Do Heat Events Pose a Greater Health Risk for Individuals with Type 2 Diabetes?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chronic medical conditions such as type 2 diabetes may alter the body's normal response to heat. Evidence suggests that the local heat loss response of skin blood flow (SkBF) is affected by diabetes-related impairments in both endothelium-dependent and non-endothelium-dependent mechanisms, resulting in lower elevations in SkBF in response to a heat or pharmacological stimulus. Thermoregulatory sweating may also be diminished by type 2 diabetes, impairing the body's ability to transfer heat from its core to the environment. Diabetes-associated co-morbidities and the medications (particularly those affecting fluid balance) required to treat these conditions may exacerbate the risk of heat-related illness by decreasing SkBF and sweating further. Unfortunately, the majority of studies measure local heat loss responses in the hands and feet and lack measures of core temperature. Therefore, the impact of these impairments on whole-body heat loss remains unknown. This review addresses heat-related vulnerability in individuals with type 2 diabetes by examining the literature related to heat loss responses in this population. Type 2 diabetes, its associated co-morbidities, and the medications required in their treatment may cause dehydration, lower SkBF, and reduced sweating, which could consequently impair thermoregulation. This effect is most evident in individuals with poor blood glucose control. Although type 2 diabetes can be associated with impairments in SkBF and sweating, more physically active individuals requiring fewer medications and having good blood glucose control may be able to tolerate heat as well as those of similar age and body composition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it