Relationship Between Inflammation and Endothelial Dysfunction in Essential Hypertension
Bibliographic record
Abstract
Background: A proposed pathogenic link between inflammation and hypertension is possibly through endothelial dysfunction. Objective: To study the relationship between inflammation and endothelial dysfunction in essential hypertension Methods: In a cross-sectional prospective study, 102 patients with essential hypertension underwent endothelial function evaluation at rest and after reactive hyperaemia by high-resolution B-mode ultrasound images in right upper arm after a written, informed consent. Glucose, lipid profile, creatinine, hsCRP (Diagnostics Biochem Canada Inc.), IL-6 (BD OptEIA™) and TNF- α (BD OptEIA™) were estimated in a 12 hours overnight fasting blood sample. Results: 102 patients (mean age 45 ± 8years, duration of hypertension 3.89 ± 0.43 years, and antihypertensive treatment in 91% and statins in 39.2%) were studied. The mean flow mediated vasodilatation (FMD) of the brachial artery was 12.2 ± 8.0%. 39 (38.2%) of patients had an abnormal FMD (a change of less than 10% in the diameter of the vessel wall). No correlation was found between FMD and duration of hypertension, systolic or diastolic blood pressure, body mass index, waist circumference or lipid profile using Spearman's test of correlation. hsCRP (75 patients), TNF-α levels (75 patients) and IL-6 levels (64 patients) were 69.5 ± 67.4 mg/L,125 ± 252pg/ml and 527 ± 1253pg/ml respectively. No correlation was found between any of the inflammatory markers and brachial FMD. Conclusions: A significant inflammation was observed in well controlled hypertensive patients. However there was no correlation between endothelial dysfunction and the degree of inflammation. Absence of target organ damage, younger age, shorter duration of hypertension and treatment could be the factors responsible for the same.
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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 | 0.001 |
| 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) | 0.001 | 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".