Metabolic Syndrome - Risk Factors for Atherosclerosis and 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
Objective: To evaluate the lipoprotein profiles, triglycerides and glycemia along with the abdominal fat to explore the risk factors associated with non-diabetic state to IGF, IGT and Type-2 diabetes in Canadian population. Methods: We examined 780 subjects using the ADA and WHO criteria to classify them into groups based on (1) normal glucose tolerance with FBS < 6.0 and 2hBS < 7.0 mmol/l), (2) IFG; FPG ≥6.1 mmol/l but 2hBS > 7.8-11.1 mmol/l; (3) combined IFG/IGT (FPG ≥7.0 mmol/l and 2hBS > 11.1 mmol/l). We compared the three groups for glycemia, insulin secretion and insulin sensitivity based on their WHR, abdominal and visceral fat measurements. Results: The subjects with higher 2 hrs glucose levels 5.2 for NGT vs. 9.1 for IGT and 13.4 mmol/l for NIDDM, p < 0.001, apo C-III level (12.8 (DM) vs. 8.9 mg/dl (normal), p < 0.001), waist to hip ratio (0.91 (IGT) vs. 0.89 (Normal), p < 0.01) and abdominal fat and were found to be highly insulin resistant. Conclusions: The higher apolipoproteins levels, BMI and abdominal and visceral fat accompanied by poor glycemia were shown to be associated strongly with the metabolic abnormalities. These factors led to the worsening of insulin secretory dysfunction and insulin resistance and were strong predictors of diabetes. Abbreviations: 2hBS, 2-hour blood sugar, • FBS, fasting blood glucose, •NGT, normal glucose tolerance, • IFG, impaired fasting glucose, • IGT, impaired glucose tolerance, • MS, metabolic syndrome, • IR, insulin resistance • ISI, insulin sensitivity index • OGTT, oral glucose tolerance test • WHR, waist-to-hip ratio, • BMI, body mass index, • VFA, visceral fat area, • SFA, subcutaneous fat area, • WHO, World Health Organization.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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