Identifying The “Danger Zone” For Individuals Performing Intermittent Work In The Heat
Bibliographic record
Abstract
The capacity to dissipate heat during exercise is reduced with age. However, this impairment may not be adequately detected using rectal temperature (Tre) leading to a potential underestimation of an individual’s level of risk. Further, there is little data on the threshold limits for the risk of heat-related injury for individuals based on factors including age, physical characteristics, and fitness (VO2peak). PURPOSE: To identify cutoffs in individual characteristics that can be used to screen older adults that are at a high risk of heat strain during exercise in the heat relative to young adults. METHODS: 18 young (20-31 years) and 67 older (39-70 years) males performed three 15 min exercise bouts at a fixed rate of metabolic heat production (400 W), each followed by 15 min of recovery in the heat (35°C). We assessed total heat loss (THL; direct calorimetry), Tre, VO2peak, and anthropometric variables. Older adults were labeled as “high risk” if their THL or Tre at the end of each exercise bout was not within two standard deviations from that recorded in their young counterparts. Receiver operating characteristics (ROC) curve analysis was used to detect cutoffs to diagnose high risk older adults using age, VO2peak, and body height, mass, surface area, and fat percentage (%BF). RESULTS: Using THL 40, 43, and 42 older adults were identified as high risk in exercise bouts 1, 2, and 3, respectively, compared to 5, 4, and 3 using Tre. Using THL, cutoffs for exercise bouts 1, 2, and 3 were identified at >51 years or %BF >26.8, >24.9, and >26.8, respectively. Significant Kappa agreement (P<0.05) was confirmed when comparing the age- and %BF-cutoffs to THL. No valid cutoffs were detected in any of the variables examined using Tre (P>0.05). CONCLUSION: We show that based on whole-body heat loss responses, older individuals are at increased risk for heat-related injury during exercise in the heat at an age >51 years and/or %BF of 26.8%, whereas no level of risk was associated with other physical characteristics or fitness. Conversely, no level of risk was observed using rectal temperature responses, indicating a lack of sensitivity to accurately assess older adults’ risk for heat-related injury during exercise in the heat. SUPPORT: Workplace Safety and Insurance Board (Ontario), Natural Sciences and Engineering Research Council of Canada.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".