Colistin Nephrotoxicity: Meta-Analysis of Randomized Controlled Trials
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background Nephrotoxicity is a known adverse effect of polymyxin antibiotics, including colistin. Although previous meta-analyses have aimed to characterize colistin-associated nephrotoxicity risk relative to other antibiotics, included studies were observational in nature with high risk of confounding and heterogeneity. We conducted this systematic review and meta-analysis of exclusively randomized controlled trials (RCTs) to evaluate the incidence of nephrotoxicity associated with colistin versus minimally nephrotoxic antibiotics. Methods We searched PubMed, EMBASE, Cochrane Library, and 3 trial registries for RCTs comparing the nephrotoxicity of colistin to nonpolymyxin antibiotics. Randomized controlled trials that used aminoglycosides were excluded. Risk ratios (RRs) and 95% confidence intervals (CIs) were calculated using random-effects models. The study outcome was the rate of nephrotoxicity. Results Five RCTs with a total of 377 patients were included. Most patients received colistin for pneumonia in the intensive care unit, and the comparators were β-lactam-based regimens. Colistimethate sodium was dosed at 9 million units/day (300 mg/day of colistin base activity), with administration of a loading dose in 4 studies. The nephrotoxicity incidence in patients who received colistin was 36.2% (95% CI, 23.3% to 51.3%). The nephrotoxicity rate was significantly higher in the colistin arm than comparators (RR, 2.40; 95% CI, 1.47 to 3.91; P ≤ .001; I2 = 0%), and the number needed to harm was 5. Findings persisted upon one-study-removed-analysis. Conclusions This meta-analysis of RCTs found a colistin-associated nephrotoxicity rate of 36.2% and an increase in this risk compared with β-lactam-based regimens by 140%. Colistin should be regarded as a last-line agent and safer alternatives should be considered when possible.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 it