Exploring the Spectrum of Blood Pressure Associations with CKD: The International 24-Hour Aortic Blood Pressure Consortium (i24ABC)
Bibliographic record
Abstract
Background: Chronic kidney disease (CKD) has emerged as a significant public health concern. The kidneys are primarily exposed to pulsatile rather than steady hemodynamics, which complicates the bidirectional relationship between CKD and hypertension. We aimed to explore relationships between blood pressure (BP) parameters and renal function in a pooled dataset from 21 centers worldwide. Methods: The dataset included clinical and hemodynamic information. All participants underwent office BP measurements, in addition to 24-hour ambulatory BP monitoring (ABPM) with the same validated automated brachial oscillometric device (Mobil-OGraph, I.E.M., Germany) using a transfer function for central pressure, and mean/diastolic pressure calibration. Renal function was estimated using the CKD-EPI equation and subjects classified into the 6 eGFR categories following the KDIGO 2021 guideline. Results: We included 5204 subjects, 46.1% females, with a mean age of 60.8 ± 13.9 years. Diabetes was noted in 14.7% and hypertension in 70.3% of subjects, 76% of whom were on antihypertensive therapy. The mean eGFR was 88.5 ± 19.9 mL/min/1.73 m2. More than half of the participants (56.5%) had a normal or high eGFR (G1) and only 1.9% had a severely decreased eGFR (G5). The prevalence of hypertension increased progressively across GFR categories with 95.7% of subjects in G5 vs. 67.7% in G1 (p<0.001) with hypertension. Diastolic BP tended to decrease (p<0.001) and SBP to increase (p<0.001) with decreasing eGFR. These associations were consistent for both brachial and central values, and for office and ABPM measurement techniques. Systolic reverse dipping status was independently associated with decreased eGFR after adjustment for gender and age, and irrespective of hypertension status (β=-1.74, p=0.004). Conclusions: CKD is associated with adverse hemodynamic changes, both at the brachial and the aortic level, and in office and out-of-office measurements, indicative of arterial stiffening.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".