Crosstalk between Vitamin D and thyroid hormone with respect to patients with High Blood Pressure: A Review
Bibliographic record
Abstract
By allowing the heart to pump blood to all of the body's organs, the cardiovascular system ensures that their metabolic demands are met. Systemic vascular resistance (SVR) and cardiac output (CO) are two measures that can be used to determine blood pressure and blood flow. The heart's pumping action is a good indicator of cardiac output. Blood pressure readings deviate from the normal range for a variety of reasons that affect CO or SVR. Many factors can affect the equilibrium of systemic vascular resistance and cardiac output. Both the amount of blood circulating in the body and the force of the heart's pumping action determines CO. Ensuring the body's blood volume is maintained relies heavily on the kidney's sodium regulation and fluid handling abilities. Any decrease in kidney function, no matter how slight, will have a major impact on the body's ability to regulate fluid volume because the kidneys are so important for maintaining a healthy fluid and sodium balance. Vitamin D deficiency, defined as levels below 20 ng/ml, is on the rise, even among otherwise healthy people, and is thus a major concern in global public health. Environmental factors like vitamin D play a role in numerous biological processes, including how we perceive chronic pain and how our bodies respond to infections. Patients with autoimmune thyroid disease (AITD) are at increased risk for developing vitamin D deficiency, and new evidence suggests that vitamin D may play a role in the onset of several autoimmune diseases. Pregnancy complications, abnormal thyroid function, elevated TSH levels, elevated thyroid volume, and antithyroid antibodies were all linked to low vitamin D levels in women with AITD. The article aims to understand the link between Vitamin D and the thyroid hormone in patients with hypertensive patients along with to establish a qualitative criterion within it.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".