Kidney Injury Risk Does Not Differ Between Men And Women During Work In The Heat
Bibliographic record
Abstract
PURPOSE: Occupational heat stress increases the risk of kidney injury (KI) due to the development of hyperthermia and dehydration. Some observational evidence indicates that young women may be at a higher risk of KI compared to young men during heatwaves, but this is not always the case. Whether KI risk differs between young men and women during occupationally relevant heat stress is unknown. We tested the hypothesis that during physical work in the heat KI risk differs between men and women. METHODS: Twelve healthy men (25 ± 5 y; M) and twelve healthy eumenorrheic women (26 ± 5 y; W) in the early follicular phase of their menstrual cycle completed a 4 h exposure to 33.7 ± 0.3 °C, 54 ± 1% relative humidity (WBGT = 28.4 ± 0.3 °C, typical heat stress encountered in outdoor occupations). Each hour participants walked for 30 min at an intensity evoking a rate of metabolic heat production of 5.2 ± 0.7 W/kg body mass, which did not differ between men and women (p ≥ 0.34). Participants drank a cool non-caloric sport drink ad libitum. Rectal or intestinal temperature provided a measure of core temperature, while percent change in body weight loss (%BWL) provided an index of changes in body water. Urine was collected pre-, post-, and 1 h post-exposure. KI biomarkers of urinary insulin-like growth factor-binding protein 7 [IGFBP7] and tissue inhibitor of metalloproteinase 2 [TIMP-2] were measured and normalized to urine flow rate. The peak change in the product of IGFBP7 and TIMP-2 (Δ[IGFBP7xTIMP-2]) provided an overall index of KI risk. Data are presented as mean ± SD. RESULTS: The change in core temperature (M: +0.5 ± 0.3 °C, W: +0.4 ± 0.2 °C, p = 0.16), %BWL (M: -0.5 ± 0.5%, W: -0.5 ± 0.9%, p = 0.89), and fluid intake (M: 1524 ± 338 mL, W: 1609 ± 919 mL, p = 0.77) did not differ between men and women. Urinary IGFBP7 and TIMP2 both increased over time (time effect: p < 0.01) such that IGFBP7 (M: +93.5 ± 143.9 ng/min, W: +70.1 ± 96.4 ng/min) and TIMP2 (M: +2.6 ± 2.5 ng/min, W: 2.2 ± 2.8 ng/min) were elevated at post-, but there were no group (p ≥ 0.46) or interaction (p ≥ 0.15) effects. The peak ∆[IGFBP7xTIMP-2] did not differ between men (+3.1 ± 5.6 [ng/mL2]/1000) and women (+0.7 ± 1.2 [ng/mL2]/1000, p = 0.14). CONCLUSIONS: During occupationally relevant physical work in the heat in which fluids were freely available, KI risk does not differ between men and women. Funding: R01OH011528
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".