Variability Of Morning Urine Specific Gravity (Usg) Measurements And Effects Of Fluid Intake On Midafternoon Usg
Bibliographic record
Abstract
The measurement of urine specific gravity (USG) has been shown to be a good indicator of hydration status. USG measurements are often used to assess the hydration status of athletes prior to training and competitions and the effectiveness of pre-event fluid intake. PURPOSE: This study assessed the day to day variability of morning USG measures and the USG responses to fluid ingestion in the afternoon. METHODS: Ten recreational athletes (3 males, 7 females, 79.2 + 4.4 kg, 26.9 + 0.9 yrs) volunteered to monitor their morning body mass (kg) and hydration status (USG) for five consecutive weekdays. On two occasions, separated by 48 hrs, participants arrived at the laboratory in mid-afternoon following ad libitum drinking during the day. They drank 300 ml of water at time (t) = 0 min and an additional 300 ml at t = 15 min. Body mass, urine volume and USG were recorded before fluid intake at t = 0 and following fluid intake at t = 30, 45 and 60 min RESULTS: Mean daily USG over the 5 consecutive days was 1.017 + 0.002. The variability of morning Usg (CV = 0.17 %) and body mass (CV = 0.27 %). Subjects consumed an average of 600 + 121 ml of fluid ad libitum in the 3 hrs prior to each trial. Subjects arrived at the laboratory mid-afternoon and were well hydrated (mean USG 1.012 + 0.002) and after drinking 600 ml of fluid, USG decreased to 1.008 + 0.003, 1.004 + 0.002, and 1.003 + 0.001 at 30, 45, and 60 min. The results from the second afternoon trial produced mean Usg data that was identical to the first afternoon trial. Repeatability was consistent between trials. Pre-trial fluid intake was negatively correlated with pre-trial Usg (r = 0.54). CONCLUSIONS: This study demonstrated that morning Usg and body mass measurements are consistent between days. The ingestion of 600 ml of fluid midafternoon, following a day of ad libitum drinking, significantly decreases urine Usg.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".