirty-two men [22 +/- 4 yr old, 45 +/- 8 ml.kg(-1).min(-1) peak O(2) uptake (Vo(2 peak))] were divided into four matched cohorts (n = 8) and tested at one of four T(a) in euhydrated (EU) and hypohydrated (HYPO, -4% body mass) conditions. Subjects completed 30 min of preload exercise (cycle ergometer, 50% Vo(2 peak)) followed by a 15 min self-paced time trial. Time-trial performance (total work, change from EU) was -3% (P = 0.1), -5% (P = 0.06), -12% (P < 0.05), and -23% (P < 0.05) in 10 degrees C, 20 degrees C, 30 degrees C, and 40 degrees C T(a), respectively. During preload exercise, skin temperature (T(sk)) increased by approximately 4 degrees C per 10 degrees C T(a), while core (rectal) temperature (T(re)) values were similar within EU and HYPO conditions across all T(a). A significant relationship (P < 0.05, r = 0.61) was found between T(sk) and the percent decrement in time-trial performance. During preload exercise, hypohydration generally blunted the increases in cardiac output and blood pressure while reducing blood volume over time in 30 degrees C and 40 degrees C T(a). Our conclusions are as follows: 1) hypohydration degrades aerobic performance to a greater extent with increasing heat stress; 2) when T(sk) is >29 degrees C, 4% hypohydration degrades aerobic performance by approximately 1.6% for each additional 1 degrees C T(sk); and 3) cardiovascular strain from high skin blood flow requirements combined with blood volume reductions induced by hypohydration is an important contributor to impaired performance.

Aerobic Performance Is Degraded, Despite Modest Hyperthermia, in Hot Environments

UNLABELLED Environmental heat stress degrades aerobic performance; however, little research has focused on performance when the selected task elicits modest elevations in core body temperature (<38.5 degrees C). PURPOSE To determine the effect of environmental heat stress, with modest hyperthermia, on aerobic performance and pacing strategies. METHODS After a 30-min cycling preload at 50% VO2peak, eight euhydrated men performed a 15-min time trial on a cycle ergometer in temperate (TEMP; 21 degrees C, 50% RH) and hot (HOT; 40 degrees C, 25% RH) environments. Core and skin temperature (Tc and Tsk, respectively) and HR were continuously monitored. Performance was assessed by the total work (kJ) completed in 15 min. Pacing was quantified by comparing the percent difference in actual work performed in each of five 3-min blocks normalized to the mean work performed per 3-min block. Pace over the final 2 min was compared with the average pace from minutes 0 to 13 for end spurt analysis. RESULTS Tc and HR rose continually throughout both time trials. Peak Tc remained modestly elevated in both environments [mean (range): HOT = 38.20 degrees C (37.97-38.42 degrees C); TEMP = 38.11 degrees C (38.07-38.24 degrees C)], whereas Tsk was higher in HOT (36.19 +/- 0.40 degrees C vs 31.14 +/- 1.14 degrees C), and final HR reached approximately 95% of age-predicted maximum in both environments. Total work performed in HOT (147.7 +/- 23.9 kJ) was approximately 17% less (P < 0.05) than TEMP (177.0 +/- 25.0 kJ). Pace was evenly maintained in TEMP, but in HOT, volunteers were unable to maintain initial pace, slowing progressively over time. A significant end spurt was produced in both environments. CONCLUSIONS During a brief aerobic exercise time trial where excessive hyperthermia is avoided, total work is significantly reduced by heat stress because of a gradual slowing of pace over time. These findings demonstrate how aerobic exercise performance degrades in hot environments without marked hyperthermia.

A simple and valid method to determine thermoregulatory sweating threshold and sensitivity

Sweating threshold temperature and sweating sensitivity responses are measured to evaluate thermoregulatory control. However, analytic approaches vary, and no standardized methodology has been validated. This study validated a simple and standardized method, segmented linear regression (SReg), for determination of sweating threshold temperature and sensitivity. Archived data were extracted for analysis from studies in which local arm sweat rate (m(sw); ventilated dew-point temperature sensor) and esophageal temperature (T(es)) were measured under a variety of conditions. The relationship m(sw)/T(es) from 16 experiments was analyzed by seven experienced raters (Rater), using a variety of empirical methods, and compared against SReg for the determination of sweating threshold temperature and sweating sensitivity values. Individual interrater differences (n = 324 comparisons) and differences between Rater and SReg (n = 110 comparisons) were evaluated within the context of biologically important limits of magnitude (LOM) via a modified Bland-Altman approach. The average Rater and SReg outputs for threshold temperature and sensitivity were compared (n = 16) using inferential statistics. Rater employed a very diverse set of criteria to determine the sweating threshold temperature and sweating sensitivity for the 16 data sets, but interrater differences were within the LOM for 95% (threshold) and 73% (sensitivity) of observations, respectively. Differences between mean Rater and SReg were within the LOM 90% (threshold) and 83% (sensitivity) of the time, respectively. Rater and SReg were not different by conventional t-test (P > 0.05). SReg provides a simple, valid, and standardized way to determine sweating threshold temperature and sweating sensitivity values for thermoregulatory studies.

