An Evidence-Based Review of Diabetes Care: History, Types, Relationshipto Cancer and Heart Disease, Co-Morbid Factors, and PreventiveMeasures
Bibliographic record
Abstract
Abstract: Diabetes is characterized by hyperglycemia due to the decreased and inadequate levels of insulin in the body, resistance to the effects of insulin, or a combination of both. There are three types of diabetes, however Type 2 disease is the most common followed by Type 1 and gestational diabetes. Most common factors responsible for diabetes are obesity or being overweight, impaired glucose tolerance, insulin resistance, ethnic background, sedentary lifestyle and family history. Because of the increased longevity, it is becoming a disease of the elderly thus contributing to the complexity of managing it in the ageing population. Diabetes also has implications to cancer and heart disease. Some studies have shown increased cancer risk in prediabetic and diabetic individuals. A recent major study draws firm conclusion that diabetes promotes a person’s risk of developing different types of cancer. The occurrence and mortality of cancer types, e.g., pancreas, liver, colorectal, breast, endometrial, and bladder cancers may produce a modest rise in diabetics. Women with diabetes are 27% likelier to develop cancer compared to healthy women. On the other hand only 19% more men with diabetes are likely to develop cancer when compared to healthy men. Preventive measures such as proper diet, physical activity, weight management, smoking cessation, and controlling obesity may improve outcomes of Type 2 diabetes (T2D) and some forms of cancer. Developing awareness of the genetic association relationship between T2D and coronary heart disease has begun to provide the potential for better prevention and treatment of both disorders. Significant preventive measures for diabetes include – consumption of nutrients such as vitamin D, nuts, minerals chromium, and magnesium, controlling weight, hypertension, plant foods and a Mediterranean plant-based diet along with increased exercise.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".