Systematic Review on the Management of Diuretic Resistance in Acute Heart Failure across the Spectrum of Kidney Disease
Bibliographic record
Abstract
BACKGROUND: Diuretic resistance is commonly reported in acute heart failure (AHF), especially in patients presenting with impaired kidney function. Effective treatment strategies for promoting decongestion in this population remain unclear. METHODS: A systematic review using MEDLINE/Cochrane databases was performed from inception to January 2024, identifying randomized clinical trials (RCTs) including patients with diuretic resistance or at risk of diuretic resistance based on the presence of kidney dysfunction at study enrollment. Trials testing different pharmacological or invasive modalities compared to standard of care, placebo or an active comparator were considered. Data on decongestion-related outcomes, safety outcomes, and clinical outcomes up to 90 days were collected. RESULTS: Among the 22 RCTs included, 6 trials involved 529 patients with established diuretic resistance, while 16 trials enrolled 1,913 patients at risk of diuretic resistance. Diuretic resistance was differently defined across studies and most trials focused on interventions targeting different sites of action along the renal tubules. The different treatment strategies demonstrated efficacy in promoting decongestion while being associated with a mild increase in creatinine and cystatin C. The use of appropriately high doses of intravenous loop diuretics was able to promote decongestion across the spectrum of kidney dysfunction. The presence of baseline kidney dysfunction did not identify a population resistant to standard decongestive strategies. CONCLUSIONS: Diuretic resistance is not accurately defined in AHF but is uncommon in patients treated with appropriately high doses of intravenous loop diuretics. The main therapeutic goal in the acute setting should focus on promoting decongestion instead of overemphasizing on mild changes in kidney-related biomarkers.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.000 | 0.000 |
| 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".