No effect of nutritional adenosine receptor antagonists on exercise performance in the heat

Nutritional adenosine receptor antagonists can enhance endurance exercise performance in temperate environments, but their efficacy during heat stress is not well understood. This double-blinded, placebo-controlled study compared the effects of an acute dose of caffeine or quercetin on endurance exercise performance during compensable heat stress (40 degrees C, 20-30% rh). On each of three occasions, 10 healthy men each performed 30-min of cycle ergometry at 50% Vo2peak followed by a 15-min performance time trial after receiving either placebo (Group P), caffeine (Group C; 9 mg/kg), or quercetin (Group Q; 2,000 mg). Serial blood samples, physiological (heart rate, rectal, and mean skin body temperatures), perceptual (ratings of perceived exertion, pain, thermal comfort, motivation), and exercise performance measures (total work and pacing strategy) were made. Supplementation with caffeine and quercetin increased preexercise blood concentrations of caffeine (55.62 +/- 4.77 microM) and quercetin (4.76 +/- 2.56 microM) above their in vitro inhibition constants for adenosine receptors. No treatment effects were observed for any physiological or perceptual measures, with the exception of elevated rectal body temperatures (0.20-0.30 degrees C; P < 0.05) for Group C vs. Groups Q and P. Supplementation did not affect total work performed (Groups P: 153.5 +/- 28.3, C: 157.3 +/- 28.9, and Q: 151.1 +/- 31.6 kJ; P > 0.05) or the self-selected pacing strategy employed. These findings indicate that the nutritional adenosine receptor antagonists caffeine and quercetin do not enhance endurance exercise performance during compensable heat stress.

Reference change values for monitoring dehydration.

Abstract 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 (Posm), urine specific gravity (Usg), or body mass (Bm) 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 (Posm, Usg, Bm) 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/[21/2(CVa2+CVi2)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% Bm). Actual probabilities were obtained by substituting measured changes in Posm, Usg, and Bm for X in the exponential equation, Y=1–e–K·X, where each variable has a unique K constant. Median probabilities were 0.98 (Posm), 0.97 (Usg), and 0.97 (Bm), 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 Posm, Usg, or Bm are made.

Prior Heat Stress: Effect on Subsequent 15-min Time Trial Performance in the Heat

UNLABELLED The impact of prior heat stress on subsequent aerobic exercise-heat performance has not been studied. PURPOSE To determine whether prior heat stress degrades subsequent aerobic exercise performance in the heat. METHODS Eighteen nonheat acclimated males were trained (four practice trials) on an aerobic exercise performance test in 22 degrees C and then divided into two (n = 8) groups. One group (EUHPH; (.)VO2peak = 44 +/- 7 mL x kg x min(-1)) was tested after 90 min of recovery (in 22 degrees C) from 3 h of intermittent light-intensity (<30% (.)VO2peak) exercise-heat (50 degrees C) stress, where sweat losses were matched with fluid intake (3.5 +/- 0.5 L) to maintain euhydration. The other group (EUH; (.)VO2peak = 45 +/- 5 mL x kg x min(-1)) was tested while euhydrated without prior exercise-heat stress. Aerobic performance was determined from a 30-min cycling preload (50% (.)VO2peak) followed by a 15-min time trial in 40 degrees C. Total work during the 15-min performance time trial in EUH and EUHPH was compared, as were the percent changes from the best practice trials. RESULTS Volunteers were euhydrated (plasma osmolality < 290 mOsm x kg(-1)) and normothermic before each exercise-heat trial. Heart rate and core temperature were not different (P > 0.05) between groups at any time point during exercise. Total work was not different (P > 0.05) at baseline or between EUH (150.5 +/- 28.3 kJ; 2.0 +/- 0.3 kJ x kg(-1)) and EUHPH (160.3 +/- 24.0 kJ; 1.8 +/- 0.2 kJ x kg(-1)). The percent change in total work relative to baseline was not different (P > 0.05) between EUH (-18.7% +/- 9.2%) and EUHPH (-15.0% +/- 7.8%). CONCLUSIONS If hydration and body temperatures recover, prior exercise-heat stress does not result in a greater degradation in aerobic time trial performance in the heat compared with heat exposure alone.

