Study of biochemical parameters with insulin resistance type 2 diabetes mellitus subjects
Bibliographic record
Abstract
Introduction: Diabetes results from hyperglycemia and improper glucose, lipid, and protein metabolism. The elderly population will quadruple in 10 years. LMICs have the highest type 2 DM patients. Insulin resistance and beta cell abnormalities cause T2DM. This study compared HbA1c, FPG, and lipids to controls. Materials and methods: The study was carried out in the Department of Biochemistry L.LRM Medical College, Meerut. The study was done on 250 individuals, who included 100 uncontrolled type-2 diabetic (Group III), 100 controlled type-2 diabetic (Group II) and 50 healthy individuals (Group I). Blood biochemistry and immunology for various parameters such as Fasting Blood Sugar (FBS), Glycosylated haemoglobin (HbA1c), Total Cholesterol (TC), Triglyceride (TG), High density-lipoprotein cholesterol (HDL-c), Low density lipoprotein cholesterol (LDL-c), Very low density lipoprotein cholesterol (VLDL-c), Urea, Creatinine were carried out for all three groups. SPSS16.0 was used to analyse the results. Results: In our study we found highly significant increase (P< 0.001) of fasting blood sugar and glycosylated hemoglobin levels in group II and group III as compared to group I. In the present study, the patterns of lipid profile parameters in type-2 diabetic subjects were also studied.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".