Dietary Potassium Intake and All-Cause Mortality in Adults Treated with Hemodialysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Dietary potassium restriction in people receiving maintenance hemodialysis is standard practice and is recommended in guidelines, despite a lack of evidence. We aimed to assess the association between dietary potassium intake and mortality and whether hyperkalemia mediates this association. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A total of 8043 adults undergoing maintenance hemodialysis in Europe and South America were included in the DIETary intake, death and hospitalization in adults with end-stage kidney disease treated with HemoDialysis (DIET-HD) study. We measured baseline potassium intake from the Global Allergy and Asthma European Network food frequency questionnaire and performed time-to-event and mediation analyses. RESULTS: The median potassium intake at baseline was 3.5 (interquartile range, 2.5-5.0) g/d. During a median follow-up of 4.0 years (25,890 person-years), we observed 2921 (36%) deaths. After adjusting for baseline characteristics, including cardiac disease and food groups, dietary potassium intake was not associated with all-cause mortality (per 1 g/d higher dietary potassium intake: hazard ratio, 1.00; 95% confidence interval [95% CI], 0.95 to 1.05). A mediation analysis showed no association of potassium intake with mortality, either through or independent of serum potassium (hazard ratio, 1.00; 95% CI, 1.00 to 1.00 and hazard ratio, 1.01; 95% CI, 0.96 to 1.06, respectively). Potassium intake was not significantly associated with serum levels (0.03; 95% CI, -0.01 to 0.07 mEq/L per 1 g/d higher dietary potassium intake) or the prevalence of hyperkalemia (≥6.0 mEq/L) at baseline (odds ratio, 1.11; 95% CI, 0.89 to 1.37 per 1 g/d higher dietary potassium intake). Hyperkalemia was associated with cardiovascular death (hazard ratio, 1.23; 95% CI, 1.03 to 1.48). CONCLUSIONS: Higher dietary intake of potassium is not associated with hyperkalemia or death in patients treated with hemodialysis.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".