The prevalence of predialysis hyperkalemia and associated characteristics among hemodialysis patients: The <scp>RE‐UTILIZE</scp> study
Bibliographic record
Abstract
Abstract Introduction Hyperkalemia (HK), defined as serum potassium (K+) >5.0 mEq/L, is an independent predictor of mortality in patients on maintenance hemodialysis (HD). This study investigated the annual prevalence of HK and examined patient characteristics potentially associated with a higher annual HK prevalence. Methods This retrospective observational cohort study used Dialysis Outcomes and Practice Patterns Study (DOPPS) survey data from US patients undergoing in‐center HD thrice weekly from 2018 to 2019. The primary endpoint was the proportion of patients with any predialysis HK (K+ >5.0 mEq/L) within 1 year from the index date (date of DOPPS enrollment), using the first hyperkalemic K+ value. Secondary endpoints were the proportion of patients with moderate‐to‐severe (K+ >5.5 mEq/L) or severe (K+ >6.0 mEq/L) HK. Findings Overall, 9347 patients on HD were included in this analysis (58% male and 49% aged >66 years). Any predialysis HK (K+ >5.0 mEq/L) occurred in 74% of patients within 1 year of the index date, 52% within 3 months, and 38% within 1 month. The annual prevalence of moderate‐to‐severe and severe HK was 43% and 17%, respectively. Recurrent HK (at least two K+ >5.0 mEq/L within 1 year) occurred in 60% of patients, and 2.8% of patients were prescribed an oral K+ binder. Multivariable logistic regression analysis showed younger age, female sex, Hispanic ethnicity, and renin–angiotensin–aldosterone system inhibitor use were significantly associated with a higher annual prevalence of any predialysis HK, while Black race, obesity, recent initiation of HD, and dialysate K+ bath concentration ≥3 mEq/L were associated with a lower prevalence of HK. Discussion The annual prevalence of predialysis HK and recurrence were high among US patients on HD, whereas oral K+ binder use was low. Further studies are needed to understand the impact of dialysate K+ bath concentrations on predialysis HK among patients on HD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".