Meta-Analysis: Low-Dose Dopamine Increases Urine Output but Does Not Prevent Renal Dysfunction or Death
Bibliographic record
Abstract
BACKGROUND: Surveys have documented the continued popularity of low-dose dopamine to influence renal dysfunction even though few data support it and editorials and reviews have discouraged its use. PURPOSE: To evaluate the effects of low-dose dopamine (< or =5 microg/kg of body weight per minute) compared with placebo or no therapy in patients with or at risk for acute renal failure. DATA SOURCES: MEDLINE (1966-January 2005), EMBASE (1980-week 5, 2005), CANCERLIT (1975-2002), CINAHL (1982-January 2005), and CENTRAL (The Cochrane Library, fourth quarter, 2004); bibliographies of retrieved publications; and additional information from 50 trials. STUDY SELECTION: Two reviewers independently selected parallel-group randomized and quasi-randomized controlled trials of low-dose dopamine versus control. DATA EXTRACTION: Study methods, clinical and renal physiologic outcomes, and adverse events (arrhythmias and myocardial, limb, and cutaneous ischemia) were extracted. DATA SYNTHESIS: 61 trials that randomly assigned 3359 patients were identified. Meta-analyses using random-effects models showed no effect of low-dose dopamine on mortality (relative risk, 0.96 [95% CI, 0.78 to 1.19]), need for renal replacement therapy (relative risk, 0.93 [CI, 0.76 to 1.15]), or adverse events (relative risk, 1.13 [CI, 0.90 to 1.41]). Low-dose dopamine increased urine output by 24% (CI, 14% to 35%) on day 1. Improvements in serum creatinine level (4% relative decrease [CI, 1% to 7%]) and measured creatinine clearance (6% relative increase [CI, 1% to 11%]) on day 1 were clinically insignificant. There were no significant changes on days 2 and 3 of therapy. LIMITATIONS: Statistically significant between-study heterogeneity in physiologic but not clinical outcomes was unexplained by prespecified hypotheses. CONCLUSION: Low-dose dopamine offers transient improvements in renal physiology, but no good evidence shows that it offers important clinical benefits to patients with or at risk for acute renal failure.
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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 | 0.023 | 0.054 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.046 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".