Diuretics in the Management of Acute Kidney Injury: A Multinational Survey
Bibliographic record
Abstract
BACKGROUND: Diuretics are a common intervention in critically ill patients with acute kidney injury (AKI). However, there is no information that describes the practice patterns of diuretic use by clinicians. METHODS: Multinational, multicenter survey of intensive care and nephrology clinicians that utilized an 18-question self-reported questionnaire. RESULTS: The survey generated 331 responses from 16 countries. Academic institutions comprised 77.5%, with the remaining being from metropolitan, regional or private hospitals. The use of furosemide was most common (67.1%), delivered primarily intravenously (71.9%) and by bolus dosing (43.3%). Other diuretics were infrequently used. The majority rated current serum creatinine (73.6%) and urine output (73.4%), blood pressure (59.7%), central venous pressure (65.2%) and risk of toxicity (62.4%) important when deciding on a dose. Pulmonary edema was a prime physiologic indication for diuretic use (86.3%). Diuretic use was also common with rhabdomyolysis (55.6%), major surgery (56%), and cardiogenic shock (56.2%), and sepsis (49.5%). Diuretic use was most commonly given either prior to (57.7%) or during recovery (33.9%) after renal replacement therapy (RRT). Most (76.6%) targeted a diuresis of >or=0.5-1.0 ml/kg/h. The majority did not believe that diuretics could reduce mortality (74.3%), reduce need for (50.8%) or duration of RRT (57.8%) or improve renal recovery (68.2%), however, many stated uncertainty. Most (85.1%) would be willing to participate in a randomized trial (RCT) of diuretics in AKI with 72.4% believing it ethically acceptable to allocate patients to placebo. CONCLUSION: Diuretics are frequently used in AKI. Clinicians are most familiar with furosemide given intravenously and titrated to a physiologic endpoint of urine output. Most clinicians believe an RCT on diuretic use in AKI is justified and ethical. This survey confirms clinical agreement and a need for higher quality evidence on diuretic use in AKI.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".