Increased Sodium Intake Correlates With Greater Use of Antihypertensive Agents by Subjects With Chronic Kidney Disease
Bibliographic record
Abstract
BACKGROUND: Hypertension is a common disease in patients with chronic kidney disease (CKD) and predisposes to heart disease, stroke, and progression of renal failure. In the general population, sodium restriction has been shown to improve blood pressure (BP) control, but this is not widely recommended in CKD patients. The aim of this study was to assess the sodium balance in a CKD clinic and its effect on BP management. METHODS: We retrospectively reviewed charts from June 1998 through to June 2003 and included all patients with an estimated glomerular filtration rate (GFR) of <30 mL/min who completed a 24-h urine collection for sodium. Patients were divided into tertiles based upon their 24-h sodium excretion and analyzed by ANOVA. RESULTS: We included 141 CKD patients who had a mean (+/- SE) sodium excretion of 145.7 +/- 4.7 mmol/day. There were a significantly greater number of antihypertensive agents used with increasing sodium excretion (2.00 +/- 0.16, 2.61 +/- 0.20, and 2.77 +/- 0.19 medications, respectively for each tertile; P = .01). This difference was even more prominent when only those patients with a GFR <or=15 mL/min (n = 77) were examined (1.69 +/- 0.19, 2.52 +/- 0.27, and 3.08 +/- 0.26 medications, respectively; P = .001). Control of BP was equivalent in all groups. Multivariable analysis revealed sodium excretion (P = .00005) and age (P = .007) to be significantly associated with use of antihypertensive medication. CONCLUSIONS: We have demonstrated that increased sodium intake is associated with an increased number of antihypertensive medications to achieve comparable BP control in a population with CKD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".