A Comparative Study on Serum Level Concentration of Micronutrients Like Zinc, Copper and Chromium Status in Type 2 Diabetic Patients in Diabetes & Endocrinology Unit, Tikur Anbessa Specialized Hospital, Ethiopia
Bibliographic record
Abstract
Background: Diabetes mellitus (DM) is a chronic metabolic disorder, characterized by an absolute or relative deficiency of insulin and insulin resistance. Many studies have reported an association between diabetes and alterations in the metabolism of several micronutrients. In Ethiopia the study in the relationship between micronutrients (Zn, Cu and Cr) status and type 2 diabetes (T2DM) is scanty. The aim of this study was to assess and compare the concentration of the fasting serum zinc, copper and chromium status in T2DM and control subjects.Method: A cross-sectional comparative study, conducted on 108 human subjects divided in to two groups: 54 subjects with the diagnosis of T2DM and the other 54 subjects were grouped as the control. After demographic and anthropometric information gathered, the blood sample was collected for the biochemical analysis. Fasting serum glucose was measured by glucose oxidase methods. The serum concentration of micronutrients namely zinc, copper and chromium were determined by using atomic absorption spectrophotometer. Data were analyzed using SPSS version 16 software.Results: Compared with control groups, T2DM patients had greater BMI (p
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".