MP100CENTRAL BLOOD PRESSURES ARE INCREASED IN HEALTHY INDIVIDUALS WITH RENAL HYPERFILTRATION
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Renal hyperfiltration has been shown to be associated with mortality and cardiovascular issues, however the mechanisms explaining this association remain unknown. We propose that an augmentation of the central systolic and pulse pressures lead to the renal hyperfiltration. This study aims to show the relationship between these two parameters in a group of healthy individuals. METHODS: Of the 20,004 participants in the CARTaGENE cohort, 10,075 healthy individuals (without high blood pressure, diabetes nor cardiovascular comorbidities) had central pressure measurements. From these participants, a group of « hyperfiltrators », defined as an estimated glomerular filtration rate (eGFR) higher than the 95th percentile after stratification for sex and age was compared to a control group, defined as the participants with an eGFR between the 25th and 75th percentiles. The central blood pressures adjusted for known confounding factors and peripheral blood pressure were than compared between the two groups through general linear modelling. MP100 Figure CONCLUSIONS: In healthy individuals without cardiovascular comorbidities, renal hyperfiltration is associated with higher central systolic and pulse pressures, independently peripheral blood pressure and other known confounders. Whether this explain, at least in part, the increased cardiovascular morbidity and mortality associated with renal hyperfiltration remains to be determined.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".