Plasma levels of endothelin-1 and renal function among young and healthy adults
Bibliographic record
Abstract
BACKGROUND: Endothelin-1 (ET-1), a vasoconstrictive and pro-inflammatory peptide, is associated with several cardiovascular risk factors and outcomes. We aimed to investigate the association of plasma ET-1 levels and renal function among young and healthy adults. METHODS: Individuals aged 25-41 years were enrolled in a population-based cohort study. Main exclusion criteria were established kidney disease, cardiovascular diseases, diabetes mellitus and a body mass index>35 kg/m2. Fasting venous plasma samples were used to measure creatinine, cystatin C and ET-1. The estimated glomerular filtration rate (eGFR) was calculated using the creatinine based chronic kidney disease epidemiology collaboration (CKD-EPI) formula. Multivariable regression models were constructed to assess interrelationships of plasma ET-1 with parameters of renal function. RESULTS: Median age of the 2139 participants was 37 years, 47% males. Median creatinine and eGFR were 67 μmol/L and 112 mL/min/1.73 m2, respectively. Using quartile one as the reference group, the β-coefficients (95% confidence intervals [CIs]) for eGFR were 0.06 (- 1.22 to 1.35),-0.66 (- 1.95 to 0.62) and-1.70 (- 3.01 to-0.39) for quartiles 2-4 (p-for-trend=0.0056), respectively and β-coefficients (95% CIs) for cystatin C were 0.002 (- 0.01 to 0.02), 0.02 (0.003-0.03) and 0.03 (0.01-0.04) for quartiles 2-4 (p-for-trend<0.0001), respectively. Using ET-1 as a continuous variable, the β-coefficient (95% CI) for eGFR per 1-unit increase was-1.82 (- 3.19 to-0.44, p=0.0095) and 0.02 (0.01-0.04, p=0.0003) for cystatin C. Similar results were found between creatinine and ET-1 levels. CONCLUSIONS: ET-1 levels are strongly associated with parameters of renal function among young and healthy adults, suggesting an important role of ET-1 and endothelial function in the regulation of kidney function.
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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 | 0.001 |
| 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".