The contribution of modern 24-hour society to the development of type 2 diabetes mellitus: the role of insufficient sleep
Bibliographic record
Abstract
Epidemiological studies since 1980 have shown significant increases in the incidence of type 2 diabetes mellitus (T2DM). The public health burden generated by the growing prevalence of T2DM, which, in its fully developed form, is a lifelong illness, has been associated with further social and economic costs in affected countries. Recent studies have suggested that chronic sleep insufficiency or disrupted or poor quality sleep could contribute to the development of T2DM. Although many research findings have now shown that sleep plays a key role in glucose metabolism, the full implications of these findings have not been translated into clinical programs for improving patients' sleep quality as a means for addressing the treatment of T2DM. The purpose of this brief overview is to focus on the clinical significance of sleep in the onset and treatment of T2DM. We suggest here that physician education should emphasize the importance of sufficient sleep for overall health, including the management of T2DM, and that steps should be taken to incorporate this perspective into clinical practice. The promotion of sleep hygiene techniques as a clinical intervention could improve the regulation of glucose metabolism and thus the longevity of T2DM patients. Moreover, it may prevent secondary complications accruing from the illness and consequently reduce the significant medical costs of treating T2DM patients.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".