Serum Albumin and Uric Acid Levels in Hypertensive Patients: A Cross-Sectional Analysis From Central Tamil Nadu, South India
Bibliographic record
Abstract
Introduction Hypertension represents a significant global health challenge, with an increasing incidence among adults. Despite the prominence of infectious diseases, non-communicable conditions like hypertension remain a silent yet critical health concern. Liver and kidney functions play crucial roles in blood pressure maintenance, with serum albumin and uric acid serving as key metabolic indicators. Objective The primary objective of this study is to analyze the association between serum albumin and uric acid levels in hypertensive patients aged 30-50 years. The secondary objective is to determine whether deranged serum albumin and uric acid levels are associated with other variables like body mass index and blood pressure values. Methods An analytical cross-sectional study was conducted between September and October 2021 at a hospital in Perambalur, Tamil Nadu, India. The study employed non-probability convenient sampling to recruit hypertensive patients aged 30-50 years. Participants with coronary artery disease, stroke, liver disease, renal failure, hyperuricemia, gout, diabetes mellitus, or taking medications that affect albumin or uric acid levels were excluded. Blood pressure measurements were taken after ensuring adequate rest, and 4 ml of venous blood was collected from each participant for biochemical analysis. Serum albumin and uric acid levels were determined using the analyzer. The data analysis was performed using Microsoft Excel and statistical software. The statistical significance of the findings was evaluated using appropriate statistical tests, providing a robust framework for understanding the metabolic associations in hypertension. Results The study population of 150 hypertensive patients demonstrated a majority of 88 (58.67%) aged over 40 years and 62 (41.33%) under 40 years. The gender distribution revealed 87 (58%) males and 63 (42% females). The mean systolic blood pressure was 158.2 mmHg, with a mean diastolic blood pressure of 94.73 mmHg, indicating moderate to severe hypertension. Biochemical analysis showed an average serum uric acid level of 6.41 mg/dL and a mean serum albumin level of 3.54 mg/dL. Statistical analysis revealed a significant association between elevated uric acid levels and decreased serum albumin levels (p < 0.05), suggesting a potential interrelationship between these metabolic markers in hypertensive patients. Conclusion The study establishes hyperuricemia and hypoalbuminemia as significant risk factors for hypertension development or pathogenesis. Early detection of these metabolic derangements may provide opportunities for preventive interventions and potential disease management strategies. The findings emphasize the importance of comprehensive biochemical assessment in understanding and mitigating hypertension risk.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".