Spironolactone Use in Heart Failure Patients With End‐Stage Renal Disease on Hemodialysis: Is It Safe?
Bibliographic record
Abstract
BACKGROUND: Spironolactone is used in the treatment of cardiovascular disease, but is contraindicated in renal dysfunction due to the risk of hyperkalemia. It is not known if patients with end-stage renal disease (ESRD) on hemodialysis are at the same risk for hyperkalemia. The objective of this study was to systematically review the evidence evaluating the incidence of hyperkalemia with spironolactone use in ESRD patients on hemodialysis. HYPOTHESIS: Spironolactone use in ESRD patients on hemodialysis may not lead to greater incidence of hyperkalemia. METHODS: We searched the MEDLINE, Embase, CINAHL, Cochrane, and PubMed databases up to January 2010 for English-language, human-subject clinical trials that evaluated the rate of hyperkalemia with spironolactone use in ESRD patients on hemodialysis. Search terms included were "spironolactone," "eplerenone," "aldosterone antagonist," "heart failure," "kidney failure," "hemodialysis," "dialysis," and "renal replacement therapy." RESULTS: Six prospective trials demonstrated that spironolactone use was safe in ESRD patients on hemodialysis. The incidence of hyperkalemia with spironolactone treatment in these studies was similar to control groups. The studies involved a small population of compliant subjects who were at low risk for hyperkalemia. CONCLUSIONS: Small pilot studies demonstrated that spironolactone treatment in ESRD patients on hemodialysis did not result in higher hyperkalemia rates. Larger studies are needed to confirm these preliminary results before spironolactone is routinely considered in hemodialysis patients.
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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 | 0.007 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".