Diet-dependent acid load is associated with mean arterial pressure in a cohort of non-obese, non-black, postmenopausal women
Bibliographic record
Abstract
Higher sodium (Na+) intake is associated with higher blood pressure (BP). Whether this relationship is stronger with diet-dependent acid load (DAL) and in patients diagnosed with hypertension or normal BP is not well determined. We studied 170 postmenopausal women randomized to receive potassium bicarbonate or placebo for 36 months, after which 24-hour urine and arterialized blood samples were collected. We investigated the association between DAL estimated as urinary potential renal acid load (UPRAL) and mean arterial pressure (MAP) using a mixed-effects model, adjusting for age, anthropometrics, creatinine clearance, and treatment. Adjusted regression estimates for changes in Na+ and UPRAL on MAP after 12 months of follow-up were calculated, and further adjustments were made for changes in potassium (K+) and body mass index (BMI). MAP was inversely associated with UPRAL (β [95% confidence interval]: –0.11 [–0.25, –0.001]). There was an effect modification by hypertension (p-interaction = 0.04); MAP decreased significantly in normotensives, but the association was not significant in hypertensives. A decrease of 0.70 mm Hg in MAP [0.13, 1.69] per 50 mmol/24 hour reduction in Na+ was noted when the model was adjusted for change in K+. Our results with UPRAL exhibited a stronger dose–response for MAP, which remained significant after adjusting for BMI. UPRAL was independently associated with MAP even after adjusting for potential confounders, and the data showed that this association was more pronounced in normotensive patients. Novelty: First longitudinal study on the association of UPRAL and MAP. Association was a more robust relationship than that between U [Na+/K+] ratio and MAP. UPRAL may play a significant role in the pathogenesis of primary hypertension.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| 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) | 0.001 | 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".