Thyroid Hormones Protect Type 2 Diabetes Obese Patients Against Cardio-Metabolic Risk Factors
Bibliographic record
Abstract
Background: Dysfunction of thyroid gland was observed in obese and type 2 diabetes (T2D) patients. The serum level of thyroid stimulating hormone (TSH) is increased in these conditions and inversely correlated with risk factors that related to cardiovascular events. This study aimed to demonstrate the changes in the serum level of thyroid hormones; triiodothyronine (T3) and thyroxin (T4) and TSH in obese T2D patients and to demonstrate the gender-based effect of these hormones against the cardio-metabolic risk factors that existed in those patients. Methods: A total number of 150 obese T2D patients (100 women and 50 men) recruited from Martyr LaylaQasm Center for Diabetes Mellitus in Erbil, Iraq during 2013 were enrolled in this study. The cardio-metabolic risk factors are assessed via measuring body weight, body mass index (BMI), waist circumference, blood pressure, fasting serum glucose and lipid profile, glycosylated hemoglobin and high sensitive C-reactive protein (hsCRP). Serum total T4, T3 and TSH were measured. Results: The serum levels of T4 and T3 attended higher levels in women compared with men while the TSH level is less in women than in men. The significant positive correlations between the TSH and the cardio-metabolic risk factors (except fasting serum glucose and hsCRP) were observed. An inverse pattern was observed with T4 and T3. The coefficient factors of these correlations were higher in women compared with men. Conclusions: It concludes that the thyroid gland function is disturbed in obese T2D patients, and thyroid hormones were significantly and inversely correlated with cardio-metabolic risk factors which were prominently observed in men. J Endocrinol Metab. 2015;5(1-2):179-183 doi: http://dx.doi.org/10.14740/jem274w
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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 | 0.000 | 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) | 0.002 | 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".