Sodium Bicarbonate for the Prevention of Contrast Induced-Acute Kidney Injury
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Infusion of sodium bicarbonate has been suggested as a preventative strategy but reports are conflicting on its efficacy. The aim of this study was to assess the effectiveness of hydration with sodium bicarbonate for the prevention of contrast-induced acute kidney injury (CI-AKI). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Medline, EMBASE, Cochrane library, and the Internet were searched for randomized controlled trials comparing hydration between sodium bicarbonate and chloride for the prevention of CI-AKI between 1966 and November 2008. Fourteen trials that included 2290 patients were identified. There was significant heterogeneity between studies (P heterogeneity = 0.02; I(2) = 47.8%), which was largely accounted for by trial size (P = 0.016). Trials were therefore classified by size. RESULTS: Three trials were categorized as large (n = 1145) and 12 as small (n = 1145). Among the large trials, the incidence of CI-AKI for sodium bicarbonate and sodium chloride was 10.7 and 12.5%, respectively; the relative risk (RR) [95% confidence interval (CI)] was 0.85 (0.63 to 1.16) without evidence of heterogeneity (P = 0.89, I(2) = 0%). The pooled RR (95% CI) among the 12 small trials was 0.50 (0.27 to 0.93) with significant between-trial heterogeneity (P = 0.01; I(2) = 56%). The small trials were more likely to be of lower methodological quality. CONCLUSIONS: A significant clinical and statistical heterogeneity was observed that was largely explained by trial size and published status. Among the large randomized trials there was no evidence of benefit for hydration with sodium bicarbonate compared with sodium chloride for the prevention of CI-AKI. The benefit of sodium bicarbonate was limited to small trials of lower methodological quality.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".