Dietary Potassium Intake and All-Cause Mortality in Adults Undergoing Hemodialysis: The DIET-HD Cohort Study
Bibliographic record
Abstract
Background: Dietary modification to reduce the risk of hyperkalemia in people undergoing maintenance hemodialysis is standard practice and is commonly recommended in guidelines despite a lack of evidence. A low potassium diet may impair quality of life and nutritional status. We aimed to assess the association between dietary potassium intake and mortality and whether hyperkalemia mediates this association. Methods: 9690 adults undergoing maintenance hemodialysis in Europe and South America were recruited in the DIET-HD study, of which 1647 were excluded for lack of data-linkage identifier or incomplete or implausible dietary assessment. We measured baseline potassium intake from the GA2LEN food frequency questionnaire and performed time-to-event and mediation analyses. Results: The median dietary potassium intake at baseline was 3.5 g/day (IQR 2.5 to 5.0). During a median follow-up of 3.97 years (25,890 person-years), we observed 2921 (36%) deaths including 1316 (45%) from cardiovascular causes. After adjusting for baseline characteristics including presence of cardiac disease and food groups, dietary potassium intake was not associated with all-cause mortality (hazard ratio [HR] 1.00 95% confidence interval [CI] 0.95 to 1.05). A mediation analysis showed no association of potassium intake with mortality either through or independent of serum potassium (HR 0.999, 95% CI 0.996 to 1.002 and 1.000, 95% CI 0.999 to 1.002, respectively). Higher potassium intake was not associated with higher serum potassium (B=0.04 mEq/L 95% CI 0.00 to 0.09) or the prevalence of hyperkalemia (≥ 6.0mEq/L) at baseline (OR=1.08, 95% CI 0.93 to 1.24). Hyperkalemia was associated with cardiovascular death (HR=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 maintenance hemodialysis. Funding: Government Support - Non-U.S.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".