The effects of diuretic deprescribing in adult patients: A systematic review to inform an evidence‐based diuretic deprescribing guideline
Bibliographic record
Abstract
In this systematic review, we report on the effects of diuretic deprescribing compared to continued diuretic use. We included clinical studies reporting on outcomes such as mortality, heart failure recurrence, tolerability and feasibility. We assessed risk of bias and certainty of the evidence using the GRADE framework. We included 25 publications from 22 primary studies (15 randomized controlled trials; 7 nonrandomized studies). The mean number of participants in the deprescribing groups was 35, and median/mean age 64 years. In patients with heart failure, there was no clear evidence that diuretic deprescribing was associated with increased mortality compared to diuretic continuation (low certainty evidence). The risk of cardiovascular composite outcomes associated with diuretic deprescribing was inconsistent (studies showing lower risk for diuretic deprescribing, or comparable risk with diuretic continuation; very low certainty evidence). The effect on heart failure recurrence after diuretic deprescribing in patients with diuretics for heart failure, and of hypertension in patients with diuretics for hypertension was inconsistent across the included studies (low certainty evidence). In patients with diuretics for hypertension, diuretic deprescribing was well tolerated (moderate certainty evidence), while in patients with diuretics for heart failure, deprescribing diuretics can result in complaints of peripheral oedema (very low certainty evidence). The overall risk of bias was generally high. In summary, this systematic review suggests that diuretic discontinuation could be a safe and feasible treatment option for carefully selected patients. However, there isa lack of high-quality evidence on its feasibility, safety and tolerability of diuretic deprescribing, warranting further research.
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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 | 0.032 | 0.120 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".