Creatinine and Specific Gravity Normalization in Biological Monitoring of Occupational Exposures
Bibliographic record
Abstract
Reference values for the biological monitoring of occupational exposures are generally normalized on the basis of creatinine (CR) concentration or specific gravity (SG) to account for fluctuations in urine dilution. For instance, the American Conference of Governmental Industrial Hygienists (ACGIH(®)) uses a reference value of 1g/L for CR. The comparison of urinary concentrations of biomarkers between studies requires the adjustment of results based on a reference CR and/or SG value, although studies have suggested that age, sex, muscle mass, and time of the day can exert non-negligible influences on CR excretion, while SG appears to be less affected. The objective of this study was to propose reference values for urinary CR and SG based on the results of samples sent for analysis by occupational health practitioners to the laboratory of the Occupational Health and Safety Research Institute of Québec (IRSST). We analyzed a database containing 20,395 urinary sample results collected between 1985 and 2010. Linear mixed-effects models with worker as a random effect were used to estimate the influence of sex and collection period on urinary CR and SG. Median CR concentrations were 25-30% higher in men (1.6 g/L or 14.4 mmol/L) than in women (1.2 g/L or 10.2 mmol/L). Four percent of the samples for men and 12% for women were below the acceptable threshold for CR (4.4 mmol/L). For SG, 5% of samples for men and 12% for women were below the threshold of 1.010. The difference in SG levels between sexes was lower than for CR, with a median of 1.024 for men compared to 1.020 for women. Our results suggest that the normalization of reference values based on a standard CR value of 1 g/L as proposed by the ACGIH is a conservative approach. According to the literature, CR excretion is more influenced by physiological parameters than SG. We therefore suggest that correction based on SG should be favored in future studies involving the proposal of reference values for the biological monitoring of occupational exposures.
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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 | 0.025 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".