Limitations of Salivary Osmolality as a Marker of Hydration Status

UNLABELLED Salivary osmolality (Sosm) is a potentially useful hydration marker but may be confounded by oral artifacts. PURPOSE This study aimed to determine the efficacy of Sosm for detecting hypohydration and evaluate the effect of a simple mouth rinse. METHODS Eight healthy volunteers (six males and two females; age = 22 ± 7 yr, body mass = 83.7 ± 14.9 kg, height = 176.9 ± 9.2 cm) were measured for nude body mass (BM), plasma osmolality (Posm), and Sosm when euhydrated (EUH) and again when hypohydrated (HYP) by exercise-heat exposure with fluid restriction. After the initial saliva sample during HYP, a 10-s mouth rinse with 50 mL of water was provided, and saliva samples were obtained 1 min (RIN01), 15 min (RIN15), and 30 min (RIN30) after rinse. The ability of Sosm to detect HYP was compared with Posm. RESULTS Volunteers were hypohydrated by -4.0% ± 1.2% of BM (range = -2.2% to -5.3%). Sosm was elevated above EUH after hypohydration (EUH 58 ± 8 mmol · kg vs HYP 96 ± 28 mmol · kg, P < 0.05). Sosm baseline and change values displayed more variability than Posm based on ANOVA and regression analyses. After the oral rinse, saliva decreased in concentration (RIN01 = 61 ± 17 mmol · kg, P < 0.05) but returned to prerinse values within 15 min (RIN15 = 101 ± 25 mmol · kg) and remained similar 30 min after (RIN30 = 103 ± 33 mmol · kg). CONCLUSIONS Sosm was remarkably altered 1 min after a brief water mouth rinse. Fifteen minutes proved an adequate recovery time, indicating that the timing of oral artifacts and saliva sample collection is critical when considering Sosm for hydration assessment. Given the inherent variability and profound effect of oral intake, use of Sosm as a marker of hydration status is dubious.

Serum S-100β Response to Exercise-Heat Strain before and after Acclimation

UNLABELLED Exercise alone or in combination with environmental heat stress can elevate blood S-100beta protein concentrations. However, the explanatory power of exercise with marked environmental heat stress on the appearance of S-100beta is questionable. It is possible that the process of heat acclimation might afford additional insight. PURPOSE Determine the S-100beta response to moderate-intensity exercise with heat strain before and after heat acclimation. METHODS Nine healthy male volunteers completed 10 consecutive days of heat acclimation consisting of up to 100 min of treadmill walking (1.56 m x s(-1), 4% grade) in the heat (45 degrees C, 20% relative humidity). Changes in HR, rectal temperature (T(re)), and sweat rate (SR) were examined to determine successful acclimation. Area under the curve (AUC) for T(re) greater than 38.5 degrees C was calculated to assess cumulative hyperthermia. Blood samples were taken before and after exercise on days 1 and 10 and were analyzed for serum osmolality and S-100beta concentration. RESULTS All subjects displayed physiological adaptations to heat acclimation including a significant (P < 0.05) reduction in final HR (161 to 145 bpm) and T(re) (39.0 to 38.4 degrees C), as well as a modest (approximately 10%) increase in SR (1.10 to 1.20 L x h(-1); P = 0.09). No differences were observed in pre- to postexercise serum S-100beta concentrations on day 1 or 10, and no differences were observed in S-100beta values between days 1 and 10. No significant correlations were found between S-100beta values and any variable of interest. CONCLUSIONS S-100beta concentrations do not necessarily increase in response to exercise-heat strain, and no effect of heat acclimation on S-100beta could be observed despite other quantifiable physiological adaptations.

Water-deficit equation: systematic analysis and improvement

BACKGROUND The water-deficit equation {WD(1) = 0.6 × B(m) × [1 - (140 ÷ Na(+))]; B(m) denotes body mass} is used in medicine and nutrition to estimate the volume (L) of water required to correct dehydration during the initial stages of fluid-replacement therapy. Several equation assumptions may limit its accuracy, but none have been systematically tested. OBJECTIVES We quantified the potential error in WD(1) for the estimation of free water (FW) and total body water (TBW) losses and systematically evaluated its assumptions. DESIGN Thirty-six euhydrated volunteers were dehydrated (2.2-5.8% B(m)) via thermoregulatory sweating. Assumptions within WD(1) were tested by substituting measured euhydrated values for assumed or unknown values. These included the known (premorbid) B(m) (WD(2)), a proposed correction for unknown B(m) (WD(3)), the TBW estimated from body composition (WD(4)), the actual plasma sodium (WD(5)), the substitution of plasma osmolality (Posm) for sodium (WD(6)), and actual Posm (WD(7)). RESULTS Dehydration reduced TBW by 3.49 ± 0.91 L, 57% of which (2.02 ± 0.96 L) was FW loss, and increased plasma sodium from 139 (range: 135-143 mmol/L) to 143 (range: 141-148 mmol/L) mmol/L. Calculations for WD(1) through WD(7) all underestimated TBW loss by 1.5-2.5 L (P < 0.05). WD(1) through WD(5) underestimated FW by 0.5 L to 1.0 L (P < 0.05), but WD(6) and WD(7) estimated FW loss to within 0.06-0.16 L (P > 0.05). CONCLUSIONS WD(1) grossly underestimates TBW and FW losses. Corrections for unknowns and assumptions (WD(2) through WD(5)) improved estimates little. The use of WD(6) = 0.6 × B(m) × [1 - (290 ÷ Posm)] accurately estimates FW but still underestimates TBW losses by >40%.